Journal of Intelligent & Fuzzy Systems - Volume 35, issue 6

Authors: Jo, Taeho

Article Type: Research Article

Abstract: This article proposes the modified KNN (K Nearest Neighbor) algorithm which receives a string vector as its input data and is applied to the text summarization. The results from applying the string vector based algorithms to the text categorizations were successful in previous works and the text summarization is able to be viewed into a binary classification where each paragraph is classified into summary or non-summary. In the proposed system, a text which is given as the input is partitioned into a list of paragraphs, each paragraph is classified by the proposed KNN version, and the paragraphs which are classified …into summary are extracted ad the output. The proposed KNN version is empirically validated as the better approach in deciding whether each paragraph is essential or not in news articles and opinions. We need to define and characterize mathematically more operations on string vectors for modifying more advanced machine learning algorithms. Show more

Keywords: String vector, semantic similarity, string vector based KNN, text summarization

DOI: 10.3233/JIFS-169841

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6005-6016, 2018

Authors: Kang, Jiyoung | Lim, Jongkuk | Kim, Changho

Article Type: Research Article

Abstract: In this study, we classified emotional responses of a user by measuring the physiological response signals with the Emotion Collector, which is a wearable band equipped with a multi-sensor device. We collected physiological signal data to measure the delicate hand movements, heart rate, and skin tension of the user analysis with a focus on picking out fear among the user’s emotions. In experiments classifying fear factors into five categories, we were able to identify the characteristics of the user’s physiological responses according to the type of fear. We were also able to find the similarities and differences of physiological and …psychological results for fear. The Emotion Collector is very easy to use, robust, and suitable for mobile and long-time logging of data. It can easily be integrated into other systems or applications. The system is designed for use in emotion research as well as in everyday affective applications such as user-centered service and content. Show more

Keywords: Wearable technology, emotion, fear, multi-sensor, physiological data

DOI: 10.3233/JIFS-169842

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6017-6023, 2018

Authors: Nguyen, Tuan-Linh | Kavuri, Swathi | Lee, Minho

Article Type: Research Article

Abstract: For the artificial intelligence (AI) to effectively mimic humans, understanding humans, more specifically, human emotion is important. Sentiment analysis aims to automatically uncover the underlying sentiment or emotions that humans hold towards an entity. There is high ambiguity of emotion in text data. In this paper, we consider the sentence-level sentiment classification task, and propose a novel type of convolutional neural network combined with fuzzy logic called the Fuzzy Convolutional Neural Network (FCNN) and its associated learning algorithm. The new model is an integration of modified Convolutional Neural Network (CNN) in the fuzzy logic domain. The proposed model benefits from …the use of fuzzy membership degrees to produce more refined outputs, thereby reducing the ambiguities in emotional aspects of sentiment classification. Also it benefits from extracting high-level emotional features due to convolutional neural representation. We compare the performance of our proposed approach with conventional CNN for sentiment classification. The experimental results indicate that the proposed FCNN outperforms the conventional methods for sentiment classification task. Show more

Keywords: Sentiment analysis, fuzzy logic, convolutional neural network, convolutional neuro-fuzzy network

DOI: 10.3233/JIFS-169843

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6025-6034, 2018

Authors: Hyun, Eugin | Jin, Young-Seok

Article Type: Research Article

Abstract: In this paper, we proposed a human-vehicle classification scheme using a Doppler spectrum distribution based on 2D Range-Doppler FMCW (Frequency Modulated Continuous Wave). Typically, because humans have non-rigid motion, multiple reflection points can appear on the Doppler spectrum. However, in the actual field, the Doppler spectrum distribution of a walking human is highly variable over time. Thus method using only this characteristic of the extended Doppler spectrum is limited with regard to human-vehicle classification. In order to improve the target classification performance, we designed two feature. The first is the Doppler spectrum extension features, which is expressed as the number …of Doppler reflection points with magnitudes exceeding reference threshold. Next, we defined the Doppler spectrum variance feature, which is extracted as the difference the reflection points between two successive frames. We can determine how the Doppler spectrum expands with the first feature, and how the Doppler spectra change based on the second feature. To verify the proposed target classification scheme, we measured real data using a 24 GHz FMCW transceiver on an actual road with various scenarios of walking humans and moving vehicles. From an analysis of the results, we confirmed that the thresholds effectively classify humans and vehicles based on the two proposed features. Finally, we verified that the results of the proposed classification scheme using the two features were much better than those using the first feature alone. Show more

Keywords: Automotive radar, feature extraction, pedestrian classification, radar recognition, FMCW radar

DOI: 10.3233/JIFS-169844

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6035-6045, 2018

Authors: Ahn, Hyunsik

Article Type: Research Article

Abstract: For interactions with humans, robots need the capability of describing the events they encountered for verbal communication. In this paper, a sentential cognitive system (SCS) using sentences as a media to represent cognized events for conversational human–robot interaction (HRI) is presented. The SCS comprising multiple modules such as perception and behavior, reasoning, and memory interprets modular events to sentential form from acquired cognitive information and a cognitive grammar linking it to sentences and vice versa. The sentences are stored in a sentential memory for being retrieved by reasoning procedures with the auxiliary memories, an object descriptor and a motion descriptor, …afterward for conversational HRI. In the experiment, the proposed SCS is implemented in a robot and tested with scenarios of spatiotemporal conversation about the handling of objects. The result shows the feasibility and efficiency of the proposed SCS for conversational HRI. Show more

Keywords: Intelligent robot, cognitive system, spatiotemporal reasoning, conversational robot, human–robot interaction

DOI: 10.3233/JIFS-169845

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6047-6059, 2018

Authors: Lee, DongSeop | Kim, MyoungHee | Na, IlKang

Article Type: Research Article

Abstract: The job/career matching has been ever increasingly important social issue in every country. The career matching is to assign the right candidate to the right company. The matching is passive process by employment counselor who cannot go through all profiles of candidates and also companies’ profiles. And there can be a human mistake assigning the wrong candidate to a wrong company. To minimize miss-matching cases, the paper investigates several statistical analysis methods and also proposes an artificial intelligence based method. In this paper, the method named Artificial Intelligence based Design platform (AID) has been developed for career matching between university …students and companies. The efficiency of AID has been proven by comparing the results (matching rate representing perfect matching) obtained by the proposed method AID and statistical methods such as least squares, Pearson correlation, Manhattan distance. The paper shows that AID can produce zero miss-matching for student’s skill and company’s needs while the statistical methods produce more than 30% miss-matching. In other words, AID can assign the right student to the right company. Show more

Keywords: Artificial intelligence, job/career matching, decision support, optimization

