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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: Bhuvanya, R. | Kavitha, M.
Article Type: Research Article
Abstract: Online shopping is a form of electronic commerce that enables customers to purchase products directly from the seller over the internet using a web browser or a mobile application. With the growing number of research papers on Deep Learning (DL)-based recommendations, DL models have proven to be effective in Recommender systems. Hence in this paper, relevant product accessories recommendation is proposed using deep learning and histogram features. The proposed recommendation describes the novel way of content-based filtering which divides the work into two phases. In phase 1, the implemented approach determines the color and category of the product. In phase …2, the recommendation system retrieves the matching accessories for the chosen product. For phase 1, Decision Tree, Linear Regression, Logistic Regression, Naïve Bayes, Long Short-Term Memory (LSTM), and a novel method of Stack dense Recurrent Neural Network (RNN) along with the color histogram is applied to identify the category and color of the product. It is justified that the proposed technique of stack dense RNN achieves 98% accuracy. In phase 2, from the Machine Learning (ML) perspective, Random Forest (RF) is employed for the recommendation. The RF model finds the matching accessories for the chosen product and retrieves the top relevant items. Show more
Keywords: Deep learning, machine learning, recommender system, random forest, stack dense RNN
DOI: 10.3233/JIFS-223754
Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 1, pp. 1179-1193, 2023
Authors: Jannu, Chaitanya | Vanambathina, Sunny Dayal
Article Type: Research Article
Abstract: Over the past ten years, deep learning has enabled significant advancements in the improvement of noisy speech. Due to the short time stability of speech signal, previous speech enhancement (SE) methods concentrated only on magnitude estimation, and these methods added a phase of the mixture in reconstructing the speech. The performance is limited in these approaches since the phase will also carry some of the speech information. Some of the speech enhancement approaches were developed later to jointly estimate both magnitudes as well as phases. Recently, complex-valued models, like deep complex convolution recurrent network (DCCRN), are proposed, but the computation …of the model is very huge. In this work, we propose a Discrete Cosine Transform-based Densely Connected Convolutional Gated Recurrent Unit (DCTDCCGRU) model using dilated dense block and stacked GRU. The dense connectivity strengthens the gradient propagation by concatenating features from previous layers at the input. The advantage of the dense block is that at various resolutions, the dilated convolutions aid with context aggregation, and the dense connectivity provides a feature map with more precise target information by passing through multiple layers. To represent the correlation between neighboring noisy speech frames, a two Layer GRU is added in the bottleneck of U-Net. The experimental findings demonstrate that the proposed model outperformed the other existing models in terms of STOI (short-time objective intelligibility), PESQ (perceptual evaluation of the speech quality), and output SNR (signal-to-noise ratio). Show more
Keywords: SE-Speech enhancement, DTC-Discrete cosine transform, SNR-Signal to noise ratio, dense block
DOI: 10.3233/JIFS-223951
Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 1, pp. 1195-1208, 2023
Authors: Bektur, Gulcin
Article Type: Research Article
Abstract: In this study, an energy-efficient distributed flow shop scheduling (DFSS) problem with total tardiness minimisation and machine-sequence dependent setup times is addressed. A mixed integer linear programming (MILP) model is proposed for the problem. A variant of the NSGA II algorithm is suggested for the solution of large scale problems. The proposed algorithm is compared with the state-of-the-art NSGA II, SPEA II, and multiobjective iterated local search algorithm. The computational results show that the proposed algorithm is efficient and effective for the problem. This is the first study to propose a heuristic algorithm for the distributed flow shop scheduling problem …with total tardiness minimisation, speed scaling and setups. Show more
Keywords: Energy efficient scheduling, distributed flow shop scheduling, multiobjective optimisation, heuristic algorithms, minimisation of total tardiness, speed scaling mechanism
DOI: 10.3233/JIFS-224199
Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 1, pp. 1209-1222, 2023
Authors: Xu, Qian
Article Type: Research Article
