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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: Wu, Yan | Wang, Ling-ying | Fang, Yiling
Article Type: Research Article
Abstract: Smart city refers to the use of various information technologies to integrate urban systems and services so as to improve the efficiency of resource utilisation and improve the quality of life for citizens. For many activities related to smart cities, such as the selection of pilot cities, a large number of experts from different functionalities or departments are usually invited to make evaluations of multiple attributes. The wide-spanning nature of smart cities needs cross-functional integration of various types of expertise. Therefore, it is necessary to develop a multi-criteria large group decision-making model to gather expert opinions from a wide range …of sources to solve these problems. To do this, we first use the simple and fast algorithm for K-medoids clustering to classify experts into different subgroups and thereby reduce the complexity of the decision-making problem. Subgroup leaders will be selected at the same time to represent subgroups in subsequent decision-making processes. We then use the DEMATEL method to determine the weights of attributes. Next, to ensure that the decision outcome is supported by the majority of experts, a consensus-reaching process is proposed to reduce discrepancies in opinions. An illustrative example is adopted which involves the selection of pilot cities in Sichuan Province in order to verity the applicability of the model. Comparative analyses will be provided to verify the advantages of the proposed model. The results show that our model can effectively address evaluation problems associated with smart city activities involving a large group of experts. Show more
Keywords: Smart cities, multi-criteria large group decision making, subgroup leader, consensus
DOI: 10.3233/JIFS-213267
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 1, pp. 1383-1398, 2022
Authors: Cai, Yi | Guo, Jinlu | Tang, Zhenpeng
Article Type: Research Article
Abstract: The regularly issued low frequency data, such as the change of fund position (weekly), and Producer Price Index (monthly), can affect the subsequent trend of stock returns. However, the forecasting effect of low frequency data on high frequency has not been discussed amply. This paper proposes a new mixed frequency neural network that helps to fill this research gap. The original time series is decomposed into several components through ensemble empirical mode decomposition, then the frequency alignment method is applied to integrate the high frequency component with low frequency variable as inputs, and the CNN-BiLSTM-Attention network completes the remaining forecasting …work. The empirical results show that compared with other benchmark models, the proposed procedures perform better when predicting the high frequency components and obtain a smaller statistical error in the final ensemble results. The proposed model has great potential for the forecasting of reverse mixed time series. Show more
Keywords: Stock returns, Ensemble empirical mode decomposition, Deep learning, Attention mechanism, Mixed frequency prediction
DOI: 10.3233/JIFS-213276
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 1, pp. 1399-1415, 2022
Authors: Ngoc, Vo Truong Nhu | Viet, Do Hoang | Tuan, Tran Manh | Hai, Pham Van | Thang, Nguyen Phu | Tuyen, Do Ngoc | Son, Le Hoang
Article Type: Research Article
Abstract: Periapical Inflammation (PI) is one of the most popular diseases in adults due to complication of endodontitis or dental trauma with corresponding consequences to quality-of-life like tiredness and signs of infection. Specifically, patients having severe PI are often tiredness and high fever accompanied by signs of infection such as dry lips, dirty tongue, lymph node reaction in the area under the jaw. In X-Ray images, PI could be recognized by vague boundaries with signs of periapical ligament extensions. It is necessary to design a computerized diagnosis system based on the Deep Learning models for supporting clinicians in diagnosis of PI …from X-Ray images. In this paper, we propose a new medical system called VNU for diagnosis of PI from X-Rays images. The VNU system uses Deep Learning to classify whether X-Ray images being PI or not. The Residual Neural Network (ResNet) with 34 layers is utilized with proper data augmentation and learning algorithms. The system is designed based on 7-layer enterprise architecture (User, Business, Application, Data, Technology, Infrastructure, and Security). It is used by both the clinicians and IT operators. The system has been validated on real data from Hanoi Medical University, Vietnam consisting of 900 images with PI and 500 normal images. Two scenarios of validation namely hyperparameter selection and performance comparison with other CNN-based Deep Learning models have been performed. It has been found from the experiments that the proposed system has better performance than the others in terms of sensitivity and specificity with the corresponding values of 96.70% and 93.87%. The system is deployed on the web interface that offers flexibility for clinicians in diagnosis and training. Show more
Keywords: Apical lesions, periapical radiograph, ResNet, deep learning, VNU system
DOI: 10.3233/JIFS-213299
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 1, pp. 1417-1427, 2022
Authors: Khan, Vakeel A. | Ali Khan, Izhar | Esi, Ayhan | Alam, Masood
Article Type: Research Article
Abstract: The main purpose of this paper is to introduce invariant convergence in intuitionistic fuzzy normed space. Following which we present some characteristics of this notion with respect to intuitionistic fuzzy norm. We also define strongly invariant convergence, ideal invariant convergence and invariant ideal convergence in intuitionistic fuzzy normed space. After that, we establish the relationship between these notions with respect to intuitionistic fuzzy norm. Lastly, we define ideal invariant Cauchy and invariant ideal Cauchy criteria for sequences in intuitionistic fuzzy normed space and relate it to their convergence notion.
