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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: Zhang, Dabin | Yu, Zehui | Ling, Liwen | Hu, Huanling | Lin, Ruibin
Article Type: Research Article
Abstract: As CO2 emissions continue to rise, the problem of global warming is becoming increasingly serious. It is important to provide a robust management decision-making basis for the reductions of carbon emissions worldwide by predicting carbon emissions accurately. However, affected by various factors, the prediction of carbon emissions is challenging due to its nonlinear and nonstationary characteristics. Thus, we propose a combination forecast model, named CEEMDAN-GWO-SVR, which incorporates multiple features to predict trends in China’s carbon emissions. First, the impact of online search attention and public health emergencies are considered in carbon emissions prediction. Since the impact of different variables …on carbon emissions is lagged, the grey relational degree is used to identify the appropriate lag series. Second, irrelevant features are eliminated through RFECV. To address the issue of feature redundancy of online search attention, we propose a dimensionality reduction method based on keyword classification. Finally, to evaluate the features of the proposed framework, four evaluation indicators are tested in multiple machine learning models. The best-performed model (SVR) is optimized by CEEMDAN and GWO to enhance prediction accuracy. The empirical results indicate that the proposed framework maintains good performance in both multi-scenario and multi-step prediction. Show more
Keywords: Carbon emissions prediction, online search attention, machine learning, time series forecasting
DOI: 10.3233/JIFS-236451
Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-16, 2024
Authors: Luo, Zhenrong | Jiang, Lei
Article Type: Research Article
Abstract: In order to construct an evaluation index system suitable for tourism management classroom teaching, this article evaluates the teaching effectiveness of teachers and improves the teaching quality of tourism management courses. This article is based on developmental evaluation theory, using Analytic Hierarchy Process, Project Response Theory, and CIPP model to construct an indicator system suitable for tourism management classroom teaching. Then, based on the collected data of 5763 students, the reliability and effectiveness of the tool and indicator system were first verified. Then, the variable of teacher teaching style was introduced to construct an OLS regression model for empirical research. …The research will summarize teacher and student data collected through the platform and conduct reliability analysis in SPSS 22.0 software, using Cronbach α The credibility of coefficient testing and evaluation tools. Cronbach in Environmental Fundamentals α The cβoefficient value is 0.8350. Cronbach for resource allocation α The coefficient is 0.735, and the Cronbah of the implementation process α Cronb Bach with a coefficient of 0.7 47 for teaching performance α The coefficient is 0.7240, indicating that rat ings has high reliability. Research has found that among the four specific types, the holistic type has the greatest impact on the specific situation, the holistic type has the greatest impact on the environmental foundation and resource allocation, and the legislative type has the greatest impact on the implementation process and teaching performance. Show more
Keywords: Tourism management, AHP method, CIPP model, teaching style
DOI: 10.3233/JIFS-235844
Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-14, 2024
Authors: Vaikunta Pai, T. | Singh, Manmohan | Shaik, Nazeer | Ashokkumar, C. | Anuradha, D. | Gangopadhyay, Amit | Rao, Goda Srinivasa | Reddy, T.Sunilkumar | Nagaraju, D.
Article Type: Research Article
Abstract: As the demand for energy in India continues to surge, accurate forecasting becomes paramount for efficient resource allocation and sustainable development. This study proposes an innovative approach to forecasting Indian primary energy demand by integrating Artificial Intelligence (AI) techniques with Fuzzy Auto-regressive Distributed Lag (FADL) models. FADL models, incorporating fuzzy logic, allow for a nuanced representation of uncertainties and complexities within the energy demand dynamics. In this research, historical energy consumption data is analysed using FADL models with both symmetric and non-symmetric triangular coefficients, enhancing the model’s adaptability to the inherent uncertainties associated with energy forecasting. This study addresses the …urgent need for enhanced energy planning models in the context of sustainable development. Our research aims to provide a comprehensive framework for predicting future Total Final Consumption (TFC) in alignment with the Indian National Energy Plan’s net-zero emissions target by 2035. Recognizing the limitations of current models, our research introduces a novel approach that integrates advanced algorithms and methodologies, offering a more flexible and realistic assessment of TFC trends. The primary objective of this study is to develop an improved energy planning model that surpasses existing projections by incorporating sophisticated algorithms. We aim to refine Show more
Keywords: Auto-regressive, distributed lag, energy consumption, forecast, triangular coefficient
DOI: 10.3233/JIFS-240729
Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-12, 2024
Authors: Ma, Chengfei | Yang, Xiaolei | Lu, Heng | He, Siyuan | Liu, Yongshan
Article Type: Research Article
Abstract: When calculating participants’ contribution to federated learning, addressing issues such as the inability to collect complete test data and the impact of malicious and dishonest participants on the global model is necessary. This article proposes a federated aggregation method based on cosine similarity approximation Shapley value method contribution degree. Firstly, a participant contribution calculation model combining cosine similarity and the approximate Shapley value method was designed to obtain the contribution values of the participants. Then, based on the calculation model of participant contribution, a federated aggregation algorithm is proposed, and the aggregation weights of each participant in the federated aggregation …process are calculated by their contribution values. Finally, the gradient parameters of the global model were determined and propagated to all participants to update the local model. Experiments were conducted under different privacy protection parameters, data noise parameters, and the proportion of malicious participants. The results showed that the accuracy of the algorithm model can be maintained at 90% and 65% on the MNIST and CIFAR-10 datasets, respectively. This method can reasonably and accurately calculate the contribution of participants without a complete test dataset, reducing computational costs to a certain extent and can resist the influence of the aforementioned participants. Show more
