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The purpose of the Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology is to foster advancements of knowledge and help disseminate results concerning recent applications and case studies in the areas of fuzzy logic, intelligent systems, and web-based applications among working professionals and professionals in education and research, covering a broad cross-section of technical disciplines.
The journal will publish original articles on current and potential applications, case studies, and education in intelligent systems, fuzzy systems, and web-based systems for engineering and other technical fields in science and technology. The journal focuses on the disciplines of computer science, electrical engineering, manufacturing engineering, industrial engineering, chemical engineering, mechanical engineering, civil engineering, engineering management, bioengineering, and biomedical engineering. The scope of the journal also includes developing technologies in mathematics, operations research, technology management, the hard and soft sciences, and technical, social and environmental issues.
Authors: Cosme, Luciana Balieiro | D’Angelo, Marcos Flávio Silveira Vasconcelos | Caminhas, Walmir Matos | Camargos, Murilo Osorio | Palhares, Reinaldo Martínez
Article Type: Research Article
Abstract: The traditional Interacting Multiple Model (IMM) filters usually consider that the Transition Probability Matrix (TPM) is known, however, when the IMM is associated with time-varying or inaccurate transition probabilities the estimation of system states may not be predicted adequately. The main methodological contribution of this paper is an approach based on the IMM filter and retention models to determine the TPM adaptively and automatically with relatively low computational cost and no need for complex operations or storing the measurement history. The proposed method is compared to the traditional IMM filter, IMM with Bayesian Network (BNs) and a state-of-the-art Adaptive TPM-based …parallel IMM (ATPM-PIMM) algorithm. The experiments were carried out in an artificial numerical example as well as in two real-world health monitoring applications: the PRONOSTIA platform and the Li-ion batteries data set provided by NASA. The Retention Interacting Multiple Model (R-IMM) results indicate that a better prediction performance can be obtained when the TPM is not properly adjusted or not precisely known. Show more
Keywords: Adaptive systems, dynamic systems, filtering techniques, markov models, system state estimation
DOI: 10.3233/JIFS-201129
Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 155-166, 2021
Authors: An, Jiangfeng | Wu, Jun | Zheng, Penghua | Pan, Ying | Zhou, Xuejie | Yang, Mingshu
Article Type: Research Article
Abstract: The environmental adaptabilities of low-density polyethylene (LDPE) play an important role for high-speed trains’ reliability and comfort. The weathering of LDPE depends on environment factors, while the complexity of the weathering processes inhibits the evaluation of environmental weathering risks. To elucidate the correlation between weathering and environmental factors, and to predict the weathering risk of target areas of interest, three-year-long natural weathering tests were conducted at twelve natural exposure stations in China. Properties of weathered LDPE were compared and analysed using factor analysis. The fuzzy recognition method based on analytic hierarchy process (AHP) was established and used to predict the …weathering risk based on environmental database. The results indicate that the factor scores can partitioned the atmospheric environments into five weathering risk grades. This article used the accumulated cumulative temperature of the daily maximum temperature for weathering risk evaluation, which is more scientific than the annual average temperature widely used and is useful for revealing the difference in LDPE weathering in Turpan and Korla. A comparative chart of LDPE’s weathering risk in China was established by this fuzzy recognition method for the first time, which caters to the continuous extension of high-speed railway to new regions. Show more
Keywords: Weathering risk, fuzzy recognition, factor analysis, accumulated temperature, low-density polyethylene
DOI: 10.3233/JIFS-201201
Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 167-179, 2021
Authors: Alli, P. | Dinesh Peter, J.
