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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: Tian, Xianghua | Luan, Feng | Li, Xu | Wu, Yan | Chen, Nan
Article Type: Research Article
Abstract: In the hot strip rolling process, accurate prediction of bending force is beneficial to improve the accuracy of strip crown and flatness, and further improve the strip shape quality. Due to outliers and noise are commonly present in the data generated in the rolling process, not only the prediction accuracy should be considered, but also the uncertainty of prediction results should be described quantitatively. Therefore, for the first time, the authors establish an interval prediction model for bending force in hot strip rolling process. In this paper, we use Artificial Neural Network (ANN) and whale optimization algorithm (WOA) to produce …a prediction interval model (WOA-ANN) for bending force in hot strip rolling. Based on the point prediction by ANN, interval prediction is completed by using lower upper bound estimation (LUBE) and WOA, and three indexes are used to evaluate the performance of the model. This paper uses real world data from steel factory to determine the optimal network structure and parameters of the interval prediction model. Furthermore, the proposed WOA-ANN model is compared with other interval prediction models established by other three optimization algorithms. The experimental results show that the proposed WOA-ANN model has high reliability and narrow interval width, and can well complete the interval prediction of bending force in hot strip rolling. This study provides a more detailed and rigorous basis for setting bending force in hot strip rolling process. Show more
Keywords: Artificial neural network (ANN), whale optimization algorithm (WOA), bending force, lower upper bound estimation (LUBE), interval prediction
DOI: 10.3233/JIFS-221338
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 7297-7315, 2022
Authors: Qi, Quan-Song
Article Type: Research Article
Abstract: The performance evaluation of public charging service quality is frequently viewed as the multiple attribute group decision-making (MAGDM) issue. In this paper, an extended TOPSIS model is established to provide a new means to solve the performance evaluation of public charging service quality. The TOPSIS method integrated with FUCOM method in probabilistic hesitant fuzzy circumstance is applied to rank the optional alternatives and a numerical example for performance evaluation of public charging service quality is used to test the newly proposed method’s practicability with the comparison with other methods. The results display that the approach is uncomplicated, valid and simple …to compute. The main results of this paper: (1) A novel PHF-TOPSIS method is proposed; (2) The extended TOPSIS method is developed in the probabilistic hesitant fuzzy environment; (3) The FUCOM method is used to obtain the attribute weight; (4) The normalization process of the original data has adapted the latest method to verify the precision; (5) The built models and methods are useful for other selection issues and evaluation issues. Show more
Keywords: Multiple attributes group decision making (MAGDM), probabilistic hesitant fuzzy sets (PHFS), FUCOM method, TOPSIS method, performance evaluation, public charging service quality
DOI: 10.3233/JIFS-220999
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 7317-7328, 2022
Authors: Karthik, G.L. | Samson Ravindran, R.
Article Type: Research Article
Abstract: Fetal Electrocardiogram (FECG) analysis helps in diagnosis of fetal heart. Extracting FECG from composite abdominal signal that contains noises like maternal ECG (MECG), electrical interference etc is a topic of great research interest, and several approaches have been reported. The proposed method is Heuristic RNN-based Kalman Filter for Fetal Electrocardiogram Extraction (HRKFFEE) which is based on redundant noise and signal patterns in the residual signal of FECG and MECG. Two functional blocks are used in the proposed method. The first functional block is based on Heuristic RNN equipped with legacy Long Short-Term Memory (LSTM) for assembling a knowledgebase and the …second functional block is RNN-based Kalman filter. Upon testing, the proposed method delivers better average values of accuracy, F Score, Precision and Specificity as 93.118%, 93.106%, 92.9495 % and 92.98% respectively. Show more
Keywords: FECG Extraction, RNN-based Kalman filter, Legacy LSTM
DOI: 10.3233/JIFS-221549
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 7329-7340, 2022
Authors: Zhang, Guidong | Sheng, Yuhong | Shi, Yuxin
Article Type: Research Article
Abstract: The multivariate uncertain regression model reveals the relationship between the explanatory and response variables to us very effectively. In this paper, firstly, the uncertain maximum likelihood estimation method for the parameters of the one-dimensional uncertain regression model is extended to the multivariate uncertain regression model to obtain estimates of the parameters. Secondly, in order to determine the reasonableness of the estimated values that are obtained by the various parameter estimation methods, uncertain hypothesis testing is applied to the multivariate uncertain regression model. Finally, some numerical examples are given to verify the feasibility of the method.
