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Int. J. Fuzzy Syst. Appl.最新文献

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Fuzzy Multi-Objective Portfolio Optimization Considering Investment Return and Investment Risk 考虑投资收益和投资风险的模糊多目标投资组合优化
Int. J. Fuzzy Syst. Appl. Pub Date : 2022-01-01 DOI: 10.4018/ijfsa.285552
Shayarath Srizongkhram, Pisacha Suthamanondh, Kittitath Manitayakul, K. Shirahada, N. Chiadamrong
{"title":"Fuzzy Multi-Objective Portfolio Optimization Considering Investment Return and Investment Risk","authors":"Shayarath Srizongkhram, Pisacha Suthamanondh, Kittitath Manitayakul, K. Shirahada, N. Chiadamrong","doi":"10.4018/ijfsa.285552","DOIUrl":"https://doi.org/10.4018/ijfsa.285552","url":null,"abstract":"Portfolio selection and optimization deal with the selection of the most suitable projects in a portfolio. The expected goals can be achieved while considering the balance among selected projects, to ensure that all selected projects consume resources effectively. This study proposes and compares multi-objective portfolio investment optimization algorithms under uncertain conditions. The investment return (in terms of the fuzzy net present value of the portfolio) and investment risk (in terms of the credibilistic risk index) have simultaneously been considered. In addition, fuzzy chance-constrained programming is introduced as an optimization constraint to handle such uncertainty by specifying a desired confidence level of the decision makers. The outcome of this study can then help decision makers to decide what projects and when to invest. Decision makers can deal with a limited budget with logical relationships, and within their desired financial and risk requirements.","PeriodicalId":233724,"journal":{"name":"Int. J. Fuzzy Syst. Appl.","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129285637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
The Compromise Ratio Method With Intuitionistic Fuzzy Distance for FMAGDM 基于直觉模糊距离的FMAGDM折衷比方法
Int. J. Fuzzy Syst. Appl. Pub Date : 2022-01-01 DOI: 10.4018/ijfsa.2022010108
Shuai Li, Jingjing An, Jiangxia Nan
{"title":"The Compromise Ratio Method With Intuitionistic Fuzzy Distance for FMAGDM","authors":"Shuai Li, Jingjing An, Jiangxia Nan","doi":"10.4018/ijfsa.2022010108","DOIUrl":"https://doi.org/10.4018/ijfsa.2022010108","url":null,"abstract":"The compromise ratio method (CRM) is an effective method to solve multiple attribute group decision making (MAGDM). Distance measure of intuitionistic fuzzy (IF) numbers (IFNs) is important for CRM. In this paper, according to the IF distance of IFNs, an extended compromise ratio method (CRM) is developed for (MAGDM) problems which attribute weights and evaluation values of alternatives on attributes are expressed in linguistic variables parameterized using TIFNs. Finally, the effectiveness and practicability of the extended CRM with IF distance are demonstrated by solving a software selection problem.","PeriodicalId":233724,"journal":{"name":"Int. J. Fuzzy Syst. Appl.","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114664332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
A Theoretical Linguistic Fuzzy Rule-Based Compartmental Modeling for the COVID-19 Pandemic 基于语言模糊规则的新型冠状病毒大流行理论分区模型
Int. J. Fuzzy Syst. Appl. Pub Date : 2022-01-01 DOI: 10.4018/ijfsa.2022010103
Zakaria Shams Siam, R. Hasan, Hossain Ahamed, Samiya Kabir Youme, Soumik Sarker Anik, Sumaia Islam Alita, R. Rahman
{"title":"A Theoretical Linguistic Fuzzy Rule-Based Compartmental Modeling for the COVID-19 Pandemic","authors":"Zakaria Shams Siam, R. Hasan, Hossain Ahamed, Samiya Kabir Youme, Soumik Sarker Anik, Sumaia Islam Alita, R. Rahman","doi":"10.4018/ijfsa.2022010103","DOIUrl":"https://doi.org/10.4018/ijfsa.2022010103","url":null,"abstract":"Recently COVID-19 pandemic has affected the whole world quite seriously. The number of new infectious cases and death cases are rapidly increasing over time. In this study, a theoretical linguistic fuzzy rule-based Susceptible-Exposed-Infectious-Isolated-Recovered (SEIIsR) compartmental model has been proposed to predict the dynamics of the transmission of COVID-19 over time considering population immunity and infectiousness heterogeneity based on viral load in the model. The model’s equilibrium points have been calculated and stability analysis of the model’s equilibrium points has been conducted. Consequently, the fuzzy basic reproduction number, R0f of the fuzzy model has been formulated. Finally, the temporal dynamics of different compartmental populations with immunity and infectiousness heterogeneity using the fuzzy Mamdani model are delineated and some disease control policies have been suggested to get over the infection in no time.","PeriodicalId":233724,"journal":{"name":"Int. J. Fuzzy Syst. Appl.","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121323744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Generalized Fuzzy Divergence Measure, Pattern Recognition, and Inequalities 广义模糊散度测度、模式识别和不等式
Int. J. Fuzzy Syst. Appl. Pub Date : 2022-01-01 DOI: 10.4018/ijfsa.285983
R. Saraswat, Neha Khatod