Keywords: Intuitionistic fuzzy normed space, Ideal convergent, Invariant mean
DOI: 10.3233/JIFS-213327
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 1, pp. 1429-1438, 2022
Authors: Radhika, K. | Arun Prakash, K.
Article Type: Research Article
Abstract: Multi-objective optimization is an emerging field concerning optimization problems associated with more than one objective function, each of them has to be optimized simultaneously. Multi-objective optimization is widely used in logistics and supply chains to reduce the cost and time involved in transportation. With the increase in Global Supply Chains, many organizations are facing the challenges of delivering products to their customers at a fast pace, low cost, and high reliability. There are numerous factors that may affect the goal of an organization to optimize the cost, time, and effort during the transportation of their products to the end customers. …For instance, in the existing transportation problems, the type of vehicles used for the movement of the products is not focused. Transportation of the goods is considered to utilize any type of vehicle irrespective of the nature of the goods. However, in real-life scenarios, there are certain constraints in the vehicle used to transport the finished goods or raw materials from a source to a destination. Vehicles such as tanker trucks, top open trucks, closed trucks, etc. need to be booked based on the nature of goods to be transported. Also, the cost and time of transportation are uncertain in nature. In this paper, we formulate the Multi-Objective Solid Transportation Problem (MOSTP) by considering the above issue. The uncertain parameters of the problem are considered as Pentagonal Intuitionistic Fuzzy Numbers (PIFN). Magnitude method is used for defuzzification. An algorithm to find the solution of formulated Intuitionistic Fuzzy Multi-Objective Solid Transportation problem (IFMOSTP) is provided. The proposed model is illustrated by a numerical example which is solved with the help of LINGO software. Show more
Keywords: Intuitionistic fuzzy sets, intuitionistic fuzzy numbers, magnitude ranking, multi-objective solid transportation problems, fuzzy programming
DOI: 10.3233/JIFS-213517
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 1, pp. 1439-1452, 2022
Authors: Ramachandran, Lakshmanan | Mohan, Veerasamy
Article Type: Research Article
Abstract: Image segmentation is an essential part of almost any image processing methodology and it play a critical role in protecting the region of interest on any substrate image before its actual analysis is prescribed. In fact, the accuracy of any processing done by image segmentation will largely depends on the efficiency of the segmentation algorithm employed. A typical segmentation method employing a important features of Canny–GLCM (Gray Level Co-occurrence Matrix) incorporated with a simple Artificial Neural Network (ANN) model is proposed in this research work for segmentation of shrimp variability. Performance metrics related to accuracy have been compared with benchmark …of this method, and the sensitivity of efficiency level has been described. The segmentation in the proposed research work is targeted towards Penaeus Monodon (PM), and Litopenaeus Vannamei (LV) diversities for main threats detection of White Spot Syndrome (WSS). The proposed model has better performance metrics, such as (94.67%), sensitivity (94.79%), specificity (94.51%) and positive predictive (94.79%) while compared to other existing methods. Show more
Keywords: Image segmentation, white spot syndrome, gray level cooccurence matrix, neural network, detection accuracy
DOI: 10.3233/JIFS-220172
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 1, pp. 1453-1466, 2022
Authors: Jin, Xin
Article Type: Research Article
Abstract: With the development of the Internet and mobile networks, social networks have gradually become an essential tool and widespread application. Therefore, the research on short text semantic modelling of social networks has attracted widespread attention. However, modelling short texts encounter the semantics sparsity and multiple meanings of a word in social networks. To solve the above problems, we propose a user-based topic model with topical word embeddings semantic modelling method, namely SM-UTM. Firstly, we construct the user topic model to aggregate short text. Secondly, we build word pair in the user topic model to alleviate semantics sparsity in social networks. …In addition, we introduce the time information of social networks into the topic model to jointly constrain the generation process of topics, to improve the quality of semantic representation of social network short texts. Finally, we use the topic word embedding learning based on deep learning to train and optimize the word vector according to the learning results of the user topic model, to alleviate the problem of polysemy in social networks. We build multiple groups of quantitative and qualitative experiments based on the crawled real Sina Weibo data. The experimental results show that our SM-UTM is significantly better than the comparison method in the evaluation indicators of topic consistency, purity and entropy. Show more
Keywords: Topic model, topical word embeddings, social network, semantic modelling, semantics sparsity
DOI: 10.3233/JIFS-212614
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 1, pp. 1467-1480, 2022
Authors: Mariappan, Gengaraj | Lakshmanan, Kalaivani
Article Type: Research Article
