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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: Mishra, Aneesh Kumar | Singh, Ravindra Kumar | Jain, Neelesh Kumar
Article Type: Research Article
Abstract: Datasets mainly consist of ambiguous objects, redundant and uncertain attribute values which increase complexity, time and cost in Knowledge Discovery in Databases (KDD) process. Rough set-based attribute reduction techniques deals with ambiguity but fails to handle uncertainty available in a real-valued dataset. Combining rough set with intuitionistic fuzzy set provides a great opportunity to the researchers working on attribute reduction of real-valued datasets as it provides better results when compared to the traditional fuzzy rough set theory. In this paper, we present a new intuitionistic fuzzy rough set model for attribute reduction to avoid misclassification and perturbation by handling hesitancy, …ambiguity and uncertainty present in a dataset. We define an intuitionistic fuzzy tolerance relation between two objects along with lower and upper approximations based on that relation. Next, the concept of Degree of dependency is utilized to present attribute reduction by using model due to its better performing nature over other methods. The algorithm of the proposed technique is applied on benchmark datasets to perform a comparative study with recent approaches. We obtain the best result for the reduced Breast Cancer dataset by our proposed approach, with an accuracy of 98.96% along with 0.90 standard deviation by using SMO classifier. Finally, our proposed method is used to present a methodology to improve the prediction of umami peptides. Here, we record the best results with sensitivity, specificity, accuracy, AUC, and MCC of 96.8%, 93.6%, 97.7%, 0.988, and 0.899, respectively. From the experiments, it can be concluded that our method outperforms the existing methods. Show more
Keywords: Rough set, fuzzy set, intuitionistic fuzzy set, attribute reduction, tolerance relation, degree of dependency
DOI: 10.3233/JIFS-212987
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 3, pp. 3741-3755, 2022
Authors: Idrais, Jaafar | El Abassi, Rida | El Moudene, Yassine | Sabour, Abderrahim
Article Type: Research Article
Abstract: Online social networks (OSNs) occupy an important part in users’ daily life as they maintain the flow of interaction and information exchange on all local, national, and global scales.This work develops a time series model of interactions on Facebook using the SARIMA (seasonal autoregressive integrated moving average) time series modeling technique based on empiricism with the theoretical model of regular user behavior. A case study of the Moroccan community, which has a high rate of interactions, is carried out to test the conformity of the model with the measurements. The results show that the SARIMA model is better suited to …modeling the flow of interactions. The application of the SNR method on the signal energies has allowed to measure the usage damping in the users. The multitude of applied approaches have allowed to extract some main characteristics of this large and complex network. Show more
Keywords: Data mining, OSNs, facebook, social network analysis, time series, social grouping, user behavior
DOI: 10.3233/JIFS-213391
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 3, pp. 3757-3769, 2022
Authors: Joshi, Manju Lata | Mittal, Namita | Joshi, Nisheeth
Article Type: Research Article
Abstract: In this study, a Fuzzy Semantic Graph-based approach is proposed to extract keywords and generate extractive text summaries from Hindi text documents. Hindi Wordnet is used as a knowledge source to construct the semantic graph. As the semantic relations defined in Hindi Wordnet are crisp, they do not capture the semantic relationship as a matter of degree. Due to that, many terms are represented as not being related, while these can share some meaningful relationship as per real-life scenarios. To overcome this curb of Hindi Wordnet, the paper presents several fuzzy semantic associations between such terms by assigning a value …ranging from 0 to 1 to such relations. While constructing the semantic graph to represent documents using Hindi Wordnet semantic relations, the terms sharing fuzzy semantic relations are also added to enhance the quality of the graph. The experiments are done to extract potential keywords and to generate a good content summary. It is observed that such semantics generate a more accurate summary and produce prospective keywords for the document. The performance of the proposed approach fuzzy-based semantic graph is compared to semantic graph-based approach for keyword extraction and text summarization. The keywords extracted and the summary generated by the proposed approach is match up to human extracted keywords and human-generated text summary. The proposed approach results are evaluated using precision, recall, and f-measure. Different outcomes of generated text summaries are evaluated using the ROUGE matrix. The results of the proposed approach are pretty encouraging. Show more
Keywords: Hindi wordnet, semantic graph, fuzzy semantic graph, keyword extraction, text summarization
DOI: 10.3233/JIFS-212603
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 3, pp. 3771-3788, 2022
Authors: Ishfaq, Muhammad | Al Ghour, Samer | Mehmood, Arif | Afzal, Farkhanda | Li, Zhongyan | Nordo, Giorgio
Article Type: Research Article
Abstract: In our work, we defined new operations in a new way in connection with vague hyper soft sets. These operations are vague hyper soft sets, vague hyper soft subsets, vague hyper soft complements, vague hyper soft null sets, vague hyper soft absolute sets, vague hyper soft union and vague hyper soft intersection. On the basis of these new operations vague hyper soft topology is defined. In addition, the concept of some generalized vague hyper soft open sets are reflected in vague hyper soft topology. Among these generalized vague hyper soft open sets vague hyper soft α-open set is selected to …produce different structures. Finally, on the basis of this vague hyper soft α-open set some more results are addressed. Non-validity of some results are diffused with appropriate examples. Show more
Keywords: Hyper soft sets, vague hyper soft sets, vague hyper soft union, vague hyper soft intersection, vague hyper soft topology, vague hyper soft α-open set
DOI: 10.3233/JIFS-212329
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 3, pp. 3789-3803, 2022
Authors: Cui, Fuwei | Di, Hui | Huang, Hui | Ouchi, Kazushige | Liu, Ze | Xu, Jinan
