International Journal of Fuzzy Systems最新文献

{"title":"Emergency Decision Support System in Cardiovascular Health Using T-spherical q-Rung Linear Diophantine Fuzzy Set and Logistic Differential Evolution","authors":"G Punnam Chander, Sujit Das","doi":"10.1007/s40815-024-01836-7","DOIUrl":"https://doi.org/10.1007/s40815-024-01836-7","url":null,"abstract":"<p>In the field of cardiovascular health, the need to make quick decisions in emergency situations is mandatory to save one’s life. During cardiovascular abnormalities, often the patients become unresponsive as the physical and mental conditions become unstable. A meticulous approach that considers various aspects of emergency circumstances is crucial to address these challenges effectively. This paper proposes an effective emergency decision-making method for cardiovascular health using a new T-spherical q-rung linear diophantine fuzzy set (TSqLDFS), logistic differential evolution optimization, and evidential reasoning methodologies. TSqLDFS is employed with a broader scope of bounds for the experts to assess the evaluation values for alternatives corresponding to specified attributes without any restriction. The optimal weights of each attribute are obtained using logistic differential evolution optimization. Then, the aggregated T-spherical q-rung linear diophantine fuzzy values (TSqLDFVs) of each alternative are calculated using evidential reasoning. Subsequently, the score values are evaluated, facilitating the selection of the optimal choice with the highest score. The outcomes of the proposed approach in the context of cardiovascular health have been compared with the existing methods, ensuring its robustness and better performance in medical scenarios.</p>","PeriodicalId":14056,"journal":{"name":"International Journal of Fuzzy Systems","volume":"47 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142175351","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Probabilistic Hesitant Fuzzy Multi-criteria Group Decision-Making Method Integrated DIBR and Tri-reference Point Theory","authors":"Feng Zhu, Yumin Liu, Jingjing Sun, Jichao Xu, Ning Wang","doi":"10.1007/s40815-024-01728-w","DOIUrl":"https://doi.org/10.1007/s40815-024-01728-w","url":null,"abstract":"<p>As an effective tool to show the fuzziness of qualitative information, the probabilistic hesitant fuzzy set (PHFS) can utilize a group of membership degrees with a clear probability distribution to show the opinions of decision-maker (DM). Given this merit, many probabilistic hesitant fuzzy multi-criteria group decision-making (PHF-MCGDM) methods have been designed. However, most of the existing PHF-MCGDM methods have some limitations, including the difficulty of reflecting DMs’ ambiguous and hesitant preferences for criteria weights and the inability to comprehensively show the impacts of DMs’ irrational behaviors. To address these limitations, this paper develops a novel PHF-MCGDM method that integrates the defining interrelationships between ranked criteria (DIBR) approach and tri-reference point (TRP) theory. First, the PHF-DIBR approach is constructed to determine criteria weights by fully expressing DMs’ ambiguous and hesitant preferences for the importance of criteria. Second, the novel probabilistic hesitant fuzzy correlation coefficient (NPHFCC) is developed for deriving the weights of DMs, which remedies the flaws of the existing correlation coefficients (CC). Moreover, TRP theory is used to describe the psychological behavior effects of DMs and derive the order of alternatives. Finally, the applicability of the proposed method is validated by the case about office flooring material selection, while the sensitivity and comparison analyses are also conducted to further prove its advantages and effectiveness.</p>","PeriodicalId":14056,"journal":{"name":"International Journal of Fuzzy Systems","volume":"105 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142175385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design of Fuzzy Delay Compensation Controller Based on Amplitude Compensation Method for Power System with Communication Delay","authors":"Jun Li, Hongliang Gao, Yong Wang","doi":"10.1007/s40815-024-01781-5","DOIUrl":"https://doi.org/10.1007/s40815-024-01781-5","url":null,"abstract":"<p>In a networked power system, communication delay in the feedback signal during transmission process can have a detrimental impact on the effectiveness of the power system stabilizer (PSS) in suppressing low-frequency oscillations. To address this problem, a controller design method to compensate for short constant time delays is proposed. The proposed approach utilizes Mamdani fuzzy inference system to design a fuzzy delay compensation damping controller (FDCDC) and establishes control rules based on the amplitude compensation method. The proposed FDCDC takes the delayed feedback signal as input and generates additional excitation control signal as output. The controller considers the effect of delay on the performance of PSS controller and compensates for the delay through fuzzy output. To evaluate the effectiveness of the proposed FDCDC, a networked power system model is developed using MATLAB Simulink’s SimPowerSystems library and TrueTime 2.0 toolbox. The aim of this study is to investigate the impact of short constant time delay on the performance of PSS controller in a networked environment and to assess the performance of the proposed controller. The simulation results demonstrate that the proposed FDCDC exhibits good adaptability and robustness in compensating for the effect of delay on PSS control.