Abstract: As the problem of sub-health continues to expand among urban residents, forestry tourism has been further developed, and forest wellness travel for the purpose of recuperation has gradually become the focus of transformation and upgrading of the current big health industry. In order to refine the evaluation of the development potential of regional forest health tourism and achieve further promotion of regional forest health tourism, the study first established the construction principles of the evaluation system, combined with expert consultation and theoretical analysis methods to select evaluation indicators, and used analytic hierarchy process to obtain the weight of each indicator. …An adaptive variational genetic algorithm was then proposed to improve the BP neural network to form the AGA-BP model, which was finally applied to the assessment of the progression potentiality of forest wellness travel. The outcomes demonstrate that among the assessment indicators of forest wellness travel progression potentiality, the environmental quality has the largest weight of 0.4598; the convergence and precision of the AGA-BP model proposed by the research have been upgraded by 80% and 50% respectively, with a faster global search speed; in the assessment of the regional forest wellness travel progression potentiality, the method is highly consistent with the actual assessment outcomes, with an average precision rate of 98% indicating that it can accurately and effectively conduct potentiality assessment, providing a methodological reference for the sustainable progression of forest wellness travel. Show more
Keywords: Forest recreation, tourism, progression potentiality, BP neural network
DOI: 10.3233/JIFS-230582
Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 1, pp. 1223-1234, 2023
Authors: Zou, Wang | Zhang, Wubo | Tian, Zhuofeng | Wu, Wenhuan
Article Type: Research Article
Abstract: In the field of text classification, current research ignores the role of part-of-speech features, and the multi-channel model that can learn richer text information compared to a single model. Moreover, the method based on neural network models to achieve final classification, using fully connected layer and Softmax layer can be further improved and optimized. This paper proposes a hybrid model for text classification using part-of-speech features, namely PAGNN-Stacking1 . In the text representation stage of the model, introducing part-of-speech features facilitates a more accurate representation of text information. In the feature extraction stage of the model, using the multi-channel attention …gated neural network model can fully learn the text information. In the text final classification stage of the model, this paper innovatively adopts Stacking algorithm to improve the fully connected layer and Softmax layer, which fuses five machine learning algorithms as base classifier and uses fully connected layer Softmax layer as meta classifier. The experiments on the IMDB, SST-2, and AG_News datasets show that the accuracy of the PAGNN-Stacking model is significantly improved compared to the benchmark models. Show more
Keywords: Text classification, part-of-speech features, multi-channel, stacking algorithm
DOI: 10.3233/JIFS-231699
Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 1, pp. 1235-1249, 2023
Authors: Chen, Huakun | Jia, Qianlei | Huang, Wei | Shi, Jingping | Safwat, Ehab
Article Type: Research Article
Abstract: There is a growing body of literature that recognises the importance of Z-numbers proposed by Prof Zadeh. However, due to the complicated structure and short presentation time, many unknowns about Z-numbers still exist. To fill these gaps, this study aims to make use of rectangular coordinate system to express linguistic Z-numbers. Simultaneously, this study sets out to design a score function to quantify the information contained in different Z-numbers. Subsequently, distance measure and similarity measure are also presented from the perspective of coordinate system. Besides, linguistic discrete Z-numbers and belief rule base (BRB) model are combined to construct a novel …reasoning model on the basis of implication operators. To verify the validity of the proposed method, three representative examples of epidemic level assessment, multicriteria group decision-making (MCGDM), and network security assessment are employed. The comparison with other widely used methods are performed to further demonstrate the superiority of the proposed method. Show more
Keywords: Linguistic Z-numbers, score function, rectangular coordinate system, distance measure, similarity measure
DOI: 10.3233/JIFS-223025
Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 1, pp. 1251-1268, 2023
Authors: Zhu, Zhihui | Zhu, Meifang
Article Type: Research Article
Abstract: In recent years, chronic diseases, an aging population, and high healthcare costs have become global concerns. The Internet of Things (IoT) is transforming society by enabling physical objects to sense and collect data about their surroundings. It has evolved to encompass a wide range of sensing strategies, and it continues to improve in terms of sophistication and cost reduction. IoT can play an important role in enhancing human health through remote healthcare. The application of advanced IoT technology in healthcare is still a significant challenge due to a number of issues, such as the shortage of cost-effective and accurate smart …medical sensors, the absence of standardized IoT architectures, the heterogeneity of connected wearable devices, the multidimensionality of data generated, and the need for interoperability. In order to provide insight into the advance of IoT technologies in healthcare, this paper presents a comprehensive discussion on IoT device capabilities, focusing on the hardware and software systems, as well as the processing abilities, operating systems, and built-in tools. Show more