Abstract: In this manuscript, a hybrid technique is proposed for Torque Ripple (TR) minimization of Switched Reluctance Motor (SRM). The proposed technique is the consolidation of Wingsuit flying search (WFS) optimization and Gradient Boosting Decision Tree (GBDT) algorithm, hence it is known as WFS-GBDT technique. The control mechanisms consists of fractional order proportional integral derivative (FOPID) speed controller on external loop as well as current controller on internal loop with controlling turn activate and deactivate angles for SRM. The complexity of acquiring the ideal evaluation of proportional, integral and derivative gains for speed and current controller including turn activate and deactivate …angles are deemed as a multi-objective optimization issue. Here, the WFS optimize the gain parameters of external speed loop along internal current loop with commutation angles for turn activate and deactivate switches. The WFS optimization processing is used to productive machine learning dataset under the types of SRM parameter. By using the satisfied dataset, the GBDT is predicted and mandatory forecasting is implemented in the entire machine operating stage. The optimized gain parameters based, the fractional order proportional integral derivative controller is tuned exactly. The proposed WFS-GBDT control technique lessens the torque ripple and quick settling time with this proper control, because of its systematic random search capabilities, thereby enhancing the dynamic execution of SRM drive. Finally, the proposed technique is activated in MATLAB/Simulink site, its performance is analyzed with existing techniques, like Base, ALO and WFS. The best, worst, mean, standard deviation for ISEspeed using proposed technique attains 230.5364, 231.5934, 230.952 and 0.05314. The best, worst, mean and standard deviation for torque ripple using proposed technique attains 0.4571, 0.6548, 0.585 and 0.472. The best, worst, mean, standard deviation for ISEcurrent using proposed technique attains 3.1257, 3.9754, 3.5783 and 0.0472. Show more
Keywords: Switched reluctance motor, torque ripple minimization, speed, current, gain parameters and dynamic efficiency
DOI: 10.3233/JIFS-212519
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 1, pp. 1481-1504, 2022
Authors: Khalil, Alamgir | Arshad, Kainat | Ijaz, Muhammad | Khan, Sajjad Ahmad | Manzoor, Sadaf | El-Morshedy, Mahmoud
Article Type: Research Article
Abstract: Statistical lifetime distributions play a very important role in modeling data sets in various fields. Extending the existing distributions is of great interest in statistical research. The modification of the distributions provides more flexible model as compared to existing one. In this article, we propose a new probability model using Quadratic Rank Transmutation Map technique, named as Transmuted Lomax Exponential Distribution (TLED). The new distribution can model data sets with increasing, decreasing and bathtub shape hazard rates. Various statistical properties of the proposed distribution such as moments, order statistics, quantile function, mean residual life function and characteristic function are derived. …Further, the parameter estimates are obtained through Maximum Likelihood method along with asymptotic confidence intervals. The utility of the new model is evaluated by analyzing two real data sets. In order to access the performance of the new model, several goodness of fit measures is used. The results indicate that the new model best fits the data as compared to the other extensions of the Lomax distribution. Show more
Keywords: Lomax distributions, maximum likelihood, transmuted, estimation, hazard function
DOI: 10.3233/JIFS-212544
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 1, pp. 1505-1518, 2022
Authors: Mehmood, Arif | Al Ghour, Samer | Afzal, Farkhanda | Nordo, Giorgio | Saleem, Najma
Article Type: Research Article
Abstract: This paper concern the study of the notions of some new definitions and results. Three new definitions are given namely, neutrosophic soft quad semi-open, neutrosophic soft quad pre-open and neutrosophic soft quad *b open sets in neutrosophic soft quad-topological spaces. Among these one of the interesting neutrosophic soft quad generalized open set known as neutrosophic soft quad pre-open set is chosen then on the basis of this definition some fundamentals are generated. These are including, neutrosophic soft quad interior, neutrosophic soft quad boundary, neutrosophic soft quad exterior and neutrosophic soft quad closer. In continuation, attention has been focused …on neutrosophic soft separation axioms which are defined in terms of neutrosophic soft p-open sets with respect to soft points then on the basis of definitions and results given, neutrosophic soft separation axioms are discussed mostly in terms of neutrosophic soft closer of the sets. In addition, some more results are addressed in neutrosophic soft quad-opological spaces with respect to soft points. Stress has been given on the neutrosophic soft quad topological property. Lastly, results on product of neutrosophic soft quad topological spaces, Bolzano-Weierstrass Property, compactness, countably compactness and sequentially compactness are addressed in terms of neutrosophic soft p-open sets in neutrosophic soft quad topological spaces. Show more
Keywords: Neutrosophic soft set, neutrosophic soft points, neutrosophic soft quad-topological space, neutrosophic soft p-open set, set and neutrosophic softp-separation axioms
DOI: 10.3233/JIFS-212547
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 1, pp. 1519-1540, 2022
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