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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: Jia, Lijuan | Hou, Fang
Article Type: Research Article
Abstract: The evaluation of physical education teaching effectiveness is an important component of physical education teaching, and plays a multifaceted role in the process of physical education teaching. The information provided by it can control and regulate the progress of physical education teaching activities as a whole, ensuring that physical education teaching activities develop towards predetermined goals. With the development of the popularization of physical education, people’s requirements for the quality of physical education continue to improve, and the role and position of evaluation in teaching has become increasingly evident. Evaluation of physical education teaching effectiveness has become an indispensable process …in teaching activities. The college physical education teaching effect evaluation can be regarded as a multiple attribute decision making (MADM). Thus, this paper collected information in probabilistic hesitant fuzzy sets (PHFSs) and using CRITIC method to obtain the unknown weight among attributes. Further, a novel probabilistic hesitant fuzzy QUALIFLEX (PHF-QUALIFLEX) method was constructed for MADM. Finally, a numerical case for college physical education teaching effect evaluation was illustrated with this proposed model and other methods were utilized to compare with PHF-QUALIFLEX method to verify the feasibility and applicability. Show more
Keywords: Multiple attributes decision making (MADM), probabilistic hesitant fuzzy sets (PHFSs), QUALIFLEX method, CRITIC method, teaching effect evaluation
DOI: 10.3233/JIFS-231769
Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 4, pp. 5659-5670, 2023
Authors: Zhang, Yunlai
Article Type: Research Article
Abstract: The teaching of painting techniques can comprehensively cultivate students’ basic artistic abilities, mainly including various forms of techniques such as sketching, line drawing, copying, and sketching, showcasing the charm and value of art itself. From a comprehensive perspective, expressing the image in the creator’s heart in painting art and utilizing certain artistic techniques can fully highlight the core value of painting. At the same time, teachers can effectively cultivate students’ foundation in painting and help them clarify the development goals of today’s art major, thereby comprehensively cultivating students’ core artistic literacy. The teaching quality evaluation of painting majors in universities …is classical multiple-attribute group decision-making (MAGDM) issues. Recently, the TODIM and TOPSIS method has been used to solve MAGDM issues. The 2-tuple linguistic Pythagorean fuzzy sets (2TLPFSs) are used as a tool for characterizing uncertain information during the teaching quality evaluation of painting majors in universities. In this manuscript, we design the 2-tuple linguistic Pythagorean fuzzy TODIM-TOPSIS (2TLPF-TODIM-TOPSIS) method to solve the MAGDM under 2TLPFNs. In the end, a numerical case study for teaching quality evaluation of painting majors in universities is given to validate the proposed method. The main research contribution of the paper is summarized: (1) the 2TLPF-TODIM-TOPSIS method is proposed for MAGDM problem with 2TLPFSs; (2) the 2TLPF-TODIM-TOPSIS method is given for teaching quality evaluation of painting majors in universities and were compared with some existing methods; (3) Through the comparison, it is found that 2TLPF-TODIM-TOPSIS method for teaching quality evaluation of painting majors in universities proposed in the study are effective. Show more
Keywords: Multiple attribute group decision making (MAGDM), 2-tuple linguistic Pythagorean fuzzy numbers (2TLPFNs), TODIM-TOPSIS method, teaching quality evaluation, painting majors in universities
DOI: 10.3233/JIFS-232226
Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 4, pp. 5671-5683, 2023
Authors: Shen, Haiyang | Huo, Kui | Qiao, Xin | Li, Chongzhi
Article Type: Research Article
Abstract: In order to solve the problems with the traditional aircraft target type recognition algorithm, such as difficulty in feature selection, weak generalization ability, slow recognition speed, and low recognition accuracy, this paper put forward a new method that could detect and recognize aircraft targets in aerial images quickly and accurately. The aircraft targets in the images were detected rapidly and located through YOLOv3-tiny, and after image denoising, shadow detection, and positioning, then we used the Sobel operator to calculate the edge gradient of the target; the image of the aircraft target was segmented by using the region growth method, and …then the principal component analysis (PCA)was used to obtain the central axis of the aircraft target. The projected distance from the edge contour to the central axis was sampled at equal intervals along the direction of the central axis, and its ratio to the length of the central axis was calculated to construct the feature vector. Finally, the Spearman rank correlation method was used to match the feature vectors to realize the recognition of the aircraft type. Experiments showed that the proposed method had strong adaptability and small computation and could quickly detect and accurately recognize aircraft targets in aerial images. Show more
Keywords: Deep learning, aircraft identification, principal component analysis, spearman rank correlation
DOI: 10.3233/JIFS-232239
Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 4, pp. 5685-5696, 2023
Authors: Gong, Meng
Article Type: Research Article