Article Type: Research Article
Abstract: The day-to-day progress in communication plays a vital role in transmitting millions and trillions of data through the unsecured network channels. It creates a way where the user’s data becomes the victim of various security threats. Among those users’ data, images act as primary data, and its encryption security methodologies are fascinating. The conventional encryption techniques don’t work well against the various other hidden security threats but require substantial computational time and cost with poor permutation performance. Hence to deal with this, an auto-encoder induced DNA (Deoxyribonucleic acid) sequence via chaotic image encryption framework is designed in our proposed work. …It integrates the properties of DNA encoding and the chaotic maps to handle the data losses effectively and resist several attacks such as statistical attacks, chosen-plaintext attacks, etc. Moreover, an auto-encoder is used to control the data noises, thereby ensuring a better encryption performance. Here, the auto-encoder is activated to generate a permuted image with less time complexity and noise. A secret key is then initialized with the aid of SHA-256. Finally, image encryption and decryption are achieved, followed by the successful transmission of data over a digital network. The performance of the proposed work is analyzed with varied metrics to strengthen its efficiency over the prior techniques. Show more
Keywords: Permuted image, SHA-256, DNA computing sequence, stacked auto-encoder, chaos based image encryption
DOI: 10.3233/JIFS-201224
Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 181-198, 2021
Authors: Shahri, Majid Mardani | Jahromi, Abdolhamid Eshraghniaye | Houshmand, Mahmoud
Article Type: Research Article
Abstract: The purpose of maintenance is to ensure the maximum efficiency and availability of production assets at optimal cost considering quality, safety, and environmental aspects. Assets criticality analysis is one of the main steps in many maintenance methodologies, including Reliability Centered Maintenance. The present study seeks to provide a solution for determining critical assets for more efficient maintenance management. In this regard, an integrated approach of the analytical hierarchy process and fuzzy inference system was proposed based on the concept of the risk matrix. According to the concept of the risk matrix, two main criteria of failure consequences and probability were …employed to determine assets criticality. Analytic Hierarchy Process (AHP) was used to consider all sub-criteria of failure consequences and probability. Finally, using two main criteria as inputs, a fuzzy inference system was developed to determine the criticality of the assets. The proposed approach was implemented in a gas refinery; the results showed its effectiveness and applicability in the process of prioritizing assets based on criticality criteria. The proposed approach has the advantages of multi-criteria decision-making techniques, modeling ambiguity and uncertainty in real issues, modeling the process of inference in the human mind, and storing the knowledge of the organization’s expert. Show more
Keywords: Assets criticality analysis, maintenance management, fuzzy inference system, risk matrix, analytical hierarchy process
DOI: 10.3233/JIFS-201407
Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 199-217, 2021
Authors: Nishanthini, Radhakrishnan | Jeyabalan, Ramasamy | Balasundar, Samipillai | Kumar, Gurunathan
Article Type: Research Article
Abstract: The conception of magic labeling in fuzzy graphs elongates to fuzzy vertex magic labeling together with consecutive non-integer values in (0, 1] and the graph’s repercussion is named as fuzzy consecutive vertex magic labeling graphs (FCVM) along with the z -index. In this manuscript, we give some properties associated with FCVM labeling along with z -index as well as the presence of FCVM labeling with z -index in trees and some generalizations. Moreover, we examine the FCVM labeling along with z -index of both regular and irregular graphs. Finally, in real-time applications, we bestow an instance for fuzzy consecutive vertex …magic labeling graphs. Show more
Keywords: Fuzzy vertex magic, fuzzy consecutive vertex magic, comb graph, generalized butterfly graph, generalized peterson graph
DOI: 10.3233/JIFS-201489
Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 219-230, 2021
Authors: Fu, Wenqing | Khalil, Ahmed Mostafa | Zahran, Ahmed Mohamed | Basheer, Rehab
Article Type: Research Article
Abstract: The aim of this article is to present the concept of restricted union and extended intersection of belief interval-valued soft sets, along with its properties. In addition, we propose the concept of possibility belief interval-valued soft set theory and investigate their properties. For suitability of possible applications, there are seven kinds of operations (e.g., union, intersection, restricted union, extended intersection, complement, soft max-AND, and soft min-OR) on the possibility belief interval-valued soft sets are defined and their basic theoretical are given. Then, we construct two algorithms by using soft max-AND and soft min-OR operations of possibility interval-valued soft sets for …fuzzy decision-making problem. Lastly, we introduce an algorithm using a possibility interval-valued soft set to solve the decision-making problems and clarify its applicability by a numerical example. Show more
Keywords: Interval-valued fuzzy set, belief interval-valued soft set, possibility belief interval-valued soft set, decision-making
DOI: 10.3233/JIFS-201621
Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 231-249, 2021
Authors: Berenjian, Golnaz | Motameni, Homayun | Golsorkhtabaramiri, Mehdi | Ebrahimnejad, Ali
Article Type: Research Article