Keywords: Federated aggregation algorithm, contribution assessment, cosine similarity, Shapley value, equitable distribution
DOI: 10.3233/JIFS-236977
Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-17, 2024
Authors: Pandey, Sakshi Dev | Ranadive, A.S. | Samanta, Sovan | Dubey, Vivek Kumar
Article Type: Research Article
Abstract: Several methodologies have been proposed in the literature of graph theory for depicting collaboration among entities. However, in these studies, the measure of collaboration is taken based on the crisp graphical properties and discusses only its positive effects. In this manuscript, we discuss the simultaneous collaboration and competition that are observed among individuals, organizations, countries, communities and many others. The notion of bipolar fuzzy bunch graph (BFBG) is introduced in this study to effectively capture the positive and negative effects of both the terms collaboration and competition, which is jointly called coopetition. The goal of this paper is to introduce …an improved representation and analytical measure for coopetition. To further enrich the literature on competition graphs, the notion of survival and winning competition among species has been introduced and also provides its bipolar fuzzy competition degrees. We also introduce two types of coopetition measures to understand the ranking structure of entities (i.e. which node batter collaborates and competes with other nodes) in the network: a) bipolar fuzzy coopetition degree and b) bipolar fuzzy coopatition index. In the form of a bipolar fuzzy coopetition graph, we find evidence to validate our framework and computations. We gathered research articles on COVID-19 and their citations over a specific time period from a specific journal. To demonstrate our approach, we displayed bipolar fuzzy collaboration and competition of various countries on COVID-19 and classified their rankings based on their positive and negative coopetition indices. Show more
Keywords: Bipolar fuzzy bunch degree, communication potential effect (CPE), bipolar fuzzy mixed graph, winning and survival competition, coopetition degree, coopetition index
DOI: 10.3233/JIFS-234061
Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-20, 2024
Authors: Ding, Xiaomei | Ding, Huaibao | Zhou, Fei
Article Type: Research Article
Abstract: Given that cloud computing is a relatively new field of study, there is an urgent need for comprehensive approaches to resource provisioning and the allocation of Internet of Things (IoT) services across cloud infrastructure. Other challenging aspects of cloud computing include IoT resource virtualization and disseminating IoT services among available cloud resources. To meet deadlines, optimize application execution times, efficiently use cloud resources, and identify the optimal service location, service placement plays a crucial role in installing services on existing virtual resources within a cloud-based environment. To achieve load balance in the fog computing infrastructure and ensure optimal resource allocation, …this work proposes a meta-heuristic approach based on the cat swarm optimization method. For more clarity in the difference between the work presented in this research and other similar works, we named the proposed technique MH-CSO. The algorithm incorporates a resource check parameter to determine the accessibility and suitability of resources in different situations. This conclusion was drawn after evaluating the proposed solution in the ifogsim environment and comparing it with particle swarm and ant colony optimization techniques. The findings demonstrate that the proposed solution successfully optimizes key parameters, including runtime and energy usage. Show more
Keywords: Load balancing, cat swarm optimization, fog computing, resource allocation and IoT
DOI: 10.3233/JIFS-233418
Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-16, 2024
Authors: Zhou, Ruohan | Chen, Wei | Xie, Congjin
Article Type: Research Article
Abstract: The field of business management involves a large amount of data and information sources, including market data, customer data, supply chain data, etc. In order to quantify and analyze different resources, help enterprises better plan and allocate resources, and improve resource utilization efficiency, a clustering analysis based digital resource integration algorithm for business management is studied. Build a business management digital resource integration framework, including data layer, integration layer, and storage layer, to integrate and store data from different sources of business management databases, thereby facilitating unified management and utilization of digital resources by enterprises. The data layer collects data …from different business management databases and stores it in the database according to different sources; The integration layer preprocesses the collected data, simply fixes errors and missing information in the data, and improves data quality. Adopting a feature extraction method based on the projection direction uncorrelation strategy of the labeled power set conversion method, the useful feature information of digital resources in enterprise management can be effectively extracted; Based on the two-step clustering analysis method, business management digital resources are clustered according to similar characteristics to complete the classification and integration of business management digital resources, and improve the efficiency of resource utilization; The storage layer adopts the Security Information Diffusion Algorithm (IDA) storage model to store integrated and classified digital resources managed by enterprises, ensuring data security and effectively preventing data leakage and illegal access. The experimental results show that the digital resource structure of business management integrated by this algorithm is clear, with a data redundancy of less than 8% and a difference of less than 11% . The time consumption for data integration is less than 2.11 minutes, indicating good resource integration ability. Show more
Keywords: Cluster analysis, business administration, digitization, resource integration, data storage, resource sharing
DOI: 10.3233/JIFS-235573
Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-13, 2024
Authors: Rachamadugu, Sandeep Kumar | Pushphavathi, T.P.