Abstract: With the increasing maturity and widespread application of computer multimedia technology, many universities have attempted to use multimedia technology for English teaching in order to solve some of the difficulties and contradictions faced in current college English teaching practices. Practice has proven that multimedia teaching of college English not only increases the amount of information in classroom teaching, but also improves the effectiveness of classroom teaching. At the same time, due to deviations in understanding, lack of conditions, and improper operation in work, the normal functioning of multimedia teaching is also restricted, which affects the effectiveness of multimedia teaching in …college English. How to carry out multimedia teaching of college English is indeed an important topic that needs further research. The fuzzy comprehensive evaluation of multimedia teaching effectiveness in college English is a classical multiple attribute decision making (MADM) problems. Recently, the TODIM and GRA method has been used to cope with MADM issues. The double-valued neutrosophic sets (DVNSs) are used as a tool for characterizing uncertain information during the fuzzy comprehensive evaluation of multimedia teaching effectiveness in college English. In this manuscript, the double-valued neutrosophic number Exponential TODIM-GRA (DVNN-ExpTODIM-GRA) method is built to solve the MADM under DVNSs. In the end, a numerical case study for fuzzy comprehensive evaluation of multimedia teaching effectiveness in college English is given to validate the proposed method. Show more
Keywords: Multiple attribute decision making (MADM), double-valued neutrosophic sets (DVNSs), ExpTODIM method, GRA method, multimedia teaching effectiveness
DOI: 10.3233/JIFS-233116
Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 4, pp. 5697-5707, 2023
Authors: Zhang, Qianhong | Pan, Bairong | Ouyang, Miao | Lin, Fubiao
Article Type: Research Article
Abstract: The article is concerned with large time behavior of solution to second-order fractal difference equation with positive fuzzy parameters x n + 1 = A + x n B + x n - 1 , n = 1 , 2 , ⋯ , here the initial values x i (i = -1, 0) and the parameters A , B are positive fuzzy numbers. Utilizing a generalization of division (g-division) of fuzzy numbers, one presents large time behaviors of positive fuzzy solution including persistence, boundedness, …global convergence. Moreover, two numerical examples verify the effectiveness of the qualitative analysis. Show more
Keywords: Second- order fractal difference equation, g-division, large time behavior, positive fuzzy parameter
DOI: 10.3233/JIFS-224099
Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 4, pp. 5709-5721, 2023
Authors: Xu, Huajie | Zhou, Yanping | Chen, Huiying | Kou, Yuanyuan
Article Type: Research Article
Abstract: In the era of the knowledge economy, how integrating into the network of collaborative innovation and promoting technology sharing has become the key to enhancing the competitiveness of enterprises. It is well known that inter-organizational trust is essential to technology sharing. Firstly, this paper discussed how inter-organizational trust plays a role in technology-sharing behavior. Secondly, based on “organization is bounded rational”, we established an evolutionary game model to analyze the influencing factors of technology sharing. Finally, we used the numerical simulation method to verify the model. Research shows that affective trust facilitates technology acquisition and cognitive trust facilitates technology sharing. …The synergetic benefit distribution coefficient influences the evolutionary equilibrium strategy of technology sharing, and there is an optimal synergistic benefit distribution coefficient that maximizes the willingness of both enterprises to share technology. Technology transfer cost and technology leakage risk negatively affect technology-sharing behavior. The degree of technology complementarity, trust coefficient, incentive coefficient, and the ability of shared technologies to transform into synergistic benefits positively influence technology-sharing behavior. The research provides a new way to solve the practical problem of collaborative innovation technology sharing among enterprises. Show more
Keywords: Collaborative innovation, inter-organizational trust, technology sharing, technology acquisition, evolutionary game
DOI: 10.3233/JIFS-231898
Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 4, pp. 5723-5738, 2023
Authors: Huang, Peixin | Luo, Qifang | Wei, Yuanfei | Zhou, Yongquan
Article Type: Research Article
Abstract: Data clustering is a machine learning method for unsupervised learning that is popular in the two areas of data analysis and data mining. The objective is to partition a given dataset into distinct clusters, aiming to maximize the similarity among data objects within the same cluster. In this paper, an improved honey badger algorithm called DELHBA is proposed to solve the clustering problem. In DELHBA, to boost the population’s diversity and the performance of global search, the differential evolution method is incorporated into algorithm’s initial step. Secondly, the equilibrium pooling technique is included to assist the standard honey badger algorithm …(HBA) break free of the local optimum. Finally, the updated honey badger population individuals are updated with Levy flight strategy to produce more potential solutions. Ten famous benchmark test datasets are utilized to evaluate the efficiency of the DELHBA algorithm and to contrast it with twelve of the current most used swarm intelligence algorithms and k-means. Additionally, DELHBA algorithm’s performance is assessed using the Wilcoxon rank sum test and Friedman’s test. The experimental results show that DELHBA has better clustering accuracy, convergence speed and stability compared with other algorithms, demonstrating its superiority in solving clustering problems. Show more
