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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: Yin, Rui | Lu, Wei | Yang, Jianhua
Article Type: Research Article
Abstract: The amalgamation of fuzzy model and deep learning has become one hot topic in today’s fuzzy community. However, with the model goes deeper, a pivotal aspect for performance enhancement, the interpretability of the model will deteriorate. To enhance the classification accuracy of classifiers while ensuring interpretability, we propose a stacked architecture-based fuzzy classifier named PT-SAFC. Borrowing the hierarchically stacked thought originated from deep learning, the PT-SAFC is composed by stacking two distinct fuzzy systems, implemented by fuzzy neuro-networks. Here, we propose an improved Takagi-Sugeno-Kang (TSK) model (PTFS) for data transfer by incorporating fuzzy cognitive maps (FCM). It imparts the TSK …model with the data processing capability akin to deep learning models, thereby mitigating the interpretability loss arising from an increase in model depth. Furthermore, the multi-prototypes fuzzy system for decision making (MPDFS) is constructed to map data onto classes. An enhanced gradient descent method with restriction mechanism of prototype position is designed for parameter optimization. The experiments underscore PT-SAFC’s achievement of a harmonious equilibrium between interpretability and classification accuracy. And, PT-SAFC maintains an advantage in classification performance even compared to deep learning methods. Furthermore, experiments validate PT-SAFC’s capability to manipulate data distribution to augment classification efforts. Show more
Keywords: fuzzy classifier, fuzzy cognitive map, data position transformation, gradient descent method
DOI: 10.3233/JIFS-236087
Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 2037-2052, 2024
Authors: Bhukya, Raghuram | Vodithala, Swathy
Article Type: Research Article
Abstract: Social media is becoming a crucial part of our everyday lives, whether it’s for product advertising, developing brand value, or reaching out to users. At the same time, sentiment analysis (SA) is a method for determining the emotions associated with online information. The main obstacle to SA’s success is the presence of sarcasm in the text. Previous studies on the identification of sarcasm use lexical and pragmatic signs such as interjection, punctuation, and sentimental change, amongst others. Deep learning (DL) models can be used to learn the lexical and contextual aspects of informal language because handcrafted features cannot be generalised. …In addition, word embedding can be used to train the DL models and provide effective results on big datasets at the same time. Optimal Deep Learning based Sarcasm detection and classification using an ODL-SDC method is presented in this study. ODL-SDC analyses social media data to look for and classify any sarcasm that may have been used there. In addition, the Glove embedding approach is used to transform feature vectors. A approach known as the chaotic crow search optimization on deep belief network (CCSO-DBN) is also used to classify and detect satire. Many benchmark datasets were used to evaluate the ODL-SDC method, and the results show it to be more effective than existing approaches in a number of performance metrics. Show more
Keywords: Sarcasm detection, deep learning, social media, word embedding, feature vectors, classification
DOI: 10.3233/JIFS-222633
Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 2053-2066, 2024
Authors: Tasbozan, Hatice
Article Type: Research Article
Abstract: Hypersoft set theory represents an advanced version to soft set theory, offering enhanced capabilities for addressing uncertainty. By combining hypersoft set theory with nearness approximation spaces, a novel mathematical model known as near hypersoft set emerges. This hybrid model enables improved decision-making accuracy. In this study, our focus is on selecting an object from a product containing a function parameter set described by a distinct Cartesian feature with multiple arguments. Furthermore, we define fundamental features and topology on this set.