Keywords: Multivariate uncertain regression model, maximum likelihood estimation, uncertain hypothesis testing
DOI: 10.3233/JIFS-213322
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 7341-7350, 2022
Authors: Bakhat, Khush | Kifayat, Kashif | Islam, M. Shujah | Islam, M. Mattah
Article Type: Research Article
Abstract: The method of marking video clips with action symbols is known as vision-based human activity recognition. Robust solutions to this problem have a variety of practical implementations. Due to differences in motion performance, recording environments, and inter-personal differences, the challenge is difficult. We specifically resolve these problems in this study work, and we solve imitations of state-of-the-art research. Projected human activity recognition is based on an amalgamation of CEV & SGM features. The proposed solution outperforms current models and produces state-of-the-art outcomes as compared to the best effectiveness of the control, according to experimental results on the datasets.
Keywords: Complex networks, entropy, human activity recognition, human action recognition, CEV, SGM
DOI: 10.3233/JIFS-213514
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 7351-7362, 2022
Authors: Pavithra, P. | Hariharan, B.
Article Type: Research Article
Abstract: Cloud computing become increasingly more famous consistently, as numerous associations tend to outsource their information. With the outbreak of email message leakage, the protection and security of sensitive email data have become clients’ essential concerns. Encrypted email data is a superior method to ensure security, yet it will enormously restrict the searching. To take care of this difficulty keyword-based search over encrypted information is presented. The current search strategies permit the client to search utilizing just the specific keywords. There is no capacity to bear errors and format irregularities. In order to overcome those drawbacks, optimal secured fuzzy-based multi-keyword search …over encrypted email data is proposed here. The email sender encrypts the email data before outsourcing the data to a cloud server. For encryption, the proposed method utilizes the optimal secure XOR (OSXOR) encryption algorithm. Here the key value is optimally selected by the mayfly optimization algorithm (MOA). After the encryption, the encrypted email is outsourced to the cloud server. The data owner creates an encrypted searchable index using an input file to enable querying across encrypted emails and then assigns either the index or the gathering of encrypted messages to a cloud server. The receiver receives them from the cloud server and is fed back information, but it is unable to comprehend the signal. The recipient of the encrypted email can decode it and create a search trapdoor in the encrypted email database. For searching, fuzzy-based multi-keyword search is proposed. The effectiveness of the proposed methodology is analyzed in terms of different metrics namely, Memory Usage, Execution time, Encryption and decryption time and search time. The experimental result shows that the proposed method takes a minimum search time is 0.51 s and it achieves maximum searching accuracy of 98%. The implementation is done in JAVA with a Cloud simulator. Show more
Keywords: Cloud computing, encryption, decryption, mayfly optimization, fuzzy-based multi keyword search and search time
DOI: 10.3233/JIFS-213521
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 7363-7375, 2022
Authors: Xu, Xinrui
Article Type: Research Article
Abstract: At present, with the continuous changes in the market situation and the continuous improvement of the supply chain network structure, the competition in all walks of life has become more and more intense, which has risen from simple enterprise competition to competition in the entire supply chain. In the construction industry, the structure of the construction supply chain is more complex and diverse, and it is more necessary to select high-quality suppliers for sincere cooperation. This requires construction companies to establish a complete supply chain management system, select high-quality suppliers to achieve win-win cooperation and improve their competitiveness. Therefore, construction …enterprises need to comprehensively consider various factors, build a reasonable and feasible evaluation index system according to their own demand for materials, and use appropriate evaluation methods to select material suppliers with specific advantages, so as to ensure the entire construction supply chain of the project. of smooth operation. In this paper, we introduced some calculating laws on interval-valued intuitionistic fuzzy sets (IVIFSs), Hamacher sum and Hamacher product and further propose the induced interval-valued intuitionistic fuzzy Hamacher ordered weighted average (I-IVIFHOWA) operator. Meanwhile, we also study some ideal properties of built operator. Then, we apply the I-IVIFHOWA operator to deal with the multiple attribute decision making (MADM) problems under IVIFSs. Finally, an example for selecting the building material suppliers is used to test this new approach. Show more