</p>","PeriodicalId":14056,"journal":{"name":"International Journal of Fuzzy Systems","volume":"37 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142175357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Fast Finite-Time Output Feedback Control of Uncertain Nonlinear Systems","authors":"Maoxian Zhao, Zheng Li, Fang Wang","doi":"10.1007/s40815-024-01678-3","DOIUrl":"https://doi.org/10.1007/s40815-024-01678-3","url":null,"abstract":"<p>This work reflects on a fast finite-time control issue of nonlinear systems. Both the unmeasurable states of system and unknown nonlinearities are consideblack in this article. A state observer is constructed to eliminate the constraint that the states of system need to be measublack. By utilizing the fuzzy logic systems (FLSs), the unknown nonlinearities are coped with. The singularity issue from the virtual controllers design is skillfully tackled by constructing the smooth piecewise function. The practical fast finite-time stability criterion (fast FTS criterion) is firstly established. Then, a fast finite time output feedback controller is established. By means of the proposed stability criterion, the fast finite time stability of the closed-loop system is guaranteed. Eventually, two examples demonstrate the efficacy of the proposed control strategy.</p>","PeriodicalId":14056,"journal":{"name":"International Journal of Fuzzy Systems","volume":"108 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142175350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Identification Method for Rotor Axis Orbits based on Enhanced Hierarchical Multivariate Fuzzy Entropy and Extreme Learning Machine","authors":"Chen Fei, Lan Pengfei, Liu Ting, Zhang Tingting, Wang Kun, Liu Dong, Fan Mao, Wang Bin, Wu Fengjiao","doi":"10.1007/s40815-024-01801-4","DOIUrl":"https://doi.org/10.1007/s40815-024-01801-4","url":null,"abstract":"<p>The rotor system is the core equipment of industrial rotating machinery, and ensuring its safety is an essential basis for improving the productivity of the equipment. As a critical monitoring quantity reflecting the operating status of the rotor system, identification models based on axis orbits are effective means for detecting equipment faults. However, most of the existing axis orbit identification models belong to the category of image recognition, and these methods have defects such as unclear physical meaning of features and weak generalization performance. Therefore, the paper returns to the essence of axis orbits and proposes a rotor axis orbit recognition method based on multivariate swing signals, feature extraction and pattern recognition. Firstly, the mutually perpendicular swing signals of the rotor are obtained based on eddy current sensors. Secondly, we propose a feature extraction tool for extracting the multivariate signals named enhanced hierarchical multivariate fuzzy entropy (EHM_vFE), a nonlinear dynamics metric based on the enhanced hierarchical decomposition method. Next, the features of axis orbits are extracted by the EHM_vFE. Finally, some of the extracted features are input into an extreme learning machine (ELM) for model training, and the effectiveness of the method is verified with the remaining samples. We apply the proposed method to the rotor axis orbit identification case, and the results show that its recognition rate is 98.963%. In comparison experiments with recognition models based on nonlinear dynamics indicators, multivariate signal processing methods, traditional image feature extraction methods, and popular deep learning models, the proposed model shows substantial advantages, verifying the reasonableness and superiority of the proposed method. This study provides a new idea for rotor shaft fault diagnosis, which has significant reference value for promoting the development of intelligent operation and maintenance of industrial equipment.