Keywords: Healthcare, internet of things, medical device, wireless sensor networks, data management, literature review
DOI: 10.3233/JIFS-224166
Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 1, pp. 1269-1288, 2023
Authors: Yuan, Pei
Article Type: Research Article
Abstract: With the globalization of the world’s economy, culture, science and technology, and the increasing frequency of international cooperation and exchanges, English will play an increasingly important role. For non-English majors in Chinese colleges and universities, college English is a public compulsory basic course, which plays a very important role in expanding students’ knowledge, improving foreign language cultural literacy and comprehensive language use ability. An important part of college English classroom teaching is teaching evaluation, which not only helps teachers obtain teaching feedback information, improve teaching management, and ensure teaching quality, but also effectively helps students adjust learning strategies, improve learning …methods, and improve learning efficiency. The English classroom teaching quality evaluation could be deemed as a classic multiple attribute group decision making (MAGDM) problem. In this paper, as a useful outranking approach, the extended QUALIFLEX method is utilized to address some MAGDM issues by using picture 2-tuple linguistic sets (P2TLSs). In addition, integrating the QUALIFLEX method with P2TLSs, the extended QUALIFLEX method with P2TLNs is constructed and all calculating procedures are simply depicted. Eventually, an empirical application of English classroom teaching quality evaluation has been offered to demonstrate this novel method. Show more
Keywords: Multiple attribute group decision making (MAGDM), picture fuzzy sets (PFSs), picture 2-tuple linguistic sets (P2TLSs), the extended QUALIFLEX method, English classroom teaching quality evaluation
DOI: 10.3233/JIFS-230969
Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 1, pp. 1289-1302, 2023
Authors: Jin, Xiaofang
Article Type: Research Article
Abstract: The huge demand for translation talents has prompted the universities to focus on improving the quality of translation teaching. As a necessary means to improve teaching quality, translation teaching quality (TTQ) evaluation plays a role in guiding, regulating and managing translation teaching, and is an important part of translation teaching. The TTQ evaluation of college English is affirmed as multi-criteria group decision-making (MCGDM). The purpose of this article is to proposed a new improved grey relation analysis (GRA) method based on cumulative prospect theory (CPT-GRA) to solve the MCGDM under IVNSs. At the end of this paper, an example for …TTQ evaluation of college English is illustrated through the built method and the comparison of this new method with other proposed IVNSs methods demonstrates the availability and difference of this method. Show more
Keywords: Multi-Criteria Group Decision-Making (MCGDM), interval-valued neutrosophic sets (IVNSs), Grey relation analysis (GRA), Cumulative Prospect Theory (CPT), translation teaching quality (TTQ) evaluation
DOI: 10.3233/JIFS-231191
Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 1, pp. 1303-1312, 2023
Authors: Li, Yan
Article Type: Research Article
Abstract: With the development of socialist market economy, the exhibition industry has emerged as the tertiary industry matures in a globalized economic environment. As a new economic form, the exhibition economy presents new opportunities for economic development. The research on the exhibition industry at home and abroad has been relatively mature, and there has been a scientific analysis of the industrial linkage effect of the exhibition industry. The strong industrial linkage effect has made the exhibition industry occupy a very important position in the economic development of cities. However, in the development of China’s urban exhibition industry today, it is no …longer a simple question of developing and enhancing the strategic position of the exhibition industry in economic development, but rather a question of how to enhance the competitiveness of China’s urban exhibition industry. Only when the level of competitiveness is improved can the economic and social benefits brought by the exhibition industry be brought into full play. The fuzzy comprehensive competitiveness evaluation of urban exhibition industry is a classical multiple attribute decision making (MADM) problems. Recently, the TODIM and VIKOR method has been used to cope with MAGDM issues. The hesitant fuzzy sets (HFSs) are used as a tool for characterizing uncertain information during the fuzzy comprehensive competitiveness evaluation of urban exhibition industry. In this manuscript, the hesitant fuzzy TODIM-VIKOR (HF-TODIM-VIKOR) method is built to solve the MADM under HFSs. In the end, a numerical case study for fuzzy comprehensive competitiveness evaluation of urban exhibition industry is given to validate the proposed method. Show more
Keywords: Multiple attribute decision making(MAGDM), Hesitant fuzzy sets (HFSs), TODIM, VIKOR, urban exhibition industry
DOI: 10.3233/JIFS-231672
Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 1, pp. 1313-1323, 2023
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