DOI: 10.3233/JIFS-169846

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6061-6070, 2018

Authors: Lee, Min-Hyuck | Yeom, Seokwon

Article Type: Research Article

Abstract: Recently, drone technology has developed rapidly for various purposes. A drone is very useful for aerial surveillance due to its remote sensing capability. Multiple target detection and tracking are essential to recognize any harmful threats in advance, however the image captured at a distance is easily degraded due to blurring and noise as well as low resolution. This paper addresses the detection and tracking of moving vehicles with drone imaging. A drone captures video sequences of multiple moving vehicles from a distance. Cars and buses are the objects of interests driving on urban roads. The detection step consists of frame …difference followed by thresholding and morphological operation considering the size of region of interest (ROI). The centroids of the ROI’s are considered measurements for tracking. Tracking is performed with interacting multiple model (IMM) filtering, which estimate the state of vectors and covariance matrices using multiple modes of Kalman filtering. The measurements in the validation region are associated with established tracks by the nearest neighbor rule. In the experiment, total seven moving cars and buses are captured at a long distance by a drone. It will be shown that the proposed method well detects the moving vehicles and achieves a good accuracy in estimating their locations. Show more

Keywords: Drone imaging, object detection, multiple target tracking, IMM filtering, frame difference

DOI: 10.3233/JIFS-169847

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6071-6078, 2018

Authors: Park, Young-Hoon

Article Type: Research Article

Abstract: With the development of intelligent vehicles, in-vehicle security and privacy receive considerable attention from researchers and drivers. The data stored in a vehicle control unit (VCU) may contain privacy-sensitive content, which may be exposed to unauthorized devices or attackers due to the structural problems of the in-vehicle network. To overcome this problem, data can be encrypted with the target module’s key before being transmitted to the in-vehicle network. However, this may lead to another efficiency problem. In this study, we propose a model that adopts the proxy re-encryption (PRE) scheme to the in-vehicle network. This is called privacy-enhancing in-vehicle …network key management (PINK). In the proposed model, the data stored in the VCU is encrypted with a master key. In addition, when the stored data is requested by a node, it is transformed into a ciphertext that can only be decrypted with the node’s key using the PRE scheme. Moreover, for the case in which a special group of nodes request the data several times, simultaneously, a group-based key management scheme i provided. Further it is demonstrated using simulations that the proposed PINK scheme can be efficiently applied to the in-vehicle network. Show more

Keywords: In-vehicle network, proxy re-encryption, privacy, key management

DOI: 10.3233/JIFS-169848

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6079-6087, 2018

Authors: Nguyen, Trong-Kha | Ly, Vu Duc | Hwang, Seong Oun

Article Type: Research Article

Abstract: Recent research in the computer security sector has primarily been qualitative, focusing on detection aspects where malware has already infected the target. Challenges for security vendors include developing better techniques for early detection of malware attacks before they can do malicious damage. Malware prediction models are needed that can describe and predict malware generation processes. In this study, we address the feasibility of quantitative characterization of malware in security assessment, we propose a model with aim to explain the mechanism behind malware generation which contributes to estimating malware discovery. Although several malware modeling systems have been proposed, such models have …shortcomings in related to historical data and do not consider malware data as a time series. Using time series analysis, we provide predictive neural network models for five datasets from Symantec and Malwr. The models explore the structures of malware data along with leveraging non-linear and linear properties to predict the number of future malware. Our examination also reveals that it is possible to model the malware discovery process using a neural network based non-linear model. In addition, our analysis provides insights into understanding the mechanisms that generate malware data series. This information can be useful for intelligence services and vital to threat assessment. Show more

Keywords: Time series forecasting, malware, neural network

DOI: 10.3233/JIFS-169849

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6089-6100, 2018

Authors: Maisen, Chakkraphop | Auephanwiriyakul, Sansanee | Theera-Umpon, Nipon

Article Type: Research Article

Abstract: The Mammographic image is a tool for observing breast cancer. Analyzing difficulties include shape, size variety, nearby tissue, and noise. In this paper, we propose a method to classify mammogram abnormalities based on learning vector quantization inference classifier (LVQIC) with fuzzy co-occurrence matrix (FCOM) textural features. The system is implemented on the Mini-MIAS data set with a 5-class problem, i.e., the classification of architectural distortion (AD), spiculated mass (SPIC), calcification (CALC), well-defined/circumscribed masses (CIRC), and normal (NORM). The implementation is also on a 2-class problem consisting of AD-vs-All, SPIC-vs-All, CALC-vs-All, CIRC-vs-All, and NORM/abnormal. The best blind test result is from …the 5-class problem with features from fuzzy co-occurrence matrix (FCOM) with 4 clusters, co-occurrence distance d  = 2, and 16 prototypes per class. The best classification result is 100% correct classification with 0.03, 0.04, 0.06, and 0.02 false positive rate for AD, SPIC, CALC, and CIRC, respectively. Show more

Keywords: Mammograms, breast cancer, breast abnormality detection, neuro fuzzy, feature selection

DOI: 10.3233/JIFS-169850

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6101-6116, 2018

Authors: Hwang, Seong Oun | Kim, Ki Hong | Lee, Hyun Jhin

Article Type: Research Article

Abstract: As office workers spend most of their time in front of computer monitors, they are at the risk of suffering from forward head posture syndrome. Repeated head forward postures may cause cervical discs. To address a precautionary approach for the syndrome, we propose a pervasive system. The purpose of this article is to identify design issues in pervasive computing when applied to forward head syndrome, which can give designers insights into how people interacts with the pervasive service and help shape a future research direction to cover those findings.

Keywords: Pervasive system, head posture, syndrome, pattern, prototype

DOI: 10.3233/JIFS-169851

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6117-6123, 2018

Authors: Eun, Seongbae | Jung, Jinman | Yun, Young-Sun | So, Sun Sup | Heo, Junyoung | Min, Hong

Article Type: Research Article

Abstract: IoT devices are diverse in their characteristics and made by many vendors, hence the inter-operation among them is difficult. Especially, end users can’t make their own programs by do-it-yourselves. IFTTT and Zapier platforms are designed to help end users to make them inter-operable easily and prevail in these days. Their approach is categorized into a Trigger-Action-Programming, in which trigger conditions and actions are already made by professional programmers of several IoT vendors and end users composite them into their own applications easily. But, their drawback is that the composition can be made at once in the first level, hence end …users can’t make more complicated applications. Our approach is based on a dataflow programming paradigm which resembles the TAP in that the internal actions are triggered when all the inputs of a node are prepared. In our approach, a composition of some atomic nodes becomes another atomic node, so the composition would continue iteratively. This feature is so generous that several visual programming languages like LabView are relied on the approach for various fields. We propose the overall architecture of our system and explain them. We also present Internet of Things examples of our approach, which shows that atomic dataflow objects can be associated to produce composite dataflow objects. And they are also composited to make more complex applications iteratively. We compare IFTTT, Zapier, and our approach qualitatively and show that end users can make more diverse and flexible applications in our approach. Show more

Keywords: Internet of Things(IoT), automatic programming, Trigger-Action-Programming, IF This Then That(IFTTT), dataflow approach

