Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Purchase individual online access for 1 year to this journal.
Price: EUR 315.00Impact Factor 2024: 1.7
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: Cai, Mingqian | Zhou, Ligang | Chen, Mingxian | Chen, Huayou
Article Type: Research Article
Abstract: Linguistic q-rung orthpair fuzzy sets (Lq-ROFSs) can facilitate describing the uncertainty and the vagueness information existing in the real world. Based on the advantages of Lq-ROFSs, this paper innovatively puts forward a new method to solve the multi-attribute group decision-making (MAGDM) problems when the attribute weight is completely unknown, and proves the feasibility and effectiveness of this method through illustrative examples. Firstly, we propose the linguistic q-rung orthopair fuzzy generalized power average (Lq-ROFGPA) operator, which considers not only the importance of the data itself, but also the interaction between the data, and prove its properties. In particular, the linguistic q-rung …orthopair fuzzy weighted generalized power average (Lq-ROFWGPA) operator takes into account the weight between data, which can better aggregate evaluation information. Then, we introduce decision making trial and evaluation laboratory (DEMATEL) method of the linguistic q-rung orthpair fuzzy numbers (Lq-ROFNs) to analyze the causal relationship and key elements of complex systems. Based on DEMATEL method, we further develop a weight model to calculate the attribute weights, which can make up for the deficiency which is the influence of the interaction between attributes that the existing weight determination method for Lq-ROFNs does not consider. Finally, we present a new MAGDM method based on the Lq-ROFWGPA operator and DEMATEL method. Further, several practical examples are given to illustrate the effectiveness and superiority of this new method in comparison with other existing MAGDM methods. Show more
Keywords: Multiple-attribute group decision-making, linguistic q-rung orthopair fuzzy numbers, generalized power average operator, DEMATEL
DOI: 10.3233/JIFS-230712
Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 639-658, 2024
Authors: Wang, Pingping | Chen, Jiahua
Article Type: Research Article
Abstract: As a decision information preference which includes membership degree (MD), non-membership degree (NMD), and probability, the probabilistic dual hesitant fuzzy set (PDHFS) is a crucial tool for effectively expressing uncertain information. In the domains of multi-attribute decision making (MADM) and multi-attribute group decision making (MAGDM), distance measures are extremely helpful tools. In this study, a novel PDHFS distance measure is put out, on which a MAGDM method that takes decision-makers’ (DMs’) psychological behavior into account is proposed. First, a novel distance measure is put forward to effectively assess the difference between different PDHFSs by adding consideration of the distances between …MDs and between NMDs. Second, a similarity-trust analysis method based on the new distance measure is employed to calculate expert weights for integrating group decisions, and the group satisfaction index and regret theory are extended to a probabilistic dual hesitant fuzzy information environment. A MAGDM method based on the novel distance measure and regret theory is proposed. Finally, the proposed method is applied to the selection of radiation protection strategies in nuclear power plants, and it is also determined through parametric analysis that DMs’ tendency to avoid regret has an impact on the outcomes of decisions. When the method proposed in this study is compared to existing approaches, the findings demonstrate that the method’s performance in resolving MAGDM issues in a PDHFS environment is superior. Show more
Keywords: Multi-attribute group decision making, probabilistic dual hesitant fuzzy set, distance measures, regret theory, EDAS, similarity-trust analysis
DOI: 10.3233/JIFS-233148
Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 659-675, 2024
Authors: Quyang,
Article Type: Research Article
Abstract: The completion degree of sports training can not reach the corresponding standard, and the training effect will be greatly weakened. In order to improve the effect of sports training, the evaluation method of sports training completion degree based on deep residual network is studied. The image collector based on ARM is used to collect the action images of athletes in sports training, and the collected action images are preprocessed based on spatial scale filtering and regression factors. Construct a depth residual network, learn the implicit relationship between athletes’ state and the dynamic change process of sports training actions through off-line …training, and train the model; In the online application process, the preprocessed action images will be input into the trained evaluation model to evaluate the athletes’ sports training action completion in real time. At the same time, residual shrinkage unit and attention mechanism are used to optimize the depth residual network, which improves the training efficiency and evaluation performance of the network. The experimental results show that this method has good evaluation performance under the condition of setting parameters, and can effectively improve the effect of physical training. Show more
Keywords: Deep residual network, sports training, action completion degree, image acquisition, image denoising
DOI: 10.3233/JIFS-233773
Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 677-691, 2024
Authors: Naik, N.V. | Hyma, J. | Prasad Reddy, P.V.G.D.
