Pub Date : 1900-01-01DOI: 10.5899/2014/JFSVA-00191
S. Moghari, M. M. Zahedi
Until now, some methods for minimizing deterministic fuzzy finite tree automata (DFFTA) and weighted tree automata have been established by researchers. Those methods are language preserving, but the behavior of original automata and minimized one may be different. This paper, considers both language preserving and behavior preserving in minimization process. We drive Myhill-Nerode kind theorems corresponding to each proposed method and introduce PTIME algorithms for behaviorally and linguistically minimization. The proposed minimization algorithms are based on two main steps. The first step includes finding dependency between equivalency of states, according to the set of transition rules of DFFTA, and making merging dependency graph (MDG). The second step is refinement of MDG and making minimization equivalency set (MES). Additionally, behavior preserving minimization of DFFTA requires a pre-processing for modifying fuzzy membership grade of rules and final states, which is called normalization.
{"title":"Minimization of Deterministic Fuzzy Tree Automata","authors":"S. Moghari, M. M. Zahedi","doi":"10.5899/2014/JFSVA-00191","DOIUrl":"https://doi.org/10.5899/2014/JFSVA-00191","url":null,"abstract":"Until now, some methods for minimizing deterministic fuzzy finite tree automata (DFFTA) and weighted tree automata have been established by researchers. Those methods are language preserving, but the behavior of original automata and minimized one may be different. This paper, considers both language preserving and behavior preserving in minimization process. We drive Myhill-Nerode kind theorems corresponding to each proposed method and introduce PTIME algorithms for behaviorally and linguistically minimization. The proposed minimization algorithms are based on two main steps. The first step includes finding dependency between equivalency of states, according to the set of transition rules of DFFTA, and making merging dependency graph (MDG). The second step is refinement of MDG and making minimization equivalency set (MES). Additionally, behavior preserving minimization of DFFTA requires a pre-processing for modifying fuzzy membership grade of rules and final states, which is called normalization.","PeriodicalId":308518,"journal":{"name":"Journal of Fuzzy Set Valued Analysis","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134584424","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}
Pub Date : 1900-01-01DOI: 10.5899/2015/JFSVA-00226
J. P. M. Kanyinda, R. M. Matendo, B. U. E. Lukata
This article shows that the {it L-R method} introduced in this work is one of valid methods for computing performance measures of fuzzy queues. Using this calculation technique, we find the number of customers and the waiting time of a simple queue M/M/1 in fuzzy environment. L-R method has the advantage of being short, convenient and flexible compared to the well-known and called alpha-cuts method.
{"title":"Computing Fuzzy Queueing Performance Measures by L-R Method","authors":"J. P. M. Kanyinda, R. M. Matendo, B. U. E. Lukata","doi":"10.5899/2015/JFSVA-00226","DOIUrl":"https://doi.org/10.5899/2015/JFSVA-00226","url":null,"abstract":"This article shows that the {it L-R method} introduced in this work is one of valid methods for computing performance measures of fuzzy queues. Using this calculation technique, we find the number of customers and the waiting time of a simple queue M/M/1 in fuzzy environment. L-R method has the advantage of being short, convenient and flexible compared to the well-known and called alpha-cuts method.","PeriodicalId":308518,"journal":{"name":"Journal of Fuzzy Set Valued Analysis","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114558351","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}
Pub Date : 1900-01-01DOI: 10.5899/2017/jfsva-00379
M. Dirbaz, F. Dirbaz
In this paper, the formulate of second order of fuzzy Taylor's method based on gH difference is calculated. On the following we used the second order of fuzzy Taylor's method for solving the fuzzy initial value problem. Finally we present the error table of numerical example.
{"title":"A Numerical Solution of Fuzzy Initial Value Problem Based on Fuzzy Method","authors":"M. Dirbaz, F. Dirbaz","doi":"10.5899/2017/jfsva-00379","DOIUrl":"https://doi.org/10.5899/2017/jfsva-00379","url":null,"abstract":"In this paper, the formulate of second order of fuzzy Taylor's method based on gH difference is calculated. On the following we used the second order of fuzzy Taylor's method for solving the fuzzy initial value problem. Finally we present the error table of numerical example.","PeriodicalId":308518,"journal":{"name":"Journal of Fuzzy Set Valued Analysis","volume":"07 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129630500","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}
Pub Date : 1900-01-01DOI: 10.5899/2014/JFSVA-00141
A. Yousefli, M. Ghazanfari, M. B. Abiri
In this paper a fuzzy decision aid system is developed base on new concepts that presented in the field of fuzzy decision making in fuzzy environment (FDMFE). This framework aids decision makers to understand different circumstances of an uncertain problem that may occur in the future. Also, to keep decision maker from the optimization problem complexities, a decision support system, which can be replaced by optimization problem, is presented to make optimum or near optimum decisions without solving optimization problem directly. An application of the developed decision aid model and the decision support system is presented in the field of inventory models.