DOI: 10.3233/JIFS-169852

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6125-6131, 2018

Authors: Lee, Duckki | Helal, Sumi | Jung, Eunsung

Article Type: Research Article

Abstract: With the emergence of mobile and pervasive computing, digital gadgets and products have become a pervasive and of our lives. Everyday, they influence us explicitly or implicitly and are changing our way of life as well as our behaviors, either intentionally or unintentionally. Throughout the past decade, research has been conducted to make persuasion interactive rather than unilateral. The outcome is known today as persuasive computing technology. There have been considerable efforts to apply persuasive technology in many domains, especially healthcare. Although these efforts to are gradually coming to fruition, several problems and challenges remain. Most currently available persuasive systems …were not based on explicit theoretical foundations of persuasion theories and models when they were developed. There are two major reasons: (1) a general lack of theoretical frameworks and practical methodologies for building persuasive systems or applications, and (2) it is difficult for computer scientists and developers to understand and harness persuasion theories and models. In response, we have developed an Action-based Behavior Model (ABM) that can be utilized by computer scientists and developers. In this paper, we validate ABM through a scenario-based case, describing how it can be utilized in participatory telehealth to enable persuasion. Show more

Keywords: Persuasion-enabled telehealth, persuasive system, persuasive computing, smart health

DOI: 10.3233/JIFS-169853

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6133-6140, 2018

Authors: Teeyapan, Kasemsit | Theera-Umpon, Nipon | Auephanwiriyakul, Sansanee

Article Type: Research Article

Abstract: This paper presents a novel binary classifier based on two best fitting hyperellipsoids in the feature space, called twin-hyperellipsoidal support vector machine (TESVM). The idea of TESVM is inspired by the minimum volume covering ellipsoid together with twin-hypersphere support vector machine (THSVM) which is a variant of the well-known support vector data description (SVDD). Following the concept of THSVM, TESVM constructs two hyperellipsoids where each hyperellipsoid is closest to one class but also as far as possible from the other class in order to form a decision boundary. The construction of hyperellipsoids in the feature space is also enabled through …the use of empirical feature mapping. The experimental results on several artificial as well as standard real-world datasets are provided to demonstrate the performance of TESVM. Particularly, TESVM outperforms its spherical counterpart in term of classification accuracy. Show more

Keywords: Kernel minimum volume covering ellipsoid, twin-hyperellipsoid, twin hypersphere, empirical feature mapping

DOI: 10.3233/JIFS-169854

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6141-6152, 2018

Authors: Ko, First Moonbong | Kim, Seungcheon

Article Type: Research Article

Abstract: As the mobile communication evolves toward next generation, the 5th G, it was required that the number of base stations should be increased and the size of the base station should be reduced. In order for the base station to be designed in small size, we need to minimize the filters in the base station. There are couple of ways to reduce the size of the filters in the base station, one of which is to change the materials for the resonators of filter from the metal to ceramic. The ceramic resonator makes it possible to reduce the size of …the filter at the same time it would be difficult to get the performance as the metal resonator. In order to use ceramic resonator with the same characteristics as the metal resonator, we have to consider the sintering and the fabrication condition of ceramic resonator. This paper introduces the sintering and fabrication condition of ceramic resonator for the filter miniaturization. Show more

Keywords: RF filter, ceramic, resonator, miniaturization, sintered

DOI: 10.3233/JIFS-169855

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6153-6160, 2018

Authors: Bui, Trung Minh | Le, Duy Huu | Oscar Roberto, Saigua Labre | Kim, Wonha

Article Type: Research Article

Abstract: We present a new approach for generating thumbnail images from H.264/AVC coded bit streams. We have verified analytically that mismatch errors between the encoder and decoder prevent the direct generation of thumbnail images from H.264/AVC transform coefficients. Based on this analysis, we have devised a method that exploits both the spatial and transform domains. What distinguishes our algorithm from previous works is that it determines the thumbnail image pixels by summing the residual and estimate block averages. The residual block averages are directly acquired in the transform domain and the estimate block averages are calculated in the spatial domain. The …proposed method produces thumbnail images that are indistinguishable to the ones produced by the method that decodes the H.264/AVC-I slice bit streams and then scales them down, while, for most of images, it executes almost 3 times faster than the down-scaling method at frequently used bandwidths. Show more

Keywords: H.264/AVC, Intra prediction, Integer DCT

DOI: 10.3233/JIFS-169856

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6161-6172, 2018

Authors: Lee, Hyunmin | Kang, Sang-ug

Article Type: Research Article

Abstract: Personal content creation has become a significant part of the media industry, and sales are not necessarily the main objective of such creators. Individual creators have a greater need for privacy protection; therefore, the novel active content (AC) approach is proposed to address this need. The Intention Markup Language (InML) markup language is also introduced to express the content owner’s intentions systematically and precisely, and then to implement these as an executable code. To overcome the incompatibility and inconvenience of the existing digital rights management (DRM) systems, the novel AC format is proposed. This is based on the Portable Executable …(PE) format and consists of a PE header and sections, followed by an AC header, the content, and the intention code. The proposed content virtualization technique protects the content against a variety of attacks by treating content in main memory as if it were stored on the user’s storage. Since external players, beyond the AC control boundary, may potentially expose the content, these are controlled by hooking code included in the intention engine while the AC is in use. Finally, example use cases are presented to show how intentions can be expressed in InML documents and the creation and use of an AC file on Windows is demonstrated. Show more

Keywords: Active content (AC), privacy protection, intention markup language, personal content creation, content virtualization

DOI: 10.3233/JIFS-169857

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6173-6180, 2018

Authors: Seo, YoungKwang | Park, Geun-Ho | Kim, Wan-Jin | Kim, Hyoung-Nam

Article Type: Research Article

Abstract: A distance estimation method for hopping-frequency-coding (HFC)-based continuous wave (CW) is proposed herein. It is important to frequently update the distance estimate of a near-field underwater vehicle, robust to the time delay, Doppler effect, and volume reverberation. Frequency hopping ensures a high estimation accuracy of the wideband signal without being influenced by the Doppler effect, and also allows the receiver to update the target information at each frequency-hopping instance. The proposed algorithm, which is the initial algorithm for HFC-based CW, focuses on the update period of the estimates and real-time implementation rather than the optimization of estimation accuracy. To achieve …this goal, the proposed method exploits multiple Doppler correlators, a difference moving average filter, and four thresholds. The update period is inversely related to the hopping frequency, which is directly proportional to the Doppler frequency. As the target or transceiver moves at a high speed, the frequency-hopping period can be reduced, and the proposed algorithm can update the target information more frequently. Show more

Keywords: AUV, near-range SONAR, frequency hopping, real-time processing

DOI: 10.3233/JIFS-169858

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6181-6188, 2018

Authors: Choi, Yong Soo

Article Type: Research Article

Abstract: In the system security technology, the information hiding field is developed as technologies for embedding information into digital content as media. The proposed technique is a technical steganography technique which uses a technique of information hiding through physical / statistical change of signal of contents. In the digital watermarking or steganography technology, the embedding process is frequently performed in the frequency domain in order to increase the latent capacity and to improve the image quality. However, these methods have a disadvantage that the computation complexity is high and the constraint condition becomes complicated. In the contrast, there have been various …studies based on histogram shifting technology in reversible information hiding. Assume it selects multiple peaks on the histogram shifting, the capacity of data concealment gradually increased by applying multiple peak histogram method. The steganography technique using histogram shifting doesn’t show any significant improvement for the hiding capacity and image quality in the early methods. In this paper, we analyze the effect of information hiding technology in terms of adopting the histogram shift method including skipping. In addition, we propose 2n divergence data hiding as a complimentary technique to improve hiding capacity. The proposed method has been proven through an example using mathematical expressions, and further improvement measures could be derived. Show more