Article Type: Research Article
Abstract: Hierarchical structures have emerged as a powerful framework for response generation, which can generate fluent responses in multi-turn conversation. However, the generated responses are often generic and bland. Some researchers have adopted latent variables to improve the diversity of responses, but they can not make full use of the information from multi-turn background, leading to meaningless replies with irrelevant topics. In order to fully utilize the background information for generating diverse and informative responses, we propose a Variational Hierarchical Conversation RNNs model with Topic aware latent variables (VHCR-T). The model contains three levels of latent variables: the global level latent …variable to represent background information, the topic level latent variable to capture topic-related information, and the sentence level latent variable to increase the response diversity. When modeling the topic information, we design two different topic level latent variables to maintain the dialog coherence and role preference, and to enhance the context sensitiveness, respectively. Experimental results on Cornell Movie Dialog and Ubuntu Dialog Corpus show that our model outperforms the state-of-the-art models for multi-turn conversation generation in terms of diversity and informativeness, verifying the effectiveness of our VHCR-T model. Show more
Keywords: Multi-turn conversation, response generation, hierarchical structure, topic, latent variable
DOI: 10.3233/JIFS-211886
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 3, pp. 3805-3814, 2022
Authors: Shi, Yucai | Li, Weiqing | Lu, Pengfei | Chen, Fuxu | Qi, Xiaochen | Xiong, Changxin
Article Type: Research Article
Abstract: The precise motion control of a hydraulic motor system has some problems due to uncertain disturbance, complex nonlinear dynamics. Traditional methods are difficult to obtain the desired control performance. In this paper, a new fuzzy neural network (FNN) combined with terminal sling mode control (TSMC) and time delay estimation (TDE) is proposed. FNN is used to adjust the parameter of TSMC to reduce the time for the system to reach the equilibrium point and chatting. To increase the accuracy of the system, TDE is used to compensate the error caused by uncertain disturbance. This controller was simulated in Amesim and …Simulink, and the results showed that the control scheme proposed in this paper has the smallest angular displacement error, angular velocity error and variance than other control schemes, such as PID and sliding mode control (SMC). Furthermore, the designed controller was implemented on a drill pipe automatic handling manipulator, and its control performance was verified. Show more
Keywords: Motion control, hydraulic motor, fuzzy neural network, terminal sliding mode control, time delay estimation
DOI: 10.3233/JIFS-211398
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 3, pp. 3815-3826, 2022
Authors: Mirvakili, M. | Allahviranloo, T. | Soltanian, F.
Article Type: Research Article
Abstract: Fractional order differential equations accurately model dynamic systems and processes. In some of the fractional optimal control problems (FOCPs), due to the ambiguity in the initial conditions and the transfer of ambiguity to the solution, it is necessary to use fuzzy mathematics. In this paper, a numerical method is presented to approximate the solution for a class of Fuzzy Fractional Optimal Control Problems (FFOCPs) using the Legendre basis functions. The fuzzy fractional derivative is described in the Caputo sense. The performance index of an FFOCP is considered as a function of both the state and the control variables, and the …dynamic constraints are expressed by a set of Fuzzy Fractional Differential Equations (FFDEs). After obtaining Euler–Lagrange equations for FFOCPs and the necessary and sufficient conditions for the existence of solutions, using the definition of generalized Hukuhara differentiability (types I, II), the problem is considered in two cases. Then the distance function and an approach similar to the variational type along with the Lagrange multiplier method are used to formulate and solve the equations in a system. Time-invariant and time-varying examples are provided to assess the presented method. Numerical results show a similar trend for the state and control variables for various numbers of Legendre polynomials. Also, the convergence of state and control variables for the time-invariant system can be seen, and the same is true for control variables for the time-varying system. Show more
Keywords: Fuzzy fractional optimal control problem, Caputo derivative, Legendre basis function, Euler–Lagrange equations, Generalized Hukuhara differentiability, Numerical method
DOI: 10.3233/JIFS-210583
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 3, pp. 3827-3858, 2022
Authors: Han, Meng | Li, Xiaojuan | Wang, Le | Zhang, Ni | Cheng, Haodong
Article Type: Research Article
Abstract: Most data stream ensemble classification algorithms use supervised learning. This method needs to use a large number of labeled data to train the classifier, and the cost of obtaining labeled data is very high. Therefore, the semi supervised learning algorithm using labeled data and unlabeled data to train the classifier becomes more and more popular. This article is the first to review data stream ensemble classification methods from the perspectives of supervised learning and semi-supervised learning. Firstly, basic classifiers such as decision trees, neural networks, and support vector machines are introduced from the perspective of supervised learning and semi-supervised learning. …Secondly, the key technologies in data stream ensemble classification are explained from the two aspects of incremental and online. Finally, the majority voting and weight voting are explained in the ensemble strategies. The different ensemble methods are summarized and the classic algorithms are quantitatively analyzed. Further research directions are given, including the handling of concept drift under supervised and semi-supervised learning, the study of homogeneous ensemble and heterogeneous ensemble, and the classification of data stream ensemble under unsupervised learning. Show more
Keywords: Review, ensemble learning, supervised algorithm, semi-supervised algorithm
DOI: 10.3233/JIFS-211101
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 3, pp. 3859-3878, 2022
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