{"title":"An Integrated Model for Optimization Oriented Decision Aiding and Rule Based Decision Making in Fuzzy Environment","authors":"A. Yousefli, M. Ghazanfari, M. B. Abiri","doi":"10.5899/2014/JFSVA-00141","DOIUrl":"https://doi.org/10.5899/2014/JFSVA-00141","url":null,"abstract":"In this paper a fuzzy decision aid system is developed base on new concepts that presented in the field of fuzzy decision making in fuzzy environment (FDMFE). This framework aids decision makers to understand different circumstances of an uncertain problem that may occur in the future. Also, to keep decision maker from the optimization problem complexities, a decision support system, which can be replaced by optimization problem, is presented to make optimum or near optimum decisions without solving optimization problem directly. An application of the developed decision aid model and the decision support system is presented in the field of inventory models.","PeriodicalId":308518,"journal":{"name":"Journal of Fuzzy Set Valued Analysis","volume":"2014 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131330002","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}
Pub Date : 1900-01-01DOI: 10.5899/2016/JFSVA-00238
Mahdieh Allahviranloo, W. Recker
Understanding scheduling behavior of households has been the focus of research for nearly half a century. Presumably activity engagement is being impacted by the importance of the activity to household members as well as time and cost constraints. Depending on the level of time budget, household members would eliminates some activities from the agenda or replace them with higher priority ones. In this paper, in order to capture the importance of different activities, we propose a methodology to schedule household activities under different levels of uncertainty about the importance of the activity. In this approach we combine discrete choice models and concepts of Fuzzy logic to identify core versus non-core activities in the agenda. The possibility of inclusion of an activity is the agenda is computed by estimating the expected importance of the activity and mapping to a set of fuzzy graphs. Activity scheduling and selection is then modeled as the outcome of a mixed integer optimization problem, in which the objective function is maximizing the expected desirability gained from activities and total saved time, subject to network connectivity, time windows, time budget and cost budget constraints.
{"title":"Identifying Core vs. Non-Core Activities of Household Members","authors":"Mahdieh Allahviranloo, W. Recker","doi":"10.5899/2016/JFSVA-00238","DOIUrl":"https://doi.org/10.5899/2016/JFSVA-00238","url":null,"abstract":"Understanding scheduling behavior of households has been the focus of research for nearly half a century. Presumably activity engagement is being impacted by the importance of the activity to household members as well as time and cost constraints. Depending on the level of time budget, household members would eliminates some activities from the agenda or replace them with higher priority ones. In this paper, in order to capture the importance of different activities, we propose a methodology to schedule household activities under different levels of uncertainty about the importance of the activity. In this approach we combine discrete choice models and concepts of Fuzzy logic to identify core versus non-core activities in the agenda. The possibility of inclusion of an activity is the agenda is computed by estimating the expected importance of the activity and mapping to a set of fuzzy graphs. Activity scheduling and selection is then modeled as the outcome of a mixed integer optimization problem, in which the objective function is maximizing the expected desirability gained from activities and total saved time, subject to network connectivity, time windows, time budget and cost budget constraints.","PeriodicalId":308518,"journal":{"name":"Journal of Fuzzy Set Valued Analysis","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121829028","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}
Pub Date : 1900-01-01DOI: 10.5899/2013/JFSVA-00139
S. Rezvani
In this paper, we want represented a method for ranking of two exponential trapezoidal fuzzy numbers. A median value is proposed for the ranking of exponential trapezoidal fuzzy numbers. For the validation the results of the proposed approach are compared with different existing approaches.
{"title":"Ranking Exponential Trapezoidal Fuzzy Numbers by Median Value","authors":"S. Rezvani","doi":"10.5899/2013/JFSVA-00139","DOIUrl":"https://doi.org/10.5899/2013/JFSVA-00139","url":null,"abstract":"In this paper, we want represented a method for ranking of two exponential trapezoidal fuzzy numbers. A median value is proposed for the ranking of exponential trapezoidal fuzzy numbers. For the validation the results of the proposed approach are compared with different existing approaches.","PeriodicalId":308518,"journal":{"name":"Journal of Fuzzy Set Valued Analysis","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133662660","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}
Pub Date : 1900-01-01DOI: 10.5899/2014/JFSVA-00177
M. Paripour, E. Zarei, A. Shahsavaran
In this paper, we propose numerical solution to solve a system of fuzzy nonlinear equations based on homotopy method. In this method the algorithm is illustrated by solving several numerical examples.