Keywords: Information hiding, histogram shifting, skipping, image retrieval, multi divergence

DOI: 10.3233/JIFS-169859

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6189-6195, 2018

Article Type: Other

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6197-6197, 2018

Authors: Mao, Wei-Lung | Suprapto,

Article Type: Research Article

Abstract: Nonlinear time series analysis and forecasting are an essential part in a diverse range of physical and natural applications. This paper presents a time-division cerebellar model articulation controller (TDCMAC) network using a modified biogeography-based optimization (modified BBO) learning algorithm for nonlinear time series and measurement data prediction. The TDCMAC method is a time windowing strategy constructed using the CMAC network. BBO algorithm is designed related to the geographical distribution of species over time and space. This study presents two modified migration functions of the essential BBO, i.e. quadratic migration BBO (QBBO) and sinusoidal migration BBO (SBBO) methods, to improve …convergence rate and quality of solution. Five nonlinear time series, including Mackey-glass, Lorenz, Rossler, Limber Pine, and Ponderosa Pine data series, are employed to investigate the proposed predictor. The TDCMAC networks using QBBO and SBBO learning algorithms are compared with the gradient descent (GD) method and other existing heuristic learning methods, including particle swarm optimization (PSO), genetic algorithm (GA), and conventional BBO methods, to verify the estimation performance of the proposed method. The performances are evaluated through an extensive simulation by computing the root mean square error (RMSE), mean absolute percentage error (MAPE), and average relative variance (ARV) metrics. Experimental results demonstrate that the proposed predictor indeed achieve more accurate performances and faster learning speed for time series prediction applications. Show more

Keywords: Time-division cerebellar model articulation controller (TDCMAC), Modified biogeography-based optimization, Nonlinear time series prediction, Mackey Glass time series, Lorenz time series, Rossler time series

DOI: 10.3233/JIFS-171120

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6199-6215, 2018

Authors: Yin, Shi | Li, Baizhou | Dong, Hengmin

Article Type: Research Article

Abstract: In recent decades, many multi-attribute decision-making methods have not been effectively applied to solve practical problems because of various shortcomings. The purpose of this paper is to develop a novel dynamic multi-attribute decision-making (DMADM) method based on the improved weights function and score function. In this paper, a novel method based on the improved entropy of interval-valued intuitionistic fuzzy sets is applied to calculate attribute weight. A time weight method is developed via the multi-target nonlinear programming model based on the ideal solution and information entropy. The influence of decision-makers’ subjective preference and objective attribute information are integrated into …the time weight. A novel ranking method based on the improved score function is used to select the best alternative in the DMADM process. Moreover, the interaction among attributes is considered by the interval-valued intuitionistic fuzzy geometric weighted Heronian means operator in the proposed method. Finally, an example of partner selection with collaborative innovation is given to verify the developed approach. This study contributes to the development of DMADM theory by using improved attribute weight, time weight, and score functions, and offers us a very useful way to deal with DMADM problems in real life. Show more

Keywords: Multi-attribute decision-making (MADM), attribute weight, time weight, score function, collaborative innovation

DOI: 10.3233/JIFS-171505

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6217-6227, 2018

Authors: Wen, Ta-Chun | Chang, Kuei-Hu | Lai, Hsin-Hung

Article Type: Research Article

Abstract: Personnel selection issues can be viewed as a complicated multicriteria decision-making (MCDM) problem. Choosing the most appropriate personnel directly influences an organization’s competitiveness and its sustainable development. Thus, the personnel selection problem is a critical issue for an organization’s success. However, such dilemmas involve quantitative and qualitative factors. Moreover, deciding on how to allocate limited resources toward cultivating talent increases the difficulty of personnel selection problems. This issue can not be solved effectively by arithmetic average-based methods. To address these issues, this paper combines the minimal variance order weighted averaging (OWA) operator and importance-performance analysis (IPA) to improve personnel selection. …The advantages of the proposed method can deal with quantity and qualitative factors simultaneously in the process of personnel selection, consider the ordered weights between assessment attributes, and establish an IPA grid to provide the reference for decision-making by the management. Finally, an empirical case study of selection of higher-education students is applied to illustrate our method. Compared with the arithmetic average and interval 2-tuple linguistic VIKOR methods, our results indicated that the proposed method generates a more accurate and reasonable ranking of personnel. Show more

Keywords: Decision analysis, human resource management, 2-tuple linguistic representation model, minimal variance OWA, importance performance analysis

DOI: 10.3233/JIFS-171686

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6229-6239, 2018

Authors: Su, Tai-Sheng | Wu, Chin-Chun | Yang, Huei-Ru

Article Type: Research Article

Abstract: The aims of this paper are to consider cost and energy consumption to solve overhead crane systems’ setting issues. The main issue is that cranes use higher frequency handling equipment in heavy industry. In the overhead crane system setting issues, the determining factors, such as cost, load and energy consumption, are fuzzy. Moreover, decision makers must simultaneously consider real-world conflicting multi-objectives. In summary the question involves a fuzzy multi-objectives problem. Therefore, this paper adopted fuzzy multi-objective programming to construct a mathematical model aimed at minimizing cost and energy consumption with reference to the crane load, recovery period and budget, to …carry out a crane system configuration. The model is used for a real problem to verify its correctness. Finally, this study provides a reference for decision makers to purchase crane device configurations. Show more

Keywords: Fuzzy multi-objective linear programming, overhead crane systems, energy consumption and cost, equipment assignment

DOI: 10.3233/JIFS-171763

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6241-6253, 2018

Authors: Moradi, Mojtaba | Hafezalkotob, Ashkan | Ghezavati, Vahidreza

Article Type: Research Article

Abstract: Sustainability is one of the most significant problems in today’s world and the concept of sustainable development is being an important objective in construction projects. Since the large projects have enormous and different activities that should be scheduled by considering resource constraint and precedence relationship between them, the resource-constrained project scheduling problem (RCPSP) is a NP-hard problem. In this study, fuzzy project scheduling model is presented to solve RCPSP under uncertainty in availability of the resources and activities duration simultaneously. Subcontractors have incentive to share their resources in the form of coalition in order to reduce activities time and cost. …In this research, cooperative game methods are introduced for fair allocating utility of the project, as well as, present supper-additivity, stability and satisfaction level of each coalition. Finally, sustainability concept is analyzed in RCPSP and cooperation of subcontractors in a coalition form, whereas in the previous researches these topics addressed separately or generally in project scheduling to minimize the makespan and maximize the profit of project. The results of the proposed model indicate that the subcontractors can obtain more profit and the balance between sustainability indicators in project management arises by collaboration. Show more

Keywords: Sustainability, fuzzy project scheduling, RCPSP, cooperative game theory, satisfaction level

DOI: 10.3233/JIFS-171821

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6255-6267, 2018

Authors: Senthilkumar, R. | Justin Sunil Dhas, G.

