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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: Jiang, Hailiang | Chen, Yumin | Kong, Liru | Cai, Guoqiang | Jiang, Hongbo
Article Type: Research Article
Abstract: Learning Vector Quantization (LVQ) is a clustering method with supervised information, simple structures, and powerful functions. LVQ assumes that the data samples are labeled, and the learning process uses labels to assist clustering. However, the LVQ is sensitive to initial values, resulting in a poor clustering effect. To overcome these shortcomings, a granular LVQ clustering algorithm is proposed by adopting the neighborhood granulation technology and the LVQ. Firstly, the neighborhood granulation is carried out on some features of a sample of the data set, then a neighborhood granular vector is formed. Furthermore, the size and operations of neighborhood granular vectors …are defined, and the relative and absolute granular distances between granular vectors are proposed. Finally, these granular distances are proved to be metrics, and a granular LVQ clustering algorithm is designed. Some experiments are tested on several UCI data sets, and the results show that the granular LVQ clustering is better than the traditional LVQ clustering under suitable neighborhood parameters and distance measurement. Show more
Keywords: Supervised learning, granular computing, LVQ clustering, neighborhood granules
DOI: 10.3233/JIFS-220092
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 5, pp. 6109-6122, 2022
Authors: Sood, Mansi | Gera, Jaya | Kaur, Harmeet
Article Type: Research Article
Abstract: This work creates, evaluates, and optimizes a domain-based dictionary using labeled domain documents as the input. The dictionary is created using selected unigrams and bigrams from the labeled text documents. Dictionary is evaluated using the Naïve Bayes classification model. Classification Accuracy obtained is used as a metric to evaluate the effectiveness of the dictionary. The paper also studies the impact of applying the Stochastic Gradient Descent (SGD) technique, with Lasso and Ridge Regularization, on the effectiveness of a domain-based dictionary. Both, Lasso and Ridge regularization, with Ridge faring better than Lasso, help to optimize the dictionary size, without any significant …reduction in the accuracy. The created dictionaries are evaluated on the dataset used for their creation and subsequently on an unseen dataset as well. The applicability of a created dictionary to classify the documents belonging to a different dataset gives an idea about the generality of that dictionary. The paper establishes that the dictionaries created using the above methodology are generic enough to classify documents of other unseen datasets. Show more
Keywords: Domain-based dictionary, unigram, bigram, Naïve Bayes classification, Stochastic Gradient Descent
DOI: 10.3233/JIFS-220110
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 5, pp. 6123-6136, 2022
Authors: Zhu, Linkai | Wang, Wennan | Huang, Maoyi | Chen, Maomao | Wang, Yiyun | Cai, Zhiming
Article Type: Research Article
Abstract: A lot of manual work goes into identifying a topic for an article. With a large volume of articles, the manual process can be exhausting. Our approach aims to address this issue by automatically extracting topics from the text of large numbers of articles. This approach takes into account the efficiency of the process. Based on existing N-gram analysis, our research examines how often certain words appear in documents in order to support automatic topic extraction. In order to improve efficiency, we apply custom filtering standards to our research. Additionally, delete as many noncritical or irrelevant phrases as possible. In …this way, we can ensure we are selecting unique keyphrases for each article, which capture its core idea1 . For our research, we chose to center on the autonomous vehicle domain, since the research is relevant to our daily lives. We have to convert the PDF versions of most of the research papers into editable types of files such as TXT. This is because most of the research papers are only in PDF format. To test our proposed idea of automating, numerous articles on robotics have been selected. Next, we evaluate our approach by comparing the result with other models. Show more
Keywords: Automatic topic extraction, frequency statistic, keyphrase, N-gram
DOI: 10.3233/JIFS-220115
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 5, pp. 6137-6146, 2022
Authors: Shi, Lukui | Zu, Haoran | Tai, Jikai | Niu, Weifei
Article Type: Research Article
Abstract: Because X-ray welding images have complex backgrounds and welding defects have different sizes and shapes, effectively detecting welding defects in X-ray images is still a challenge. To solve these problems, a shape-aware network (SA-NET) was proposed, whose core was the shape-aware module (SAM). SAM includes a free-shape region proposal network (FS-RPN) and a two-level regression head (TR-Head). FS-RPN predicts the shape of the anchor boxes corresponding to each position on the feature maps, and aligns the feature maps according to the predicted anchor box shape. Then, the offset and the foreground classification score of the anchor boxes are predicted according …to the aligned feature maps. Thus, FS-RPN generates the proposal regions with a higher quality. TR-Head uses the first-level detection head, which only contains one regression branch, to further improve the quality of the proposal regions by fine-tuning the proposal regions. It employs the second-level detection head, which consists of one classification branch and one regression branch, to predict the categories and the boxes of defects. The experimental results showed that SA-NET effectively improved the quality of the proposal regions and greatly improved the detection effect of welding defects, especially defects with special shapes. Show more
Keywords: Welding defects, defect detection, shape awareness, FS-RPN, TR-head
DOI: 10.3233/JIFS-220132
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 5, pp. 6147-6162, 2022
Authors: Martinez-Gil, Jorge | Chaves-Gonzalez, Jose Manuel
Article Type: Research Article
Abstract: The automatic semantic similarity assessment field has attracted much attention due to its impact on multiple areas of study. In addition, it is also relevant that recent advances in neural computation have taken the solutions to a higher stage. However, some inherent problems persist. For example, large amounts of data are still needed to train solutions, the interpretability of the trained models is not the most suitable one, and the energy consumption required to create the models seems out of control. Therefore, we propose a novel method to achieve significant results for a sustainable semantic similarity assessment, where accuracy, interpretability, …and energy efficiency are equally important. We rely on a method based on multi-objective symbolic regression to generate a Pareto front of compromise solutions. After analyzing the output generated and comparing other relevant works published, our approach’s results seem to be promising. Show more
Keywords: Knowledge engineering, sustainable computing, semantic similarity assessment
DOI: 10.3233/JIFS-220137
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 5, pp. 6163-6174, 2022
Authors: Du, Ye | Yao, Bingxue
Article Type: Research Article
Abstract: Zhan and Jiang defined covering-based compact and loose variable precision fuzzy rough set models. Soon after, they proposed a reflexive fuzzy β-neighborhood operator and defined a covering-based generalized variable precision fuzzy rough set. Based on them, in this paper, we use the reflexive fuzzy β-neighborhood operator to establish two covering-based generalized variable precision fuzzy rough set models, which are called covering-based generalized compact and loose variable precision fuzzy rough set models, respectively. Then, we investigate the important properties of the two rough set models and their relationship to the original models. Finally, we apply the covering-based generalized compact variable precision …fuzzy rough set model to decision-making problems. A simple example is given to verify the validity of the model and compare the results with other models. Show more
Keywords: Fuzzy rough set , compact, loose, fuzzy logical operator
DOI: 10.3233/JIFS-220152
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 5, pp. 6175-6187, 2022
Authors: Angammal, S. | Hannah Grace, G.