Keywords: Multiple attribute decision making (MADM), interval-valued intuitionistic fuzzy sets (IVIFSs), IOWA operator, I-IVIFHOWA operator, building material suppliers
DOI: 10.3233/JIFS-221001
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 7377-7386, 2022
Authors: Baytürk, Engin | Küçükdeniz, Tarık | Esnaf, Şakir
Article Type: Research Article
Abstract: Location-routing problem (LRP) contains two Np-hard problems as, facility location (FL) and vehicle routing problem (VRP), in the same content. Since both problems directly affect the cost of distributions of the products and supply chain, the decision of location and routing is important for the success of companies. Therefore, many attempts are made to solve LRP problem in the literature. Researchers proposed exact and heuristic methods for LRP. However, exact methods cannot provide solutions for considerably large instances. In this paper, a new heuristic method is proposed for continuous or planar LRP. The proposed method contains fuzzy c-means for continuous …location problem and simulated annealing algorithm for vehicle routing problem, respectively. The proposed method is applied to both capacitated and uncapacitated LRP instances that are widely used in the literature. Results of the proposed method are compared with successful researches that are made on this problem in terms of the total cost. Show more
Keywords: Location-routing problem, simulated annealing algorithm, fuzzy c-means
DOI: 10.3233/JIFS-221168
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 7387-7398, 2022
Authors: Jayasree, T. | Selvin Retna Raj, T.
Article Type: Research Article
Abstract: In this paper, the classification of power quality disturbances using combined ST/MST (S-Transform/Modified S-Transform) and Radial Basis Function Neural Network (RBFNN) is proposed. The extraction of significant features from the power quality disturbance signals is one of the challenging tasks in recognizing different disturbances. The Stockwell Transform/Modified Stockwell Transform (ST/MST) based features are distinct, understandable and more immune to noise. The important attributes present in the signals are retrieved from the ST/MST contours, MST 3D plots and MST based statistical curves. The relevant features are also extracted from the statistical curves. The extracted features are given as input to the …RBFNN for further classification. This method is evaluated under both noisy and noiseless conditions. The performance of the proposed approach is compared with other conventional approaches in the literature. The simulation results demonstrate that the proposed MST based RFNN technique is more effective for the detection and classification of power quality disturbances. Show more
DOI: 10.3233/JIFS-212399
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 7399-7415, 2022
Authors: Du, Yuqin | Du, Xiangjun | Li, Yuanyuan | Hou, Fujun
Article Type: Research Article
Abstract: The aim of this paper is to introduce a Frank operator in the q-rung orthopair triangular fuzzy linguistic environment on the basis of the notion of the Frank operator and the q-rung orthopair fuzzy set. Firstly, the concept of a q-rung orthopair triangular fuzzy linguistic set (q-ROTrFLS) is proposed, then several basic operations, score, and accuracy functions to compare the q-ROTrFLS values are defined. Secondly, a series of q-rung orthopair triangular fuzzy linguistic Frank aggregation operators are developed, such as q-rung orthopair triangular fuzzy linguistic Frank weighted average (q-ROTrFLWA)operator,q-rung orthopair triangular fuzzy linguistic Frank weighted geometric (q-ROTrFLWG) operator, and we …introduce several relevant properties of these operators and prove their validity, and show the relevant relationship between some operators. Thirdly, two different decision-making approaches are constructed in the q-rung orthopair triangular fuzzy linguistic environment. Furthermore, a practical example is given to explain the developed methods. Finally, a comparative study is conducted, and the relevant sensitivity analysis is also discussed, and the outcome shows the prominence and the effectiveness of the developed methods compared to previous studies. Show more
Keywords: q-rung orthopair triangular fuzzy linguistic set, Frank operator, multi-attribute decision making (MADM), q-rung orthopair set
DOI: 10.3233/JIFS-220556
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 6, pp. 7417-7445, 2022
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