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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: Ye, Qiang | Zhang, Juwei | Chen, Quankun
Article Type: Research Article
Abstract: Different number of broken wires produce different grooves on the surface of steel wire rope. Based on the local structural features of these grooves, a new broken wire identification method is proposed. By comparing the processing effects of various image enhancement methods, a processing method called adaptive histogram equalization is selected to process the broken wire image. Aiming at a large amount of useless information in structural features extracted by HOG algorithm, a encoder-decoder neural network is designed to reduce the dimension of features. In addition, to effectively avoid information loss caused by the output layer of the BP neural …network, a joint algorithm of the BP neural network and the support vector machine is proposed. The experimental results show that using image enhancement technology to process broken wire images can effectively improve the recognition rate of broken wires; The structural features extracted by HOG algorithm are more beneficial to the quantitative recognition of broken wires than the texture features extracted by LBP operator; Compared with various dimensionality reduction methods, neural network can retain more effective information; The joint algorithm can improve the recognition rate of broken wire by at least 0.25% on the basis of BP neural network. Show more
Keywords: Steel wire rope, neural network, HOG, support vector machine
DOI: 10.3233/JIFS-231259
Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 3, pp. 4337-4347, 2023
Authors: Dingjun, He | Liang, Xu | Hui, Yang
Article Type: Research Article
Abstract: Box girders are commonly utilized in bridge engineering because of their economical and visually appealing form. Due to recent advancements in the design sector. However, safety in the economy is the fundamental demand of the current generation, therefore, it is vital to pick an optimal design. Prestrained concrete is used for large-span bridges. Standard heuristic optimization is frequently used to do structural optimization because of how complex structural concerns remain. However, traditional heuristic optimization still takes a significant amount of time. Particle Swarm trained Hierarchically Stepped Adversarial Networks (PS-HSAN) are presented as an alternative approach to speeding up the optimization …of complex problems, and their use reduces the cost of computation for optimization. To find the best design for “a three-span continuous box-girder pedestrian bridge, this research” will apply both classical heuristic optimization and PS-HSAN. This will include analyzing and assessing a variety of crime types and sample sizes. Particle swarm optimization is shown to be as effective as conventional heuristic optimization but with significant time savings. Therefore, using a PS-HSAN in structural design challenges provides an original method for handling certain structural difficulties that need a great degree of computing power while simplifying the solution of other problems. Show more
Keywords: Box girder bridge, Particle Swarm trained hierarchically stepped adversarial networks (PS-HSAN), Particle swarm optimization, structural optimization, the optimal solution
DOI: 10.3233/JIFS-231309
Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 3, pp. 4349-4360, 2023
Authors: Xia, Zhile | Mou, Jinping
Article Type: Research Article
Abstract: In this paper, the containment control problem of second-order nonlinear heterogeneous multi-agent system is studied. In order to deal with complex uncertainties such as unknown parts, uncertainties, and input constraints in the system, we designed a distributed fuzzy adaptive controller. The interval type-II (IT2) fuzzy set is adopted to deal with the uncertainty of membership functions. We construct a matrix equality and a matrix inequality to deal with the asymmetric Laplace matrix. The controller designed is simple and the designed controller only uses the information of itself and its neighbors. Therefore, it is very easy to be compensated in practice. …Finally, a simulation example is introduced to verify the effectiveness of the proposed methods. Show more
Keywords: Containment problem, fractional-order systems, heterogeneous multi-agent systems, distributed type-II fuzzy adaptive controller
DOI: 10.3233/JIFS-231350
Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 3, pp. 4361-4370, 2023
Authors: Pushpa, M. | Sornamageswari, M.
Article Type: Research Article
Abstract: The requisite of detecting Autism in the initial stage proposed dataset is exceptionally high in the recent era since it affects children with severe impacts on social and communication developments by damaging the neural system in a broader range. Thus, it is highly essential to identify this Autism in the primary stage. So many methods are employed in autism detection but fail to produce accurate results. Therefore, the present study uses the data mining technique in the process of autism detection, which provides multiple beneficial impacts with high accuracy as it identifies the essential genes and gene sequences in a …gene expression microarray dataset. For optimally selecting the genes, the Artificial Bee Colony (ABC) Algorithm is utilized in this study. In contrast, the feature selection process is carried out by five different algorithms: tabu search, correlation, information gain ratio, simulated annealing, and chi-square. The proposed work utilizes a hybrid Extreme Learning Machine (ELM) algorithm based Adaptive Neuro-Fuzzy Inference System (ANFIS) in the classification process, significantly assisting in attaining high-accuracy results. The entire work is validated through Java. The obtained outcomes have specified that the introduced approach provides efficient results with an optimal precision value of 89%, an accuracy of 93%, and a recall value of 87%. Show more
Keywords: Autism, data mining, gene expression, gene selection, hybrid classifier
DOI: 10.3233/JIFS-231608
Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 3, pp. 4371-4382, 2023
Authors: Prasad, Padavala Sai | Nair, Prabha Shreeraj | Patil, Anagha | Patil, Nilesh Madhukar | Chaturvedi, Abhay | Taqui, Syed Noeman | Almoallim, Hesham S. | Alharbi, Sulaiman Ali | Raghavan, S.S.