Abstract: Regarding the ever-increasing development of data and computational centers due to the contribution of high-performance computing systems in such sectors, energy consumption has always been of great importance due to CO2 emissions that can result in adverse effects on the environment. In recent years, the notions such as “energy” and also “Green Computing” have played crucial roles when scheduling parallel tasks in datacenters. The duplication and clustering strategies, as well as Dynamic Voltage and Frequency Scaling (DVFS) techniques, have focused on the reduction of the energy consumption and the optimization of the performance parameters. Concerning scheduling Directed Acyclic Graph …(DAG) of a datacenter processors equipped with the technique of DVFS, this paper proposes an energy- and time-aware algorithm based on dual-phase scheduling, called EATSDCDD, to apply the combination of the strategies for duplication and clustering along with the distribution of slack-time among the tasks of a cluster. DVFS and control procedures in the proposed green system are mapped into Petri net-based models, which contribute to designing a multiple decision process. In the first phase, we use an intelligent combined approach of the duplication and clustering strategies to run the immediate tasks of DAG along with monitoring the throughput by concentrating on the reduction of makespan and the energy consumed in the processors. The main idea of the proposed algorithm involves the achievement of a maximum reduction in energy consumption in the second phase. To this end, the slack time was distributed among non-critical dependent tasks. Additionally, we cover the issues of negotiation between consumers and service providers at the rate of μ based on Green Service Level Agreement (GSLA) to achieve a higher saving of the energy. Eventually, a set of data established for conducting the examinations and also different parameters of the constructed random DAG are assessed to examine the efficiency of our proposed algorithm. The obtained results confirms that our algorithm outperforms compared the other algorithms considered in this study. Show more
Keywords: Green service level agreement, hroughput, dynamic voltage and frequency scaling, energy-aware scheduling, slack-time distribution, petri nets
DOI: 10.3233/JIFS-201696
Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 251-272, 2021
Authors: Sindhu, Muhammad Sarwar | Rashid, Tabasam | Kashif, Agha
Article Type: Research Article
Abstract: Aggregation operators are widely applied to accumulate the vague and uncertain information in these days. Hamy mean (HM) operators play a vital role to accumulate the information. HM operators give us a more general and stretchy approach to develop the connections between the arguments. Spherical fuzzy sets (SpFSs ), the further extension of picture fuzzy sets (P c FSs ) that handle the data in which square sum of membership degree (MD), non-membership degree (NMD) and neutral degree (ND) always lie between closed interval [0, 1]. In the present article, we modify the HM operators like spherical fuzzy HM …(S p FHM ) operator and weighted spherical fuzzy HM (WS p FHM ) operator to accumulate the spherical fuzzy (S p F ) information. Moreover, various properties and some particular cases of S p FHM and the WS p FHM operators are discussed in details. Also, to compare the results obtained from the HM operators a score function is developed. Based on WS p FHM operator and score function, a model for multiple criteria decision-making (MCDM) is established to resolve the MCDM problem. To check the significance and robustness of the result, a comparative analysis and sensitivity analysis is also performed. Show more
Keywords: Spherical fuzzy sets, MCDM, linear programming model, Hamy mean operator
DOI: 10.3233/JIFS-201708
Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 273-298, 2021
Authors: Masood, Naveen | Farooq, Humera
Article Type: Research Article
Abstract: Most of the electroencephalography (EEG) based emotion recognition systems rely on single stimulus to evoke emotions. EEG data is mostly recorded with higher number of electrodes that can lead to data redundancy and longer experimental setup time. The question “whether the configuration with lesser number of electrodes is common amongst different stimuli presentation paradigms” remains unanswered. There are publicly available datasets for EEG based human emotional states recognition. Since this work is focused towards classifying emotions while subjects are experiencing different stimuli, therefore we need to perform new experiments. Keeping aforementioned issues in consideration, this work presents a novel experimental …study that records EEG data for three different human emotional states evoked with four different stimuli presentation paradigms. A methodology based on iterative Genetic Algorithm in combination with majority voting has been used to achieve configuration with reduced number of EEG electrodes keeping in consideration minimum loss of classification accuracy. The results obtained are comparable with recent studies. Stimulus independent configurations with lesser number of electrodes lead towards low computational complexity as well as reduced set up time for future EEG based smart systems for emotions recognition Show more
Keywords: Common spatial pattern (CSP), electrodes selection, electroencephalography (EEG), emotion recognition, feature extraction, genetic algorithm
DOI: 10.3233/JIFS-201779
Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 299-315, 2021
Authors: Li, Shugang | Wang, Ru | Zhang, Yuqi | Lu, Hanyu | Cai, Nannan | Yu, Zhaoxu
Article Type: Research Article
Abstract: Identifying potential social media influencers (SMIs) accurately can achieve a long-time and effective concept marketing at a lower cost, and then promote the development of the corporate brand in online communities. However, potential SMIs discrimination often faces the problem of insufficient available information of the long-term evolution of the network, and the existing discriminant methods based on link analysis fail to obtain more accurate results. To fill this gap, a consensus smart discriminant algorithm (CSDA) is proposed to identify the potential SMIs with the aid of attention concentration (AC) between users in a closed triadic structure. CSDA enriches and expands …the users’ AC information by fusing multiple attention concentration indexes (ACIs) as well as filters the noise information caused by multi-index fusion through consensus among the indexes. Specifically, to begin with, to enrich the available long-term network evolution information, the unidirectional attention concentration indexes (UACIs) and the bidirectional attention concentration indexes (BACIs) are defined; next, the consensus attention concentration index (CACI) is selected according to the principle of minimum upper and lower bounds of link prediction bias to filter noise information; the potential SMI is determined by adaptively calculating CACI among the user to be identified, unconnected user group and their common neighbor. The validity and reliability of the proposed method are verified by the actual data of Twitter. Show more
Keywords: Concept marketing, social media influencers, attention concentration index, consensus smart discriminant algorithm
DOI: 10.3233/JIFS-201809
Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 1, pp. 317-329, 2021
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