Keywords: Soft sets, near sets, near soft sets, hypersoft set, near hypersoft set
DOI: 10.3233/JIFS-224526
Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 2067-2076, 2024
Authors: Gong, Zengtai | Jiang, Taiqiang
Article Type: Research Article
Abstract: In the existing conflict analysis models, they used a triangular fuzzy number on [0, 1] to describe the range of an agent’s attitude towards an issue, but there are still some shortcomings in describing the specific attitude and degree of conflict represented by the triangular fuzzy number. In this paper, the conflict analysis model is extended, improved and perfected. Firstly, the expectation of triangular fuzzy number is used in the [-1, 1] triangular fuzzy information system to reasonably express the specific attitudes represented by a triangular fuzzy number. Secondly, the weights of each issue are obtained by using the Sugeno …measure, which determines the total attitude of the agent towards all issues. Thirdly, the relationship between agents is obtained with the help of the weighted distance of triangular fuzzy numbers. Finally, the thresholds α and β are calculated by means of triangular fuzzy decision theory rough sets. Show more
Keywords: Conflict analysis, three-way decisions, triangular fuzzy number
DOI: 10.3233/JIFS-231296
Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 2077-2090, 2024
Authors: Huang, Juan | Gou, Fangfang | Wu, Jia
Article Type: Research Article
Abstract: With the development of Internet of Things technology, 5G communication has gradually entered people’s daily lives. The number of network users has also increased dramatically, and it has become the norm for the same user to enjoy the services provided by multiple network service providers and to complete the exchange and sharing of a large amount of information at the same time. However, the existing opportunistic social network routing is not sufficiently scalable in the face of large-scale network data. Moreover, only the transaction information of network users is used as the evaluation evidence, ignoring other information, which may lead …to the wrong trust assessment of nodes. Based on this, this study proposes an algorithm called Trust and Evaluation Mechanism for Users Based on Opportunistic Social Network Community Classification Computation (TEMCC). Firstly, communication communities are established based on community classification computation to solve the problem of the explosive growth of network data. Then a trust mechanism based on the Bayesian model is established to identify and judge the trustworthiness of the recommended information between nodes. This approach ensures that more reliable nodes can be selected for interaction and complete data exchange. Through simulation experiments, the delivery rate of this scheme can reach 0.8, and the average end-to-end delay is only 190 ms. Show more
Keywords: Trust mechanism, evaluation mechanism, community, opportunistic social networks
DOI: 10.3233/JIFS-232264
Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 2091-2108, 2024
Authors: Chen, Rong | Lan, Furong | Wang, Jianhua
Article Type: Research Article
Abstract: In order to effectively control the pressure and energy consumption of multiple air compressors within an acceptable range, an intelligent pressure switching control method for air compressor group control based on multi-agent RL is studied. This method uses sensors in the air compressor field control cabinet to collect data such as header pressure, air storage tank pressure, and air storage tank temperature and sends them to the edge data collector for integration. After integration, the main control cabinet sends them to the upper computer. Combined with the on-site collected data, a multi-agent-based air compressor group control model is designed to …convert multiple air compressors in the air compressor group control problem into a multi-agent mode, facilitating unified switching control of the air compressor group. Then, using the intelligent pressure switching control method based on deep Q-learning, driven by a neural network controller, the frequency of the frequency converter is adjusted to control the pressure at the outlet of the air compressor terminal header within the set value range, completing the pressure intelligent switching control. After testing, this method has good application results in pressure control, energy saving, and other aspects after being used for intelligent pressure switching control of air compressor group control. Show more
Keywords: Multi-agent, intensive learning, air compressor group control, pressure intelligence, neural network controller
DOI: 10.3233/JIFS-233217
Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 2109-2122, 2024
Authors: Xu, Huifen | Fang, Cheng | Zhang, Shuai
Article Type: Research Article
Abstract: Remanufacturing, with its environmental and economic implications, is gaining significant traction in the contemporary industry. Owing to the complementarity between remanufacturing process planning and scheduling in actual remanufacturing systems, the integrated remanufacturing process planning and scheduling (IRPPS) model provides researchers and practitioners with a favorable direction to improve the performance of remanufacturing systems. However, a comprehensive exploration of the IRPPS model under uncertainties has remained scant, largely attributable to the high complexity stemming from the intrinsic uncertainties of the remanufacturing environment. To address the above challenge, this study proposes a new IRPPS model that operates under such uncertainties. Specifically, the …proposed model utilizes interval numbers to represent the uncertainty of processing time and develops a process planning approach that integrates various failure modes to effectively address the uncertain quality of defective parts during the remanufacturing process. To facilitate the resolution of the proposed model, this study proposes an extended non-dominated sorting genetic algorithm-II with a new multi-dimensional representation scheme, in which, a new self-adaptive strategy, multiple genetic operators, and a new local search strategy are integrated to improve the algorithmic performance. The simulation experiments results demonstrate the superiority of the proposed algorithm over three other baseline multi-objective evolutionary algorithms. Show more