Article Type: Research Article
Abstract: For many, Covid-19 is a short-term, mildly debilitating disease. But some people are still struggling with monthly symptoms with persistent inflammation, chronic pain and shortness of breath. The situation of “long-term cowardice” has become so debilitating that it is now common for some to say that they are tired even if they walk a short distance. So far, the focus has been on saving lives from the plague. But now there are growing concerns about people facing the long-term consequences of the COVID epidemic. The fundamental question, with the uncertainty of whether those with chronic goiter, or all those affected, …will fully recover is raised. In this paper a smart monitoring model was proposed to keep monitoring the COVID patient’s health conditions. The smart method keep on watching the different changes reflected in the body conditions and ensure the changes in the database. In case any emergency is raised, then these smart monitoring tools inform the information to the doctors. This can very much helpful for the patients to communicate with the doctors. Show more
Keywords: Health care, inflammation, chronic pain, long-term consequences, COVID epidemic
DOI: 10.3233/JIFS-231899
Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 3, pp. 4383-4393, 2023
Authors: Dou, Weiwei
Article Type: Research Article
Abstract: The so-called “college English” teaching quality evaluation is to provide a basic, comprehensive, and realistic evaluation of the relevant aspects and management of teaching implementation on the basis of following the general laws of higher education; It is a comprehensive inspection of “College English” teaching and an important means of quality monitoring and policy adjustment for “College English”. As mentioned earlier, teaching evaluation is a comprehensive evaluation of teaching. Therefore, our evaluation of the quality of university public education is actually an examination of our specific measures in evaluating teaching, teaching methods and methods, teaching literature, and other aspects. The …college public English teaching quality evaluation is a classical multiple attribute decision making (MADM). In this paper, we define the triangular Pythagorean fuzzy sets (TPFSs) and investigate the MADM problems under TPFSs. Based on the traditional dual generalized weighted Bonferroni mean (DGWBM) operator and dual generalized weighted geometric Bonferroni mean (DGWGBM) operator, some triangular Pythagorean fuzzy operators are proposed: triangular Pythagorean fuzzy DGWBM (TPFDGWBM) operator and triangular Pythagorean fuzzy DGWGBM (TPFDGWGBM) operator. Accordingly, we have took advantage of these operators to develop some approaches to work out the triangular Pythagorean fuzzy MADM. Ultimately, a practical example for college public English teaching quality evaluation is took advantage of to validate the developed approach, and an influence analysis of the parameter on the final results is been presented to attest its availability and validity. Show more
Keywords: Multiple attribute decision making (MADM), Triangular Pythagorean fuzzy set, Dual generalized weighted Bonferroni mean (DGWBM) operator, Dual generalized weighted geometric Bonferroni mean (DGWGBM) operator, English teaching quality evaluation
DOI: 10.3233/JIFS-232581
Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 3, pp. 4395-4414, 2023
Authors: Shi, Huanyu | Li, Ning | Liu, Yinuo
Article Type: Research Article
Abstract: In the wake of the wide promotion of 5G network, the era of super-high-speed networks and the Internet of Everything is approaching. Combining digital technologies led by 5G with landscape architecture has become an important way for the sustainable development of garden ecology. In order to achieve refined management of gardens and improve the accuracy and consistency of garden environmental data monitoring, this study constructs a new IoT sensor multi data fusion algorithm model. Considering the high redundancy and large error data collected by multiple sensors, this paper proposes a multi data fusion algorithm based on adaptive trust estimation and …improved D-S evidence theory. The experimental data demonstrates that matched with IGA-BP, algorithm in this paper obtained the largest fitness value and the fastest convergence speed in three sensor application scenarios with different numbers of nodes. The lowest values were obtained in terms of unit energy consumption and network latency indicators. In the monitoring experiment for environmental data of landscape architecture, the algorithm obtained lower relative error and mean square error than IGA-BP in four environmental parameters of temperature, humidity, light intensity and carbon dioxide concentration. Therefore, the algorithm is effective in real-time monitoring of landscape garden environmental data, and can provide decision-making data for garden management as a reference. Show more
Keywords: 5G, sensor, multi-data fusion algorithm, internet of things, landscape architecture
DOI: 10.3233/JIFS-223961
Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 3, pp. 4415-4425, 2023
Authors: Kumar, Amit | Dhiman, Pooja