Article Type: Research Article

Abstract: Fractional order proportional, Integral and a derivative controller is a special kind of controller which is used to regulate the output voltage of a class of sepic converter to the desired level. Tuning of fractional Proportional, Integral and Derivative controller (FOPID) is achieved by different metaheuristic algorithm and the optimization performance target is chosen as minimizing the integral square error (ISE). This paper presents a performance analysis of Single Ended Primary Inductance Converter (SEPIC) by time response specifications such as rise time, settling time and steady-state error and further, the results are compared with the controllers designed by Genetic Algorithm …(GA), Particle Swarm Optimization (PSO) and Queen Bee based Genetic Algorithm (QBGA). The design and implementation of fractional order controller for a closed loop control of converter is done by utilizing a MATLAB/SIMULINK environment. Results show that QBGA algorithm exhibit better performance as compared to other optimization technique for voltage mode controller in terms of disturbance rejection. Show more

Keywords: SEPIC converter, fractional PID controller, GA, PSO, QBGA

DOI: 10.3233/JIFS-171892

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6269-6276, 2018

Authors: Owolabi, Taoreed O. | Gondal, Mohammed A.

Article Type: Research Article

Abstract: Laser induced breakdown spectroscopy (LIBS) is an excellent technique for analysis of solid and liquid samples. However there are inherent problems with concentration determination of elements present in the test sample with better accuracy. In order to address this challenge, hybrid fusion of extreme learning machine (ELM) and support vector regression (SVR) is proposed for the first time. Extreme learning machine (ELM) is a non-linear chemo-metric method which has inherent capacity to approximate any non-linear relation describing the laser induced plasma. However, ELM surfers from over-fitting which affects its accuracy for spectroscopic regression. On the other hand, SVR is a …non-linear chemo-metric tool based on statistical learning theory and overcomes the problem of over-fitting by proper tuning of its hyper-parameters. The merits of both chemo-metrics are harnessed in this work and implemented for quantitative analysis of LIBS spectra of seven standard bronze samples. The performance of ELM-SVR model which uses the output of ELM as its input is compared to that of SVR-ELM model which takes the output of SVR as its input. The hyper-parameters of the proposed models are optimized using gravitational search algorithm (GSA). On the bases of root mean square error (RMSE) as a measure of model performance, ELM-SVR performs better than SVR, ELM and SVR-ELM model with performance improvement of 95.76%, 89.33% and 52.71%, respectively. The accuracy of the proposed hybrid models would be of immense significance for quick quantitative analysis in LIBS and eventually promotes wide applicability of the technique. Show more

Keywords: LIBS spectra, extreme learning machine, gravitational search algorithm, support vector regression, quantitative analysis, hybrid model

DOI: 10.3233/JIFS-171979

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6277-6286, 2018

Authors: Heidari, S.V. | Soleymani, S. | Faghihi, F. | Mozaffari, B.

Article Type: Research Article

Abstract: The current study presents a new method for allocation of the contribution of voltage harmonic distortion for consumers and utilities. This method utilizes three-phase voltage and current waveforms at the point of common coupling (PCC) by applying an adaptive Kalman filter to estimate the amplitude and phase angle of the waveform. The fuzzy adaptation part of the Kalman filter allows resetting of the Kalman gain for fast tracking of system variations under transient conditions. Singular value decomposition based on recessive least square is used to estimate the Norton equivalent circuit for the entire system. In the proposed method an Indicator …of the voltage value is used to determine the contribution of harmonic distortion for both sides. The characteristics of the proposed method were investigated through simulation of a nonlinear load which is connected to the distribution system and practical data from 130 kV distribution system in north-west of Iran. Show more

Keywords: Harmonic component contributions, fuzzy system, kalman filter, distribution system

DOI: 10.3233/JIFS-172055

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6287-6299, 2018

Authors: Konwar, Nabanita | Davvaz, Bijan | Debnath, Pradip

Article Type: Research Article

Abstract: In this paper we study approximation properties (APs) and bounded approximation properties (BAPs) in the setting of intuitionistic fuzzy n -Banach spaces (IFnBSs). Further, we define strong intuitionistic fuzzy n -continuous and strong intuitionistic fuzzy n -bounded operators and using them we prove the existence of an IFnBS with AP. In addition, we provide examples which show that there exist IFnBSs with the AP which fail to have the BAP.

Keywords: Intuitionistic fuzzy n-Banach space; approximation property, bounded approximation property.

DOI: 10.3233/JIFS-181094

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6301-6312, 2018

Authors: Izhar, Muhammad | Khan, Asghar | Mahmood, Tariq

Article Type: Research Article

Abstract: The main motivation behind this paper is to study some structural properties of a non-associative structure Abel Grassmann’s groupoid (AG-groupoid) in terms of double-framed soft sets (DFS sets) as it hasn’t attracted much attention compared to associative structures. An AG-groupoid can be referred to as a non-associative semigroup, as the main difference between a semigroup and an AG-groupoid is the switching of an associative law. In this paper, we introduce the concept of (M , N )-double-framed soft ideals (briefly, (M , N )-DFS ideal) of AG-groupoids and investigate some properties of these notions. We have shown that every (M …, N )-DFS ideal is (M , N )-DFS AG-groupoid but the converse is not true. This is shown with the help of an example. We also discuss the properties of (M , N )-DFS ideals in regular AG-groupoids. Moreover a decision making algorithm based on DFS-sets is given. Show more

Keywords: DFS set, (M , N)-DFS AG-groupoids, (M , N)-DFS ideal, regular AG-groupoid, choice values, DFS-weighted set

DOI: 10.3233/JIFS-181119

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6313-6327, 2018

Authors: Zhang, Xuefeng | Su, Jiafu

Article Type: Research Article

Abstract: Solution selection plays an important role in crowdsourcing and is an imperative work for requesters. However, to the best of our knowledge, there is few studies focus on the problem of solution selection, especially in crowdsourcing contests for innovative tasks. This paper aims to develop a methodology incorporating quality function deployment (QFD) with 2-tuple linguistic method to assist requesters to select the right solution from a large pool of potential solutions efficiently. The methodology includes three phases. The first phase, i.e. pre-selection, is to screen potential solutions by employing the rule of non-compensatory. The second phase is to construct …relationships between requester’s requirements and solution features using quality function deployment (QFD), and further to determine the weights of solution features using 2-tuple linguistic weighted average operator and fuzzy weighted average method. The last phase is to evaluate the performance of potential solutions with respect to solution features, and further estimate their overall performance. Finally, an illustrative application case on the crowdsourcing platform-Taskcn is presented to demonstrate the implementation and effectiveness of the proposed approach. Show more

Keywords: Crowdsourcing contests, innovative tasks, solution selection, quality function deployment, 2-tuple linguistic method

DOI: 10.3233/JIFS-181122

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6329-6342, 2018

Authors: Hu, Bo | Bi, Lvqing | Dai, Songsong | Li, Sizhao

Article Type: Research Article

Abstract: A complex fuzzy set is a set whose membership grades are complex values in the unit circle in the complex plane. This paper introduces the concept of approximate parallelity between complex fuzzy sets based on the phase of complex-valued membership grade. After that, the property of approximate parallelity preserving for complex fuzzy operators and complex fuzzy inference are investigated.