Article Type: Research Article
Abstract: This paper introduces an innovative approach, the LS-SLM (Local Search with Smart Local Moving) technique, for enhancing the efficiency of article recommendation systems based on community detection and topic modeling. The methodology undergoes rigorous evaluation using a comprehensive dataset extracted from the “dblp. v12.json” citation network. Experimental results presented herein provide a clear depiction of the superior performance of the LS-SLM technique when compared to established algorithms, namely the Louvain Algorithm (LA), Stochastic Block Model (SBM), Fast Greedy Algorithm (FGA), and Smart Local Moving (SLM). The evaluation metrics include accuracy, precision, specificity, recall, F-Score, modularity, Normalized Mutual Information (NMI), betweenness …centrality (BTC), and community detection time. Notably, the LS-SLM technique outperforms existing solutions across all metrics. For instance, the proposed methodology achieves an accuracy of 96.32%, surpassing LA by 16% and demonstrating a 10.6% improvement over SBM. Precision, a critical measure of relevance, stands at 96.32%, showcasing a significant advancement over GCR-GAN (61.7%) and CR-HBNE (45.9%). Additionally, sensitivity analysis reveals that the LS-SLM technique achieves the highest sensitivity value of 96.5487%, outperforming LA by 14.2%. The LS-SLM also demonstrates superior specificity and recall, with values of 96.5478% and 96.5487%, respectively. The modularity performance is exceptional, with LS-SLM obtaining 95.6119%, significantly outpacing SLM, FGA, SBM, and LA. Furthermore, the LS-SLM technique excels in community detection time, completing the process in 38,652 ms, showcasing efficiency gains over existing techniques. The BTC analysis indicates that LS-SLM achieves a value of 94.6650%, demonstrating its proficiency in controlling information flow within the network. Show more
Keywords: Recommender Systems (RS), BagofWords (BoW), Pearson Correlation Co-efficient based Latent Dirichlet Allocation (PCC-LDA), Linear Scaling based Smart Local Moving (LS-SLM), Time Frequency and Inverse Document Frequency (TF-IDF), Community detection
DOI: 10.3233/JIFS-233851
Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-17, 2024
Authors: Zhang, Yonghong | Li, Shouwei | Li, Jingwei | Tang, Xiaoyu
Article Type: Research Article
Abstract: Electricity market violations affect the overall operations of the electricity market. This paper explores the evolutionary stability strategies of electricity generation enterprises and electricity consumers under two modes: traditional regulation and blockchain regulation to analyze blockchain technology’s mechanism and conditions in solving electricity market violations. The experimental results indicate that the likelihood of consumers accepting electricity and the regulatory capacity of regulatory agencies play a crucial role in determining the violation approach adopted by electricity generation enterprises. Under traditional regulatory models, due to information asymmetry, regulatory agencies may not be able to detect violations promptly. Meanwhile, electricity consumers may choose …to accept violations by power generation companies due to high appeal costs. Blockchain technology enables regulatory agencies to improve their regulatory capabilities by eliminating information asymmetry, reducing the cost of complaints from electricity consumers, thereby elevating the risk for enterprises engaging in market violations and optimizing the evolutionary game towards an optimum state. Show more
Keywords: Blockchain technology, electricity market, violation regulation, evolutionary game
DOI: 10.3233/JIFS-238041
Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-15, 2024
Authors: Zhang, Juwei | Wang, Jing | Liu, Mingjun | Li, Zhihui
Article Type: Research Article
Abstract: Assessing the effectiveness of physical education instruction, students’ learning, and the feedback received from the teaching process are all vital components of the physical education teaching process in colleges and universities. Improving the quality of physical education instruction in these settings is essential. With its ability to drive the digital revolution of physical education in schools, intelligent technology is bringing about significant changes in the field of education and drawing attention from people from all walks of life. To assess intelligent technology’s impact on physical education instruction in a scientific manner, this study utilizes the latest intelligent analysis and sensing …data mining to design an intelligent physical education measurement and evaluation model, which utilizes GPS positioning, built-in maps, and gravity sensing to provide real-time feedback on the trajectory, distance, and time of the movement, and then calculates the real-time and average speed of the movement, as different students’ body postures to achieve the the same effect when the required speed is not the same, this paper randomly selected students with different BMI index for empirical analysis. The experimental results show that the principal components of the factor analysis extracted four common factors with a cumulative contribution rate of 69.5%, and the test-retest reliability of the four dimensions is 0.665–0.862. Show more
Keywords: Intelligent analysis, sensor data mining, physical education, physical measurement and evaluation
DOI: 10.3233/JIFS-235410
Citation: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-16, 2024
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