Article Type: Research Article
Abstract: The reliability of an industrial system plays a significant role in new technological era where everyone is concerned about the performance of associated industry. With the frequent demands of the customers, the job of the production industries becomes more tedious to produce the required products at a high rate. To fulfill the customer’s demand, the initial focus of the industries is to work well without any interruption/failure in the entire production process. In this paper, Reliability, Availability, MTTF, MTTR, MTBF, ENOF is proposed for an industrial system namely “Injection moulding machine”. For this, the membership function for right triangular generalized …fuzzy numbers (RTrGFN) is proposed with the certain level of confidence. The real data of the Injection moulding machine is taken to validate the proposed methodology. The input data is extracted from the records/maintenance sheets of several years and found uncertainty due to the loss of any information or human mistakes. The parameters of the system like failure rate and repair time is retrieved. Based on data, AND-OR combination for the system is constructed. The lambda-tau methodology along with RTrGFN and its corresponding arithmetic operations is used for the performance analysis of the considered “Injection moulding machine”. For better understanding the results are discussed with the aid of graphs. Also after seeing the result one can conclude that this methodology is one of the best methodology for the performance analysis of a conventional system. Also authors have added the highlights and future scope of the research work at the end of the manuscript. Show more
Keywords: Reliability indicators, right triangular generalized fuzzy number, alpha cuts, injection moulding machine
DOI: 10.3233/JIFS-224022
Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 3, pp. 4427-4445, 2023
Authors: Karunanidhi, Bavithra | Ramasamy, Latha | Sathiasamuel, Charles Raja | Manivannan Sudha, Vasanth
Article Type: Research Article
Abstract: Among the list of reliability issues in Photovoltaic (PV) systems, partial shading is one of the crucial issues that affect the row current creating a wide range of current differences between rows these results in reduced output power and panel life span by creating hotspots. It also creates difficulty in tracking the power, because of multiple hotspot peaks obtainable in PV and IV (Current-Voltage) curves. Physical relocation of panels during shade occurrence is not an encouraging solution because of rooftop solar and domestic PV systems, where the area for PV installation is a ceiling. The optimization-based controller is retrofitted for …the electrical relocation of panels. It is developed based on the Cuckoo Search Algorithm (CSA), which aims to reduce the row current difference with a minimum reposition of panels as constraints. For the 9*9 PV arrangement, the row current ranges from 3.747 A to 8.424 A. It is reduced and almost made zero. Hence, the Fill factor raises from 38.073 to 51.707%. The power output is enhanced by about 20%. To prove the algorithm’s novelty a shading case for 4*3 asymmetric array arrangement is also considered for simulation studies. The proposed system proves to be economically beneficent for PV users. The performance of CSA is compared with PSO, Skyscraper, and SuDoKu. An economic analysis is carried out that adds the PV efficiency value to the proposed CSA algorithm. The real-time experimental validation holds good for 3*3 solar array agreement with theoretically simulated results. Show more
Keywords: Optimization-based shade dispersion controller, Cuckoo Search Algorithm, power output enhancement, fill factor, mismatch losses
DOI: 10.3233/JIFS-224137
Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 3, pp. 4447-4468, 2023
Authors: Huang, Ke | Zhang, Limin
Article Type: Research Article
Abstract: In the construction process, wearing a safety helmet is an important guarantee for personnel safety. However, manual detection is time-consuming, labor-intensive, and unable to provide real-time monitoring. To address this issue, a helmet-wearing detection algorithm has been proposed based on YOLOv5s. The algorithm uses the YOLOv5s network and introduces the CoordAtt coordinate attention mechanism module into its backbone to consider global information and improve the network’s ability to detect small targets. To improve feature fusion, the residual block in the backbone network has been replaced by a Res2NetBlock structure. The experimental results show that compared to the original YOLOv5 algorithm, …the accuracy and speed of the self-made helmet data set have improved by 2.3 percentage points and 18 FPS, respectively. Compared to the YOLOv3 algorithm, accuracy and speed have improved by 13.8 percentage points and 95 FPS, respectively, resulting in a more accurate, lightweight, efficient, and real-time helmet-wearing detection. Show more
Keywords: Helmet wearing detection, YOLOv5s, CoordAtt, Res2NetBlock
DOI: 10.3233/JIFS-230666
Citation: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 3, pp. 4469-4482, 2023
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