Keywords: Integrated remanufacturing process planning and scheduling, remanufacturing systems, uncertainty environment, interval processing time, non-dominated sorting genetic algorithm-II
DOI: 10.3233/JIFS-233408
Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 2123-2145, 2024
Authors: Xu, Dongsheng
Article Type: Research Article
Abstract: Universities are important talent training bases in China and the main driving force for achieving the strategic layout of “revitalizing the country through science and education” and “strengthening the country through talent". Oil painting is a global art with rich humanistic and artistic value. Most art colleges in China have set up oil painting courses. Analyze the current situation and value of oil painting course teaching in local art (teacher training) majors, and leverage the educational role of oil painting courses by enriching course offerings, emphasizing the integration of humanistic innovation, improving teacher literacy, and striving to further improve the …quality and efficiency of oil painting course teaching. The quality evaluation of oil painting teaching in universities is viewed as multiple-attribute decision-making (MADM). The grey relational analysis (GRA) is a useful tool to cope with the MADM issue. The probabilistic simplified Neutrosophic set (PSNSs) is easy to characterize uncertain information during the quality evaluation of oil painting teaching in universities. In this paper, in order to obtain the weight information, an optimization model implemented to obtain a simple and exact formula which can be employed to derive the attribute weights values based on the Lagrange function and the probabilistic simplified neutrosophic number grey relational analysis (PSNN-GRA) technique is implemented for MADM to rank the alternatives. Finally, a numerical example for quality evaluation of oil painting teaching in universities is used to verify the practicability of the PSNN-GRA technique and compares it with other techniques. Show more
Keywords: Multiple attributes decision making (MADM), probabilistic simplified neutrosophic sets (PSNSs), GRA technique, teaching quality evaluation
DOI: 10.3233/JIFS-235975
Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 2147-2159, 2024
Authors: Liu, Chen | Zhou, Kexin | Zhou, Lixin
Article Type: Research Article
Abstract: Stance detection for user reviews on social platforms aims to classify the stance of users’ reviews toward a specific topic. Existing studies focused on the internal semantic features of reviews’ texts, but ignored the external knowledge associated with the review. This paper retrieves external knowledge related to the key information of each review by mapping it to a knowledge graph. Thereafter, this paper infuses the external knowledge into deep learning model for stance detection. Considering that infusing external knowledge may bring noise to the model, this paper adopts the personalized PageRank method to filter the introduced irrelevant external knowledge. Infusing …external knowledge can improve the classification performance by providing background knowledge. In addition to considering the textual features of reviews when constructing the stance detection model, this paper employs a gated graph neural network (GGNN) approach to fuse the structural information between reviews to capture the interactions of reviews. The experiments show that the model improves 1.5% –6.9% in macro-average scores compared to six benchmark models in this paper. By combining the textual features and structural information of reviews and introducing external knowledge, the model effectively improves the stance detection performance. Show more
Keywords: Knowledge graph, structural information, gate graph neural network, stance detection
DOI: 10.3233/JIFS-224217
Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 2161-2177, 2024
Authors: Jayalakshmi, N. | Shanmugapriya, M.M.
Article Type: Research Article
Abstract: This study provides the generalization of fuzzy real numbers by imposing the elevator’s condition upon it’s legs. Our aim is to construct three types of Lift Fuzzy Real Numbers, an extension of h-generalized fuzzy real numbers, to indicate medical signals, stock market values, and commercial establishment profits over time. It explores concepts like ɛ-cut, strong ɛ-cut, β-level set, and convexity, and presents a graphical representation based on profit earned by three industries. Appropriate numerical examples are provided to support the new ideas. It’s interesting to note that Lift Fuzzy Real Numbers are also used to represent real numbers. Additionally, the …connections between the Lift Fuzzy real numbers have been established. The new fuzzy real numbers offer an advantage in representing data sets not represented by existing fuzzy numbers. Show more
Keywords: Fuzzy set, fuzzy number, α-cut, strong α-cut
DOI: 10.3233/JIFS-224320
Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 2179-2192, 2024
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