Keywords: Approximate parallelity, approximate parallelity preserving, complex fuzzy sets, complex fuzzy operators, complex fuzzy inference

DOI: 10.3233/JIFS-181131

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6343-6351, 2018

Authors: Kutlu Gündoğdu, Fatma | Kahraman, Cengiz | Civan, Hatice Nida

Article Type: Research Article

Abstract: EDAS (Evaluation Based on Distance from Average Solution) is based on the distances of each alternative from the average solution. It is similar to other distance based multi-attribute decision-making methods such as TOPSIS and VIKOR. Hesitant fuzzy sets are an extension of ordinary fuzzy sets where the hesitation arises in the assignment of membership degrees of the elements to a fuzzy set. In this paper, we extend classical EDAS method to its hesitant fuzzy version in order to capture decision makers’ hesitancies. The proposed Hesitant Fuzzy Evaluation Based on Distance from Average Solution (HF-EDAS) is based on different aggregation operators …with defuzzification and without-defuzzification processes, which is presented by four HF-EDAS versions. The proposed method has been applied to a multi-criteria and multi-expert hospital selection problem for organ transplantation. Additionally, we present a comparative analysis with hesitant fuzzy TOPSIS (HF-TOPSIS). The results show that HF-EDAS selects the same best alternative as HF-TOPSIS. However, the proposed versions of HF-EDAS indicated some slight changes in the ranking of alternatives. Show more

Keywords: EDAS, multi-criteria decision making, hesitant fuzzy sets, service quality, hospital selection

DOI: 10.3233/JIFS-181172

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6353-6365, 2018

Authors: Daneshpayeh, Roohallah | Borumand Saeid, Arsham | Mirvakili, Saeed | Rezaei, Akbar

Article Type: Research Article

Abstract: In this paper, the notions of orthogonal, dense, regular, zero-divisor, strong and complemented elements in a pseudo BL-algebra are introduced and relation between the orthogonal and zero-divisor elements for perfect (good) pseudo BL-algebras is investigated. In particular, we get some results when a pseudo BL- algebra is good or perfect. Finally, a new characterization of these elements in a pseudo BL-algebra by a diagram is given.

Keywords: Pseudo BL-algebra, (Perfect, Primary) filter, radical, (Orthogonal, Dense, Regular, Zero divisor, Strong, Complemented) elements

DOI: 10.3233/JIFS-181218

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6367-6377, 2018

Authors: Mahapatra, Tanmoy | Pal, Madhumangal

Article Type: Research Article

Abstract: In this article, a new idea of fuzzy coloring of m -polar fuzzy graph is presented while establishing the relationship between chromatic number of m -polar fuzzy graph and it’s underlying crisp graph. Some properties of m -polar fuzzy graph and new concepts of independently strong edge and independently weak edge in m -polar fuzzy graph are proved. The differences between fuzzy coloring of fuzzy graph and m -polar fuzzy graph are discussed. It is also shown that a m -polar fuzzy graph can be decomposed into m fuzzy graphs. Again, from m isomorphic fuzzy graph one …can construct a m -polar fuzzy graph. A relation among chromatic numbers of m -polar fuzzy graph and m such graphs is established. Lastly a real life application of the fuzzy coloring is discussed. Show more

Keywords: m-polar fuzzy graph, α-strength cut graphs, independently weak edges, independently strong edges, chromatic number

DOI: 10.3233/JIFS-181262

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6379-6391, 2018

Authors: Davvaz, Bijan | Kim, Yong Chan

Article Type: Research Article

Abstract: In this paper, we introduce the concepts of Alexandrov L -neighborhood filters, Alexandrov L -topologies and Alexandrov L -convergence structures in complete residuated lattices. We investigate the Galois correspondences among Alexandrov L -neighborhood filters, Alexandrov L -topologies and Alexandrov L -convergence structures. Moreover, we investigate their topological properties and give their examples.

Keywords: Complete residuated lattices, Alexandrov L-topologies, Alexandrov L-neighborhood filters, Alexandrov L-convergence structures

DOI: 10.3233/JIFS-181295

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6393-6404, 2018

Authors: Hong, Jie | Qin, Xiansheng | Li, Jing | Niu, Junlong | Wang, Wenjie

Article Type: Research Article

Abstract: Over the past two decades, motor imagery brain-computer interface (MI-BCI) system has been extensively developed. In this system signal processing algorithms are critical to robust operation. In BCI community, however, there is no comprehensive review of the recent development of signal processing algorithms. Through analyzing the latest papers, signal processing algorithms of pre-processing, feature extraction, feature selection, and classification components are discussed in detail. Besides, post-processing and other existing problems are mentioned. The following key issues are addressed: (1) which components are the key of signal processing; (2) which signal processing algorithms are frequently used in each component; (3) which …signal processing algorithms attract more attention. This information can be used as reference and guidance for further research. Show more

Keywords: Motor imagery brain-computer interface (MI-BCI), signal processing algorithms, pre-processing, feature extraction, classification

DOI: 10.3233/JIFS-181309

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6405-6419, 2018

Authors: Prabhu, S. | Flora, T. | Arulperumjothi, M.

Article Type: Research Article

Abstract: Let G (V , E ) be a Graph. A set W ⊆ V of vertices resolves a graph G if every vertex of G is uniquely determined by its vector of distances to the vertices in W . The metric dimension of G is the minimum cardinality of a resolving set. By imposing different conditions on W we get conditional resolving sets. A resolving set W is said to be an independent resolving set if W contains isolated vertices. Independent resolving number denoted by ir (G) is referred to its …cardinality. In this paper we investigate independent resolving number for Titanium dioxide Nanotube. Show more

Keywords: Metric dimension, independent resolving set, independent resolving number, Titanium dioxide, Nanotube, Nanostructure

DOI: 10.3233/JIFS-181314

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6421-6425, 2018

Authors: Yang, Jinxin | Tang, Xiaoan | Yang, Shanlin

Article Type: Research Article

Abstract: Hesitant fuzzy set theory provides an effective technique for researchers and engineers to cope with vagueness and uncertainty. In recent years, to explore the correlation between hesitant fuzzy sets, traditional correlation measure in statistics has been constantly studied in hesitant fuzzy environments. In this study, extant studies of correlation measures in hesitant fuzzy contexts are recalled and analyzed. In view of the forgoing analysis, we find out that the extant correlation coefficients have some limitations. Moreover, a few correlation coefficients are not in line with the traditional definition of correlation coefficients. In order to address the flaws of the existing …proposals, a novel hesitant fuzzy correlation coefficient is proposed in this study. The new proposal of this study can not only overcome the flaws of the old hesitant fuzzy correlation coefficients, but it also shows several desirable characteristics. The weighted form of the newly defined correlation coefficient and its features are also investigated. Finally, three numerical examples concerning supplier selection and medical diagnosis are examined using the developed correlation coefficients to demonstrate their applicability. Comparison analyses with existing proposals highlight the efficiency of our proposals. Show more