{"title":"Generalized Fuzzy Divergence Measure, Pattern Recognition, and Inequalities","authors":"R. Saraswat, Neha Khatod","doi":"10.4018/ijfsa.285983","DOIUrl":"https://doi.org/10.4018/ijfsa.285983","url":null,"abstract":"Many fuzzy information and divergence measures developed by various researchers and authors. Here, authors proposed new fuzzy divergence measure using the properties of convex function and fuzzy concept. The applications of novel fuzzy divergence measures in pattern recognition with case study, are discussed. Obtained various novel fuzzy information inequalities on fuzzy divergence measures. The new relations among new and existing fuzzy divergence measure by new f-divergence, Jensen inequalities, properties of convex functions and inequalities have studied. Finally, verified these results and proposed fuzzy divergence measures by numerical example.","PeriodicalId":233724,"journal":{"name":"Int. J. Fuzzy Syst. Appl.","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114448726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
A Novel Intuitionistic Fuzzy Correlation Algorithm and Its Applications in Pattern Recognition and Student Admission Process 一种新的直觉模糊关联算法及其在模式识别和学生录取过程中的应用
Int. J. Fuzzy Syst. Appl. Pub Date : 2022-01-01 DOI: 10.4018/ijfsa.285984
P. A. Ejegwa, I. C. Onyeke
{"title":"A Novel Intuitionistic Fuzzy Correlation Algorithm and Its Applications in Pattern Recognition and Student Admission Process","authors":"P. A. Ejegwa, I. C. Onyeke","doi":"10.4018/ijfsa.285984","DOIUrl":"https://doi.org/10.4018/ijfsa.285984","url":null,"abstract":"Many computing methods have been studied in intuitionistic fuzzy environment to enhance the resourcefulness of intuitionistic fuzzy sets in modelling real-life problems, among which, correlation coefficient is prominent. This paper proposes a new intuitionistic fuzzy correlation algorithm via intuitionistic fuzzy deviation, variance and covariance by taking into account the complete parameters of intuitionistic fuzzy sets. This new computing technique does not only evaluates the strength of relationship between the intuitionistic fuzzy sets but also indicates whether the intuitionistic fuzzy sets have either positive or negative linear relationship. The proposed technique is substantiated with some theoretical results, and numerically validated to be superior in terms of performance index in contrast to some hitherto methods. Multi-criteria decision-making processes involving pattern recognition and students’ admission process are determined with the aid of the proposed intuitionistic fuzzy correlation algorithm coded with JAVA programming language.","PeriodicalId":233724,"journal":{"name":"Int. J. Fuzzy Syst. Appl.","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129663419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
An Adaptive Fuzzy-Based Two-Layered HRRN CPU Scheduler: FHRRN 基于自适应模糊的双层HRRN CPU调度器:FHRRN
Int. J. Fuzzy Syst. Appl. Pub Date : 2022-01-01 DOI: 10.4018/ijfsa.285557
Supriya Raheja
{"title":"An Adaptive Fuzzy-Based Two-Layered HRRN CPU Scheduler: FHRRN","authors":"Supriya Raheja","doi":"10.4018/ijfsa.285557","DOIUrl":"https://doi.org/10.4018/ijfsa.285557","url":null,"abstract":"Fuzzy Based CPU scheduler becomes an emerging component of an operating system. It can handle the imprecise nature of parameters used in scheduler. This paper introduces an adaptive fuzzy based Highest Response Ratio Next CPU scheduler which is an extension of conventional CPU scheduler. Proposed scheduler works in 2 layers. At the first layer, a Fuzzy Inference System is defined which handles the uncertainties of parameters and at the second layer, an adaptive scheduling algorithm is used to schedule each task. Proposed scheduler intelligently generates the response ratio for each ready to run task which makes the system adaptive at run time. The work is compared with the conventional highest response ratio next scheduling and the existing fuzzy highest ratio next scheduling algorithms. Results validate the better performance of proposed scheduler. The proposed scheduler also provides comparable results with respect to shortest job first scheduling and shortest remaining task first scheduling algorithms.","PeriodicalId":233724,"journal":{"name":"Int. J. Fuzzy Syst. Appl.","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125207819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A New Approach Towards Intuitionistic Fuzzy Multisets 直觉模糊多集的一种新方法
Int. J. Fuzzy Syst. Appl. Pub Date : 2022-01-01 DOI: 10.4018/ijfsa.2022010105
P. Majumdar
{"title":"A New Approach Towards Intuitionistic Fuzzy Multisets","authors":"P. Majumdar","doi":"10.4018/ijfsa.2022010105","DOIUrl":"https://doi.org/10.4018/ijfsa.2022010105","url":null,"abstract":"In this paper a new definition of Intuitionistic fuzzy multisets (IFMS) has been introduced. Algebraic operations on these intuitionistic fuzzy multisets are defined and their properties under these algebraic operations are studied. The author has also introduced a new notion of complement for an IFMS in which the complement of the original set is also an IFMS. The notion of distance and similarity between two IFMS’s has been defined and their properties have also been studied here. An application of IFMS in solving a medical diagnosis problem has been provided at the end.","PeriodicalId":233724,"journal":{"name":"Int. J. Fuzzy Syst. Appl.","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121674722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