Article Type: Research Article
Abstract: Retinal fundus imaging has been used in the diagnosis of many cardiovascular and retinal-related diseases like age-related macular degeneration, pathological myopia, diabetic retinopathy, and glaucoma. In recent years, the computerized technique is adapted to fundus image analysis and processing for quick diagnosis. However, low-quality retinal pictures are produced when certain eye disorders and photographic circumstances exist. Poor-quality retinal pictures of this kind are not helpful for diagnosis, particularly when using automated image analysis software. The causes for degradation include low illumination, high illumination, image blurring, uneven illumination, low contrast, and color distortion. Several image-enhancing techniques have been developed to address …this; however, they may result in sudden changes in color levels, false borders, and the loss of picture detail, particularly in retinal images. To prevent these negative consequences, this paper proposed a novel enhancement algorithm EGF_AGC (Enhanced Guided Filter+Adaptive Gamma Correction) for color fundus retinal images. The proposed method is worked is described in four steps. The first stage of the recommended procedure is to utilize a hybrid filter to enhance the retinal pictures’ appearance details. Next, applied enhanced guided filter method to the detailed retina images to enhance the image quality. Moreover, the suggested technique also worked to retain uneven illumination issues raised in retina images using the Adaptive Gamma Correction method. The final improved retinal pictures are created by combining the phases before utilizing the HSV color approach. The databases of retinal images, which include the STARE, the DRIVE, and the CHBASE_DB1 database, were utilized to determine image enhancement effects. The findings were compared with CLAHE, Bilateral Filter, Guided Filter, and Gamma Correction retinal enhancement methods. Compared to similar enhancement approaches, experiments showed that our method could give a competitive outcome and eliminate degradation caused by low-quality fundus pictures. Show more
Keywords: Image enhancement, illumination problem, guided filter, retina images, diabetic retinopathy
DOI: 10.3233/JIFS-235991
Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 693-709, 2024
Authors: Chunhong, Zhao | Jinglei, Nie | Shuwen, Yin | Dingyu, Zhang | Chengmo, Li
Article Type: Research Article
Abstract: The design and implementation of teachers’ classroom teaching strategies is the key to the success of second language classroom teaching. In order to improve the quality of second-language classroom teaching in universities and enhance the interactivity in the teaching process, the application of virtual reality technology in second-language classroom teaching in universities is studied. Firstly, an integrated ware platform is designed for second language classroom teaching in universities, which consists of an integrated ware library and a database. Then virtual reality technology is used to design an integrated ware library within the platform and collect information such as various teaching …media resources designed in the classroom teaching content into the integrated ware library; Utilize 3DS Max software in virtual reality technology to construct three-dimensional models of teaching scenes and entities; Choose to use linear difference method to render 3D model colors; From a visual perspective, enhance the realism of the rendered model through image enhancement technology and color contrast enhancement technology. According to the functions of the physical object, various interactive events are added to the created teaching scene and the three-dimensional model of the entity and stored in the integrable ware library to achieve panoramic roaming of the second language classroom teaching scene in universities. The experimental results show that the teaching platform designed by this method can accurately construct three-dimensional models of teaching scenes and objects with good visual effects, providing users with a more realistic sensory experience and effectively improving students’ mastery of teaching content. Show more
Keywords: Virtual reality technology, classroom teaching, 3D model, color rendering, panoramic walkthrough
DOI: 10.3233/JIFS-233210
Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 711-722, 2024
Authors: Kaijun, Zhao
Article Type: Research Article