Keywords: Correlation coefficient, hesitant fuzzy sets, decision making, supplier selection, medical diagnosis

DOI: 10.3233/JIFS-181393

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6427-6441, 2018

Authors: Rashmanlou, Hossein | Pal, Madhumangal | Borzooei, Rajab Ali | Mofidnakhaei, F. | Sarkar, Biswajit

Article Type: Research Article

Abstract: Theoretical concepts of graphs are highly utilized by computer science applications. Especially in research areas of computer science such as data mining, image segmentation, clustering, image capturing and networking. The interval-valued fuzzy graphs are more flexible and compatible than fuzzy graphs due to the fact that they have many applications in networks. In this paper, at first we define three new operations on interval-valued fuzzy graphs namely strong product, tensor product and lexicographic product. Likewise, we study about the degree of a vertex in interval-valued fuzzy graphs which are obtained from two given interval-valued fuzzy graphs using the operations Cartesian …product, composition, tensor and strong product of two interval-valued fuzzy graphs. These operations are highly utilized by computer science, geometry, algebra, number theory and operation research. In addition to the existing operations these properties will also be helpful to study large interval-valued fuzzy graph as a combination of small, interval-valued fuzzy graphs and to derive its properties from those of the smaller ones. Show more

Keywords: Cartesian product, composition, tensor product, lexicographic product

DOI: 10.3233/JIFS-181488

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6443-6451, 2018

Authors: Rivaz, Azim | Azizian, Mahdieh | Kamyad, Ali Vahidian | Zadeh, Somayeh Zangoei

Article Type: Research Article

Abstract: Mathematical modelling as a useful technique to obtain a better and wider perception of a complex biological subject such as cancer, has been increasingly applied in recent years. Since the parameters of a mathematical model are obtained by observations and measurements, they are exposed to errors and have uncertainty and ambiguity in their nature. In this paper, in order to achieve a more realistic mathematical model of tumor growth, a system of integro-partial differential equations which describes the growth of a tumor characterized by the presence of cancer stem cells - which are the main reason of treatment failure …and tumor relapse - is generalized to a fuzzy integro-partial differential system. Introducing some definitions, several theorems are proved to convert the fuzzy integro-partial differential system to an optimization problem. The proposed new method computes not only the approximate fuzzy solution of the full fuzzy system, but also the difference between the exact and approximate solution. It is further found that the tumor growth paradox appears in the full fuzzy mathematical model of tumor growth as well. Show more

Keywords: Fuzzy mathematical model, tumor growth model, stem cells, fuzzy integro-differential system, tumor growth paradox

DOI: 10.3233/JIFS-18261

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6453-6460, 2018

Authors: Ünver, Mehmet | Özçelik, Gökhan | Olgun, Murat

Article Type: Research Article

Abstract: The main goal of the present paper is to study the general structure and theoretical properties of a particular type of a fuzzy measure that can be used to model multi criteria decision making problems in which there exist some sub criteria. After constructing the general form of the non-additive set function, we deal with the interaction coefficient, Möbius representation and dual measure related to proposed measure. Finally, we are concerned with the usage of this type of fuzzy measures in multi criteria decision making problems in which at least one of the criteria contains some sub-criteria.

Keywords: Fuzzy measure, nonadditive measure, sub-criteria, multicriteria decision making, Möbius representation

DOI: 10.3233/JIFS-18396

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6461-6468, 2018

Authors: Kouahla, Zineddine | Anjum, Adeel | Seridi, Hamid

Article Type: Research Article

Abstract: Similarity search for content-based retrieval - a sustained problem; many applications endures. Most of the similarity measures intend focusing the least possible set of elements to find an answer. In the literature, most work is based on splitting the target data set into subsets using balls. However, in the era of big data, where efficient indexing is of vital importance, the subspace volumes grow exponentially, which could degenerate the index. This problem arises due to inherent insufficiency of space partitioning interlaced with the overlap factor among the regions. This affects the search algorithms thereby rendering these methods ineffective as it …gets hard to store, manage and analyze the aforementioned quantities. A good topology should avoid biased allocation of objects for separable sets and should not influence the structure of the index. We put-forward a novel technique for indexing; IMB-tree , which limits the volume space, excludes the empty sets; the separable partitions, does not contain objects and creates eXtended regions that will be inserted into a new index named eXtended index , implemented in a P2P environment. These can reunite all objects in one of the subsets-partitions; either in a separable set or in the exclusion set, keeping the others empty. We also discussed the efficiency of construction and search algorithms, as well as the quality of the index. The experimental results show interesting performances. Show more

Keywords: Indexing, eXtended region, parallel, metric space, complex data

DOI: 10.3233/JIFS-18398

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6469-6478, 2018

Authors: Qu, Guohua | Li, Tianjiao | Zhao, Xia | Qu, Weihua | An, Qianying | Yan, Junai

Article Type: Research Article

Abstract: In this paper, a stochastic decision making method based on regret theory and group satisfaction is proposed with unknown attribute weights and dual hesitant fuzzy elements. Considering that the decision makers have different levels of satisfaction with the alternatives, first of all, according to the score function and the accuracy function of dual hesitant fuzzy elements, a novel group satisfaction degree function of dual hesitant fuzzy elements is defined. And then, an attribute weight optimization model based on the new group satisfaction degree of dual hesitant fuzzy elements is established and the Lagrange function is constructed to obtain the attribute …weights. Secondly, on the basis of the regret theory, the regret and rejoice valued matrices of the program are given, and then the ranking values of each alternative can be obtained by combining with the weight of the attribute. Finally, a numerical example is given to illustrate the applicability and feasibility of the proposed method. Show more

Keywords: Dual hesitant fuzzy element, regret theory, group satisfaction degree, stochastic decision making

DOI: 10.3233/JIFS-18667

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6479-6488, 2018

Authors: Xu, Bingyuan | Zhou, Zhiheng | Chen, Xi | Yang, Yi | Yang, Zhiwei

Article Type: Research Article

Abstract: A new algorithm for static hand gesture recognition is proposed in this paper, which mainly includes the following four steps: hand segmentation, arm removal, feature extraction and gesture recognition. Firstly, the hand is extracted from the background by using skin-color features and geometric characteristics. Secondly, a new arm removal algorithm is proposed, which can effectively and quickly remove the arm area by using distance transformation operations, and gesture composed of palm and fingers can be obtained. Finally, Hu moments of the gesture image and the number of fingertips are calculated and entered into the Support Vector Machine (SVM) for …training. Experiments have been performed to demonstrate that the proposed algorithm is robust in complex background, and can detect and recognize gestures in real time with an accuracy of 94.89%. Show more