The Intuitionistic Fuzzy FlowSort Method for Multicriteria Group Decision Making 多准则群体决策的直觉模糊流排序方法
Int. J. Fuzzy Syst. Appl. Pub Date : 2022-01-01 DOI: 10.4018/ijfsa.2022010104
Fedia Daami Remadi, H. Frikha
{"title":"The Intuitionistic Fuzzy FlowSort Method for Multicriteria Group Decision Making","authors":"Fedia Daami Remadi, H. Frikha","doi":"10.4018/ijfsa.2022010104","DOIUrl":"https://doi.org/10.4018/ijfsa.2022010104","url":null,"abstract":"The real life problems are multidimensional in nature and may involve some ambiguity when it comes to decision making. It is, therefore, difficult to design the evaluation criteria precisely and determine the exact value of the attributes in the multicriteria analysis. The intuitionistic fuzzy set (IFS) achieved great success in treating this kind of ambiguity in a great deal of research. The study of sorting problems is an active research issue in the multiple criteria decision aid (MCDA) area. This paper investigated one of the sorting methods, FLOWSORT, and extended it to the multicriteria group decision making based on the output aggregation of the individual sorting results. The rating of each alternative was described through linguistic terms that can be expressed in triangular intuitionistic fuzzy numbers. An illustrative example as well as an empirical comparison with other multi-criteria decision making methods were carried out to validate our extension.","PeriodicalId":233724,"journal":{"name":"Int. J. Fuzzy Syst. Appl.","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115419668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
Bipolar Complex Fuzzy Soft Sets and Their Application 双极复模糊软集及其应用
Int. J. Fuzzy Syst. Appl. Pub Date : 2022-01-01 DOI: 10.4018/ijfsa.285551
Sahar Alqaraleh, A. Alkouri, M. Massa'deh, Adeeb G. Talafha, A. Bataihah
{"title":"Bipolar Complex Fuzzy Soft Sets and Their Application","authors":"Sahar Alqaraleh, A. Alkouri, M. Massa'deh, Adeeb G. Talafha, A. Bataihah","doi":"10.4018/ijfsa.285551","DOIUrl":"https://doi.org/10.4018/ijfsa.285551","url":null,"abstract":"We introduce a new computational model to solve efficient problems. This research generalizes the concept of bipolar fuzzy soft sets (BFSS) to the realm of complex numbers. However, the ranges of positive and negative values membership BFSS functions are extended to unit disk instead of [0, 1] and [-1, 0] respectively. The main benefit of bipolar complex fuzzy soft sets BCFSSs appears in the ability to transfer bipolar fuzzy soft information to a mathematical formula without losing the full meaning of information that may appear from different phases. Some basic operations and theorems on BCFSS are defined with numerical examples. This research has extended to illustrate the utilization of BCFSS in decision making problems by generalizing the applications and algorithms.","PeriodicalId":233724,"journal":{"name":"Int. J. Fuzzy Syst. Appl.","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130592993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
A New Methodology to Arrive at Membership Weights for Fuzzy SVM 一种确定模糊支持向量机隶属度权重的新方法
Int. J. Fuzzy Syst. Appl. Pub Date : 2022-01-01 DOI: 10.4018/ijfsa.2022010106
A. Maruthamuthu, P. Murugesan, N. MuthulakshmiA.
{"title":"A New Methodology to Arrive at Membership Weights for Fuzzy SVM","authors":"A. Maruthamuthu, P. Murugesan, N. MuthulakshmiA.","doi":"10.4018/ijfsa.2022010106","DOIUrl":"https://doi.org/10.4018/ijfsa.2022010106","url":null,"abstract":"Support Vector Machine (SVM) is a supervised classification technique that uses the regularization parameter and Kernel function in deciding the best hyperplane to classify the data. SVM is sensitive to outliers, and it makes the model weak. To overcome the issue, the Fuzzy Support Vector Machine (FSVM) introduces fuzzy membership weight into its objective function, which focuses on grouping the fuzzy data points accurately. Knowing the importance of the membership weights in FSVM, we have introduced four new expressions to compute the FSVM membership weights in this study. They are determined from the Fuzzy C-means Algorithm's membership values (FCM). The performances of FSVM with three different kernels are assessed in terms of accuracy. The experiments are conducted for various combinations of FSVM parameters, and the best combinations for each kernel are highlighted. Six benchmark datasets are used to demonstrate the performance of FSVM and the proposed models’ performance are compared with the existing models in recent literature.","PeriodicalId":233724,"journal":{"name":"Int. J. Fuzzy Syst. Appl.","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129159741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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