</p>","PeriodicalId":14056,"journal":{"name":"International Journal of Fuzzy Systems","volume":"11 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142175349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exponentially Weighted Moving Average Charts Based on Interval Type-2 Fuzzy Numbers: Analyses of Quality Control and Performance","authors":"Nur Hidayah Mohd Razali, Lazim Abdullah, Ahmad Termimi Ab Ghani, Zati Aqmar Zaharudin, Asyraf Afthanorhan","doi":"10.1007/s40815-024-01794-0","DOIUrl":"https://doi.org/10.1007/s40815-024-01794-0","url":null,"abstract":"<p>A control chart is one of the most important techniques used to monitor processes of variability in the manufacturing data. However, conventional charts are relatively not suitable to deal with crisp data. Fuzzy charts are inevitable to evaluate the process with fuzzy data. Nevertheless, much of the data used in daily life cannot be used as a type-1 fuzzy number due to the complexity and uncertainty of information. It is suggested that type-2 fuzzy numbers are more capable in detecting the meaning of process shifts. This paper aims to develop interval type-2 fuzzy (IT2F) Exponentially Weighted Moving Average (IT2F-EWMA) control charts as a new method where the advantages of lower membership and upper membership, which can capture sensitivity and variability in manufacturing data. In the proposed method, we also employed the Best Nonfuzzy Performance method as the defuzzification method instead of the typical centroid method. In order to confirm the performance of the proposed control chart, the average run length (ARL) is calculated and compared to the other three charts. To test the performance of the proposed EWMA, twenty samples were analysed to identify the defects in the fertilizers’ production. Based on the result of the conventional chart, 8 out of 20 samples are “uncontrolled”. In contrast, the type-1 chart found 16 samples are “uncontrolled”, whereas IT2F-EWMA found 18 samples are “out of control”. Consequently, it is proven that IT2F-EWMA is the best method to be used in dealing with vague and fuzzy data since it is more precise and vulnerable. Lastly, the ARL test shows that IT2F-EWMA charts outperform the other control charts.</p>","PeriodicalId":14056,"journal":{"name":"International Journal of Fuzzy Systems","volume":"103 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142175360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Fault Diagnosis Method for Manufacturing System Based on Adaptive BRB Considering Environmental Disturbance","authors":"Boying Zhao, Lingkai Kong, Wei He, Guohui Zhou, Hailong Zhu","doi":"10.1007/s40815-024-01799-9","DOIUrl":"https://doi.org/10.1007/s40815-024-01799-9","url":null,"abstract":"<p>Timely fault diagnosis is essential to ensure the reliable performance of manufacturing systems. Aiming at the problems of insufficient prior information and incomplete reliability of monitoring data affected by environmental disturbance during the diagnosis process in manufacturing system, an adaptive belief rule base with index uncertainty (ABRB-u) is proposed. Initially, the adaptive method is used to accurately estimate the initial parameters, facilitating the construction of belief rule base (BRB). Subsequently, considering the limitations of the current model in dealing with uncertain monitoring data, a method for transforming matching degree is introduced, which incorporates the index uncertainty into the model. Finally, the results of the case study demonstrate that this method not only achieves favorable diagnostic outcomes in the absence of prior information but also successfully addresses the challenge of incomplete reliability in monitoring data. This offers a promising solution for fault diagnosis in manufacturing systems.</p>","PeriodicalId":14056,"journal":{"name":"International Journal of Fuzzy Systems","volume":"42 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142175382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Two-Warehouse Green Inventory Cloudy Fuzzy Model for Deteriorating Items with Two-Level Trade Credit and Shortages","authors":"Subhashree Parida, Milu Acharya","doi":"10.1007/s40815-024-01780-6","DOIUrl":"https://doi.org/10.1007/s40815-024-01780-6","url":null,"abstract":"<p>In the present era, the most delicate environmental issue is global warming, and because of this, countries across the globe are trying to manage the most hazardous emissions by making certain investments in projects to promote green industrial practices. In the current study, the inventory models are developed by including the emission of CO₂ from transportation which is controlled by the optimum investments in green technology (GT). Here, sustainable deteriorating inventory models in both crisp and cloudy fuzzy (CF) environments with a two-level trade credit scheme are proposed to boost the demand, where a delay in payment opportunity is there for suppliers and retailers. In this credit scenario, delay in payment options is given from the supplier to the retailer, and also from the retailer to the customer. In the present research, two warehouses are considered to manage the stock-out situation. For the model problems, demand is considered to be time dependent, where a multiple prepayment option for the purchasing cost involving an installment is provided to the retailers. Here the solution processes for the proposed models suggest algorithms, and then a numerical approach is followed to test the optimality criteria. The said optimum results are also presented in graphs. Again, a comparative study of the obtained results concerning the models is also highlighted. Lastly, a sensitivity analysis is performed to study the influence of variations in input parameters, which allows drawing some managerial insights.