Keywords: Arm removal, static hand gesture recognition, distance transformation, SVM

DOI: 10.3233/JIFS-18681

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6489-6500, 2018

Authors: Moral-García, Serafín | Mantas, Carlos J. | Castellano, Javier G. | Abellán, Joaqu’ın

Article Type: Research Article

Abstract: Binary Relevance (BR) is a simple and direct approach to the Multi-Label Classification (MLC). It decomposes the multi-label problem into several binary problems, one per label. It uses an algorithm of traditional supervised classification in order to solve these binary problems. On the other hand, Credal C4.5 (CC4.5) is a modification of the classical C4.5. CC4.5 estimates the probability of the class variable by using imprecise probabilities. In the literature, this new classification algorithm has obtained better results than C4.5 when both have been applied on datasets with class noise. In MLC, since there are not just a class, but …multiple labels are disposed, it is more probable that there is intrinsic noise than in traditional classification. From the previous reasons, in this work it is studied the performance of BR using Credal C4.5 as base classifier versus BR with C4.5. It is carried out an experimental study with several muti-label datasets and a considerable number of measures for MLC. This study shows that the performance of BR is improved when it uses CC4.5 as base classifier versus BR with C4.5. In consequence, it is probably suitable to apply imprecise probabilities in Decision Trees within the MLC field too. Show more

Keywords: Multi-label classification, Binary Relevance, Credal C4.5, C4.5, imprecise probabilities

DOI: 10.3233/JIFS-18746

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6501-6512, 2018

Authors: Jin, Feifei | Ni, Zhiwei | Chen, Huayou | Langari, Reza | Zhu, Xuhui | Yuan, Hongjun

Article Type: Research Article

Abstract: The single-valued neutrosophic sets (SVNSs) are useful tools to describe uncertainty and inconsistent information that exist in real world. For SVNSs theory, two important topics are single-valued neutrosophic entropy and single-valued neutrosophic similarity measurer. This paper investigates a multi-attribute decision-making (MADM) method by using single-valued neutrosophic entropy and similarity measure. First, the concepts of single-valued neutrosophic entropy and similarity measure are presented. Then, based on the trigonometric functions (i.e., sine function and cosine function), we introduce two information measure formulas and prove that they satisfy the requirements of the single-valued neutrosophic entropy and similarity measure, respectively. Furthermore, we study the …inter-relationship between single-valued neutrosophic entropy and similarity measure. By using Lagrange Multiplier Method and closeness degree, we develop a novel single-valued neutrosophic MADM method. Finally, a numerical example of selecting the desirable supplier is provided, and the comparison with existing approaches is performed to validate the rationality and effectiveness of the proposed method. Show more

Keywords: Multi-attribute decision making, single-valued neutrosophic sets, entropy, similarity measure

DOI: 10.3233/JIFS-18854

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6513-6523, 2018

Authors: Li, Chengdong | Yan, Bingyang | Tang, Minjia | Yi, Jianqiang | Zhang, Xiqiao

Article Type: Research Article

Abstract: Traffic flow prediction can not only improve the reasonability of the managers’ decision-making and road planning effectively, but also provide helpful suggestions for travelers to avoid traffic congestion. In order to further improve the prediction accuracy of traffic flow, this study presents one data driven hybrid model for short-term traffic flow prediction. This hybrid model firstly extracts the periodicity pattern from the traffic flow data, then, constructs the functionally weighted single-input-rule-modules connected fuzzy inference system (FWSIRM-FIS) for the residual data after removing the periodicity pattern from the original data, and finally, generates the final prediction results through integrating the periodicity …pattern and the output from the FWSIRM-FIS model. The partial autocorrelation function (PACF) method is adopted to determine the optimal inputs for the data driven FWSIRM-FIS model, and the iterative least square method is utilized to train the parameters of the FWSIRM-FIS. Furthermore, three detailed experiments on traffic flow prediction are made, and comprehensive comparisons with three popular artificial intelligence methods are done to verify the effectiveness and advantages of the proposed hybrid model. According to five comparison indices, the proposed hybrid model can achieve the best prediction performance, although with much less fuzzy rules. The error histograms also verify that the proposed hybrid model has the smallest prediction errors comparing to the three comparative methods. The hybrid approach proposed in this study can also be extended to some other applications which have periodicity patterns, e.g. the traveling time estimate and the electricity load forecasting. Show more

Keywords: Traffic flow prediction, fuzzy method, single input rule module, least square learning, traffic-flow pattern

DOI: 10.3233/JIFS-18883

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6525-6536, 2018

Authors: Dian, Songyi | Liang, Weibo | Zhao, Tao

Article Type: Research Article

Abstract: Finite-time stability and stabilization problems for a class of interval type-2 (IT2) fuzzy time-delay systems are studied. In this paper, we extend the concept of finite-time stability to IT2 fuzzy time-delay systems. Based on the Lyapunov stability method, integral inequality and some advanced matrix inequalities, a sufficient condition is proposed to guarantee finite-time stability of IT2 fuzzy time-delay systems. Then, by virtue of the results on finite-time stability and Finsler’s lemma, we propose an IT2 fuzzy state feedback controller which can guarantee the closed-loop system is finite time stable. The problem of finite time stabilization can be solved with con …complementarity linearization iterative algorithm. Finally, two numerical examples are provided to verify the effectiveness of the proposed approach. Show more

Keywords: IT2 fuzzy systems, state feedback control, finite-time, time-delay

DOI: 10.3233/JIFS-18933

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6537-6549, 2018

Authors: Singh, Kuldeep | Singh, Shashank Sheshar | Kumar, Ajay | Biswas, Bhaskar

Article Type: Research Article

Abstract: Mining high utility itemsets (HUIs) is a basic task of frequent itemsets mining (FIM). In recent years, a trend in FIM has been to design algorithm for mining HUIs because FIM assumes that each item can not appear more than once in a transaction and all items have the same importance (weight, unit profit, price, etc.). However, in real-world, items appear more than once in a transaction and also have some importance. HUIs mining considers that items appear with some quantity and importance. Traditional HUIs mining algorithms assume that items have only positive unit profit. However, in real-world, items …may appear with negative unit profit also. For example, it is common that a retail store sells items at a loss to stimulate the sale of other related items or simply to attract customers to their retail location. Therefore, items occur with negative unit profit or negative utility. To consider negative unit profit, HUIs with negative utility has been introduced. This paper surveys recent studies on HUIs mining with negative utility and their applications. The main goal is to provide a survey of recent advancements and research opportunities. This paper presents key concepts and terminology related to HUIs mining with negative utility. This presents a taxonomy of all the algorithms consider negative utility. To the best of our knowledge, this is the first survey on the mining task of HUIs with negative utility. The paper also presents research opportunities and the challenges in HUIs mining problems. Show more

Keywords: High utility itemsets mining, utility mining, negative utility

DOI: 10.3233/JIFS-18965

Citation: Journal of Intelligent & Fuzzy Systems, vol. 35, no. 6, pp. 6551-6562, 2018