Article Type: Research Article
Abstract: In agriculture crop planning plays an important role. There are many uncertainties and indeterminacy factors that occur in agriculture cultivation process. Hence, many parameters are determined by using intuitionistic fuzzy number. The present study discussed the new Interactive Neutrosophic Programming Approach (INPA) based on Neutrosophic Set (NS) to increase the production and profit of Ariyalur district medium farm holder with minimum expenditure taking into account the land, labour, water & food requirement constraints. To verify and validate the proposed method, the results obtained by INPA are compared with some existing optimization approaches such as FOT, IFOT and Torabi interactive fuzzy …optimization approach and it is clear that the proposed approach is superior than the existing model. Show more
Keywords: Crop planning, multi objective optimization, intuitionistic fuzzy parameter, membership function, neutrosophic programming
DOI: 10.3233/JIFS-220156
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 5, pp. 6189-6201, 2022
Authors: Jiang, Man
Article Type: Research Article
Abstract: In this paper, the notions of hesitant fuzzy dot subalgebras, hesitant fuzzy normal dot subalgebras, and hesitant fuzzy dot ideals of B-algebras are presented, and some of their features are examined, in this study. The homomorphic image and inverse image of hesitant fuzzy dot subalgebras, as well as the hesitant fuzzy dot ideal, are investigated. We also explore some related characteristics of hesitant fuzzy relations on the family of hesitant fuzzy dot subalgebras and hesitant fuzzy dot ideal of B-algebras.
Keywords: B-algebra, hesitant fuzzy dot subalgebra, hesitant fuzzy normal dot subalgebra, hesitant fuzzy dot ideal, hesitant fuzzy ρ- product relation
DOI: 10.3233/JIFS-220158
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 5, pp. 6203-6212, 2022
Authors: Yu, Shun-Chi
Article Type: Research Article
Abstract: In the recent decades, genetic algorithms (GAs) have often been applied as heuristic techniques at various settings entailing production scheduling. However, early convergence is one of the problems associated with this approach. This study develops an efficient local search rule for the target-oriented rule in traditional GAs. It also addresses the problem of two-stage multiprocessor flow-shop scheduling (FSP) by viewing the due window and sequence-dependent setup times as constraints faced by common flow shops with multiprocessor scheduling suites in the actual production scenario. Using the simulated data, this study verifies the effectiveness and robustness of the proposed algorithm. The results …of data testing demonstrate that the proposed method may outperform other algorithms, including a significant hybrid algorithm, in addressing the problems considered. Show more
Keywords: Target-oriented, genetic algorithm, two-stage multiprocessor flow shop scheduling, due window, setup time
DOI: 10.3233/JIFS-220174
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 5, pp. 6213-6228, 2022
Authors: Xu, Zhiwei | Li, Peng | Wei, Cuiping
Article Type: Research Article
Abstract: In recent years, to address the continued aging of China’s population, the Chinese government has focused on the issue of pensions through a series of pension policies. The traditional system of institutional pensions is facing serious challenges, with a variety of novel pension modes placing them under enormous pressure. Furthermore, the development of institutional pensions has been restricted by many factors, such as long construction cycles and high fees, meaning that this traditional system no longer meets the pension needs of the elderly. Improving the service quality of institutional pensions is inevitable for future progress. Thus, identifying the key factors …that influence the service quality of institutional pensions, and understanding the relationships between these factors, is hugely significant. Furthermore, traditional decision-making trial and evaluation laboratory (DEMATEL) method can not solve this problem because the number of factors is too large. To address these issues, we establish an evaluation system for Chinese pension institutions, and propose a hierarchical DEMATEL model based on probabilistic linguistic term sets (PLTSs), which can help decision makers to find the key factors influencing service quality in institutional pensions and deal with the evaluation problem with a large number of criteria. The proposed hierarchical DEMATEL model based on PLTSs fully reflects experts’ preferences and evaluation information, and is able to identify the directions in which China’s pension institutions should improve their quality of service. In addition, we use the best-worst method (BWM) to calculate the importance values of each subsystem, which makes the cause-effect relationship between subsystems more reasonable than the traditional DEMATEL method. Finally, we apply our method to evaluate nursing homes in Zhenjiang, Jiangsu province and propose some managerial implications. Show more
Keywords: Evaluation, hierarchical DEMATEL, PLTS, institutional pension, aging
DOI: 10.3233/JIFS-220181
Citation: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 5, pp. 6229-6251, 2022
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