</p>","PeriodicalId":14056,"journal":{"name":"International Journal of Fuzzy Systems","volume":"38 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142175359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Interval Intuitionistic Fuzzy Characterization Method Based on Heterogeneous Big Data and Its Application in Forest Land Quality Assessment","authors":"Junzhe Zhang, Jian Lin, Tao Wu","doi":"10.1007/s40815-024-01765-5","DOIUrl":"https://doi.org/10.1007/s40815-024-01765-5","url":null,"abstract":"<p>With the rapid advancement and ongoing evolution of data information technology, the methods and approaches for data collection have become increasingly varied. The synthesis of heterogeneous big data to minimize information loss during the aggregation process poses a significant challenge. In practical applications, fuzzy dimensionality reduction characterization has proven to be an effective approach for handling heterogeneous big data. In this study, a novel approach is proposed for characterizing and evaluating heterogeneous big data using an interval intuitionistic fuzzy framework. We establish the interval intuitionistic fuzzy transformation method for large-scale quantitative data by defining satisfaction intervals, dissatisfaction intervals, and hesitation intervals. To integrate calculation and processing for linguistic evaluation information with different granularities, a transformation formula that handles multi-granularity uncertain linguistic information and interval intuitionistic fuzzy numbers is introduced. The proposed formula aggregates heterogeneous attribute values into interval intuitionistic fuzzy numbers. We employ interval intuitionistic fuzzy entropy to determine the objective weight of each evaluation indicator. Subsequently, the interval intuitionistic fuzzy comprehensive evaluation information for each alternative scheme, enabling effective ranking based on the information, is derived. Finally, the applicability of our proposed method is verified through a case study conducted on forest land in the county area of Fujian province. This case study comprehensively assesses and ranks the forest land quality in 16 sample plots. The evaluation serves as a theoretical framework for advancing sustainable development and conservation initiatives about forest land within the county.</p>","PeriodicalId":14056,"journal":{"name":"International Journal of Fuzzy Systems","volume":"9 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142175383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Novel Interval Type-2 Fuzzy CPT-TODIM Method for Multi-criteria Group Decision Making and Its Application to Credit Risk Assessment in Supply Chain Finance","authors":"Wen Li, Luqi Wang, Obaid Ur Rehman","doi":"10.1007/s40815-024-01759-3","DOIUrl":"https://doi.org/10.1007/s40815-024-01759-3","url":null,"abstract":"<p>The assessment of credit risk in supply chain finance (SCF) stands as a pivotal procedure in facilitating enterprises to identify appropriate financing solutions, reduce financing costs, enhance capital utilization efficiency, and mitigate the risk of debt default. Multi-criteria group decision-making (MCGDM), a systematic evaluation tool, is widely used for the assessment of both qualitative and quantitative criteria. However, the conventional framework of MCGDM exhibits limitations in addressing scenarios characterized by high uncertainty in risk information, disparity in weights among decision-makers (DMs) and criteria, alongside complex and non-linear risk perception. To address these limitations, this paper introduces an analytical model that integrates Interval Type-2 Fuzzy Sets (IT2FSs), Cumulative Prospect Theory (CPT), and the TODIM (an acronym from Portuguese for Interactive and Multicriteria Decision Making) method to evaluate credit risk in SCF. Firstly, the IT2FSs are utilized to represent high uncertainty in risk assessment information of DMs. Secondly, the Dice Similarity is applied to determine the weights of DMs. Then, we seek to improve the Criterion Importance Through Intercriteria Correlation (CRITIC) method by addressing its limitations and further integrating it with the Bayesian Best–Worst Method (BBWM), offering a robust computational framework of integrated weights for criteria. Finally, the CPT-TODIM method based on IT2FSs is applied in a real case from Ping An Bank. Through rigorous sensitivity and comparative analyses conducted within the real-world context of SCF credit risk assessments, the proposed model’s theoretical robustness and practical applicability are emphatically validated.</p>","PeriodicalId":14056,"journal":{"name":"International Journal of Fuzzy Systems","volume":"6 1","pages":""},"PeriodicalIF":4.3,"publicationDate":"2024-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142175395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}