Keywords: Cluster analysis, k-means, equilibrium honey badger algorithm, differential evolution, metaheuristic optimization
DOI: 10.3233/JIFS-231922
Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 4, pp. 5739-5763, 2023
Authors: Yang, Taoli | Li, Jinjin | Li, Zhaowen | Zhou, Yinfeng | Feng, Danlu
Article Type: Research Article
Abstract: Knowledge and learning assessment is a popular topic. In existing models for constructing the knowledge structure of an individual, it is often considered whether an individual has mastered the skills to solve the corresponding item. However, the relationship between the number of skills an individual has mastered and the item is ignored. It is not reasonable to explain the phenomenon that individuals solve the same item but have different knowledge structures behind it. This paper introduces the concept of skill inclusion degree and constructs the variable precision α-models to delineate knowledge structures. The skill inclusion degree takes into account an …individual’s mastery of the number of skills assigned to each item. Firstly, the concept of the skill inclusion degree is given, and some of its properties are discussed. Then, the variable precision α-model is constructed. Moreover, the relationship between knowledge structures delineated via the variable precision α-models by a skill map is studied, and the algorithm of knowledge structures delineated via these models by a skill map is designed. Finally, the experimental results on a real dataset demonstrate the feasibility and effectiveness of the proposed algorithm. Show more
Keywords: Knowledge structure, skill map, skill inclusion degree, disjunctive model, conjunctive model, variable precision α-model
DOI: 10.3233/JIFS-222149
Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 4, pp. 5765-5781, 2023
Authors: Li, Kun | Tian, Shengwei | Yu, Long | Zhou, Tiejun | Wang, Bo | Wang, Fun
Article Type: Research Article
Abstract: In recent years multimodal sentiment analysis (MSA) has been devoted to developing effective fusion mechanisms and has made advances, however, there are several challenges that have not been addressed adequately: the models make insufficient use of important information (inter-modal relevance and independence information) resulting in additional noise, and the traditional ternary symmetric architecture cannot well solve the problem of uneven distribution of task-related information among modalities. Thus, we propose Mutual Information Maximization and Feature Space Separation and Bi-Bimodal Modality Fusion (MFSBF)framework which effectively alleviates these problems. To alleviate the problem of underutilization of important information among modalities, a mutual information …maximization module and a feature space separation module have been designed. The mutual information module maximizes the mutual information between two modalities to retain more relevance (modality-invariant) information, while the feature separation module separates fusion features to prevent the loss of independence(modality-specific) information during the fusion process. As different modalities contribute differently to the model, a bimodal fusion architecture is used, which involves the fusion of two bimodal pairs. The architecture focuses more on the modality that contains more task-ralated information and alleviates the problem of uneven distribution of useful information among modalities. The experiment results of our model on two publicly available datasets (CUM-MOSI and CUM-MOSEI) achieved better or comparable results than previous models, which demonstrate the efficacy of our method. Show more
Keywords: Multimodal sentiment analysis, mutual information, feature separation, modality fusion
DOI: 10.3233/JIFS-222189
Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 4, pp. 5783-5793, 2023
Authors: Xie, Ying | Hu, Fanchao | Liu, Xuewei | Zhai, Lirong
Article Type: Research Article
Abstract: In the actual production process, time-varying and nonlinear problems are numerous important problems to be considered, in view of these problems, a process monitoring approach based on locally weighted probabilistic kernel principal component analysis (LWPKPCA) is proposed. First, the method selects the normal process data with a high similarity to the test samples as training data of the local model, and continuously updates the local model according to the test samples to build an accurate time-varying model. Second, by weighting the data of different importance, the role of data similar to test samples in the modeling process is strengthened. Third, …the LWPKPCA model is applied to process monitoring, the monitoring indicators are established in a high-dimensional space and used to detect faults. Finally, on the basis of LWPKPCA, the penicillin fermentation process (PFP) is taken to evaluate the monitoring performance of the proposed methods. According to the comparison of the experiment results, the detection rate and accuracy rate of the LWPKPCA method is considerably better than those of probabilistic principal component analysis and probabilistic kernel principal component analysis methods. The results demonstrate that the proposed method is suitable for processing time-varying data with nonlinear characteristics, and the LWPKPCA process monitoring method is effective for improving the performance of fault detection. Show more
Keywords: Locally weighted probabilistic kernel principal component analysis, process monitoring, fault detection
DOI: 10.3233/JIFS-224383
Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 4, pp. 5795-5805, 2023
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