Abstract: To enhance the psychological resilience of athletes, a method for evaluating the psychological resilience of High-intensity Interval Training (HIIT) athletes based on evolutionary neural networks is studied. From the six criteria of frustration coping, personal characteristics, self-promotion, self-regulation, internal protection and external protection, the evaluation index of psychological resilience of athletes in sports High-intensity Interval Training is selected; the audition indicators are qualitatively analyzed according to the principle of indicator selection, and the indicators that do not meet the requirements are eliminated; Cluster analysis and coefficient of variation analysis are used to carry out quantitative analysis on the remaining evaluation …indicators after qualitative analysis; the indicators after quantitative analysis are improved, to build the assessment index system of psychological resilience of athletes in high-intensity sports training. The Back Propagation (BP) neural network is optimized by a genetic algorithm, and the evolutionary neural network is constructed. The index data set is input into the evolutionary neural network as a sample, and the index weight value is output through training. The evaluation result and corresponding evaluation grade are determined based on the index weight value and membership degree. The experimental results show that when the number of hidden layers is 3, the calculation of evaluation index weights is the best; The weight of personal traits obtained from the evaluation results is the highest (0.206), while the weight of external protection is the lowest (0.151), and the evaluation results are basically consistent with the expert results. The above results show that this method can accurately evaluate the psychological resilience of athletes and significantly enhance their psychological resilience. Show more
Keywords: Evolutionary neural network, evaluation of psychological resilience, index system construction, genetic algorithm, weight calculation
DOI: 10.3233/JIFS-233299
Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 723-737, 2024
Authors: Lei, Hongquan | Li, Diquan | Jiang, Haidong
Article Type: Research Article
Abstract: Traditional sonar image target detection analysis has problems such as long detection time, low detection accuracy and slow detection speed. To solve these problems, this paper will use the multi-feature fusion sonar image target detection algorithm based on the particle swarm optimization algorithm to analyze the sonar image. This algorithm uses the particle swarm algorithm to optimize the combination of multiple feature vectors and realizes the adaptive selection and combination of features, thus improving the accuracy and efficiency of sonar image target detection. The results show that: when other conditions are the same, under the particle group optimization algorithm, the …sonar image multiple feature detection algorithm for three sonar image detection time between 4s-9.9s, and the sonar image single feature detection algorithm of three sonar image detection time between 12s-20.9s, shows that the PSO in multiple feature fusion sonar image target detection with better performance and practicability, can be effectively applied to the sonar image target detection field. Show more
Keywords: Sonar images, particle swarm optimization algorithm, target detection, multi-feature fusion, single multi-feature fusion
DOI: 10.3233/JIFS-234876
Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 739-751, 2024
Authors: Kavitha, J.C. | Subitha, D.
Article Type: Research Article
Abstract: Automatic image thresholding is commonly used in the area of computer vision and pattern recognition for object detection. This research work proposes a new method of lesion detection in dermoscopic images using an optimal threshold based on the Newton-Raphson iteration algorithm for diagnosing melanoma. The proposed method incorporates a new strategy of finding the optimal threshold using first-order and second-order edge derivatives. The first- and second-order derivatives values obtained from the images are applied in the Newton-Raphson method which, in turn, converges to a value after a number of iterations. The converged value is considered the optimal threshold and used …as a parameter for the separation of lesion regions from healthy skin in dermoscopic images. To test the proposed system performance, the experiment is carried out on two standard data sets, the ISIC Archive and the PH2, of dermoscopic images using different classifiers such as the Naive Bayes (NB), AdaBoost and Bag of Visual words (BOVW). The proposed segmentation technique segments the lesion regions from skin images and Bag of visual words classifier classifies the dermoscopic images into different classes namely common nevi, atypical nevi and melanoma. The proposed thresholding-based segmentation performance is compared against the Otsu method and Otsu using genetic algorithm. The experimental findings reveal that the proposed Newton-Raphson iterative method surpasses various state-of-the-art and recent methods in relation to computational speed, error rate, sensitivity, and accuracy. Show more
Keywords: Image segmentation, edge detection, optimal threshold, newton raphson iterative method, bag of visual words classifier
DOI: 10.3233/JIFS-235990
Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 753-767, 2024
Authors: Anisha, C.D. | Arulanand, N.
Article Type: Research Article
Abstract: The Spiral Drawing Test (SDT) has become a prominent clinical marker for the early diagnosis of Parkinson’s Disorder (PD) by capturing tremor symptoms. The integration of AI algorithms into a PD diagnosis system has proven to be a breakthrough objective assessment that aids professionals in decision-making. However, there is a need for improvisation of the workflow architectures of AI models to optimize the diagnosis system by reducing the misdiagnosis rate. The proposed system presents PD prediction using a Spiral Drawing Test (SDT) image modality integrated with an Artificial Intelligence (AI) algorithm. The proposed study presents three hybrid workflow architectures formed …by integrating three core layers: a data augmentation layer, Transfer Layer (TL)-based feature extraction layer, and Deep Learning (DL)-based classification layer. The results were analyzed by conducting 18 experiments based on the hyperparameter values and workflow architectures. The highest accuracy obtained by the proposed study is 98% for Hybrid Workflow Architecture II. Show more
Keywords: Parkinson disorder, transfer learning
DOI: 10.3233/JIFS-231202
Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 769-787, 2024
Authors: Li, Zehao | Wang, Shunli | Yu, Chunmei | Qi, Chuangshi | Shen, Xianfeng | Fernandez, Carlos
Article Type: Research Article
Abstract: The development of a secure battery management system (BMS) for electric vehicles depends heavily on the correct assessment of the online state-of-charge (SOC) of Li-ion batteries. The ternary lithium battery is used as the research object in this paper, and a second-order RC equivalent circuit model is developed to characterize the dynamic operating characteristics of the battery. In order to solve the problem that the adaptive unscented Kalman filter (AUKF) algorithm is easy to fail SOC estimation because the error covariance matrix is not positively definite due to the incomplete accuracy of the equivalent circuit model, a corresponding solution is …proposed. Considering the poor real-time battery SOC estimate caused by the battery model’s fixed parameters, therefore we propose the Variable Forgetting Factor Recursive Least Squares (VFFRLS) algorithm for joint estimation of Li-battery SOC and the Singular Value Decomposition-AUKF (SVD-AUKF) algorithm. The SVD-AUKF algorithm can accurately estimate the SOC of the battery when the error covariance is negative. The algorithm can be adaptively adjusted in both the parameter identification and SOC estimation stages, which can effectively solve the problem of poor estimation accuracy caused by fixed parameters. According to experiments, under two separate dynamic operating situations, the joint estimation algorithm’s error is less than 2%, and its stability has also been greatly enhanced. At the same time, when the initial SOC value is set incorrectly, the convergence time of the algorithm proposed in this paper can reach within 2.1 seconds for BBDST and DST conditions, which can be well adapted to complex working conditions. Show more
Keywords: Lithium-ion battery, second-order RC equivalent circuit model, charge state, adaptive unscented Kalman filter algorithm, variable forgetting factor recursive least squares, singular value decomposition, error covariance
DOI: 10.3233/JIFS-231433
Citation: Journal of Intelligent & Fuzzy Systems, vol. 46, no. 1, pp. 789-803, 2024
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
sales@iospress.com
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
info@iospress.nl
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office info@iospress.nl
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
china@iospress.cn
For editorial issues, like the status of your submitted paper or proposals, write to editorial@iospress.nl
如果您在出版方面需要帮助或有任何建, 件至: editorial@iospress.nl