本文提出了基于同伦方法求解一类模糊非线性方程组的数值解。通过算例对该方法进行了说明。
{"title":"Numerical solution for a system of fuzzy nonlinear equations","authors":"M. Paripour, E. Zarei, A. Shahsavaran","doi":"10.5899/2014/JFSVA-00177","DOIUrl":"https://doi.org/10.5899/2014/JFSVA-00177","url":null,"abstract":"In this paper, we propose numerical solution to solve a system of fuzzy nonlinear equations based on homotopy method. In this method the algorithm is illustrated by solving several numerical examples.","PeriodicalId":308518,"journal":{"name":"Journal of Fuzzy Set Valued Analysis","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132836074","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}
Pub Date : 1900-01-01DOI: 10.5899/2016/JFSVA-00266
F. Abbasi, T. Allahviranloo, S. Abbasbandy
In this paper, we shall embark on the study of the algebraic object known as a fuzzy group which serves as one of the fundamental building blocks for the subject which is called fuzzy abstract algebra. In our opinion, the fuzzy algebraic systems are usually sets on whose elements we can operate algebraically by this we mean that we can combine two elements of the set, perhaps in several ways, to obtain a third element of the set and, in addition, we assume that these fuzzy algebraic operations are subject to certain rules, which are explicitly spelled out in what we call the axioms or postulates defining the system. In this abstract setting we then attempt to prove theorems about these very general structures. We should like to stress that these fuzzy algebraic systems and their axioms, must come from the experience of looking at many examples. Namely, they should be rich in meaningful results. Hence, the acceptable definition of fuzzy group and subgroup are presented with binary operations and on the basis of the specified parameter, called ambiguity rank, which fulfils the basic requirements. The properties of these fuzzy groups and their fundamental qualities are discussed and then, the several illustrative examples were given. The future prospect of this paper is a new attitude to fuzzy basic mathematics, which will be referred to in the end.
{"title":"A new attitude coupled with fuzzy thinking to fuzzy group and subgroup","authors":"F. Abbasi, T. Allahviranloo, S. Abbasbandy","doi":"10.5899/2016/JFSVA-00266","DOIUrl":"https://doi.org/10.5899/2016/JFSVA-00266","url":null,"abstract":"In this paper, we shall embark on the study of the algebraic object known as a fuzzy group which serves as one of the fundamental building blocks for the subject which is called fuzzy abstract algebra. In our opinion, the fuzzy algebraic systems are usually sets on whose elements we can operate algebraically by this we mean that we can combine two elements of the set, perhaps in several ways, to obtain a third element of the set and, in addition, we assume that these fuzzy algebraic operations are subject to certain rules, which are explicitly spelled out in what we call the axioms or postulates defining the system. In this abstract setting we then attempt to prove theorems about these very general structures. We should like to stress that these fuzzy algebraic systems and their axioms, must come from the experience of looking at many examples. Namely, they should be rich in meaningful results. Hence, the acceptable definition of fuzzy group and subgroup are presented with binary operations and on the basis of the specified parameter, called ambiguity rank, which fulfils the basic requirements. The properties of these fuzzy groups and their fundamental qualities are discussed and then, the several illustrative examples were given. The future prospect of this paper is a new attitude to fuzzy basic mathematics, which will be referred to in the end.","PeriodicalId":308518,"journal":{"name":"Journal of Fuzzy Set Valued Analysis","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132217597","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}
Pub Date : 1900-01-01DOI: 10.5899/2016/JFSVA-00269
J. Močkoř
Interpretations of first order fuzzy logic formulas in models based on two categories of sets with similarity relations as objects are introduced. Formulas are interpreted either as special morphisms in these categories, or f-cut systems, which generalize $alpha$-cuts of classical fuzzy sets. Relationships between these two interpretations of formulas in corresponding categories are investigated.
{"title":"Fuzzy logic interpretations in categories of fuzzy objects","authors":"J. Močkoř","doi":"10.5899/2016/JFSVA-00269","DOIUrl":"https://doi.org/10.5899/2016/JFSVA-00269","url":null,"abstract":"Interpretations of first order fuzzy logic formulas in models based on two categories of sets with similarity relations as objects are introduced. Formulas are interpreted either as special morphisms in these categories, or f-cut systems, which generalize $alpha$-cuts of classical fuzzy sets. Relationships between these two interpretations of formulas in corresponding categories are investigated.","PeriodicalId":308518,"journal":{"name":"Journal of Fuzzy Set Valued Analysis","volume":"55 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113991997","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}
Pub Date : 1900-01-01DOI: 10.5899/2013/JFSVA-00137
Ke Wang
An Uzawa method is presented for solving fuzzy linear systems whose coefficient matrix is crisp and the right-hand side column is arbitrary fuzzy number vector. The explicit iterative scheme is given. The convergence is analyzed with convergence theorems and the optimal parameter is obtained. Numerical examples are given to illustrate the procedure and show the effectiveness and efficiency of the method.
{"title":"Uzawa method for fuzzy linear system","authors":"Ke Wang","doi":"10.5899/2013/JFSVA-00137","DOIUrl":"https://doi.org/10.5899/2013/JFSVA-00137","url":null,"abstract":"An Uzawa method is presented for solving fuzzy linear systems whose coefficient matrix is crisp and the right-hand side column is arbitrary fuzzy number vector. The explicit iterative scheme is given. The convergence is analyzed with convergence theorems and the optimal parameter is obtained. Numerical examples are given to illustrate the procedure and show the effectiveness and efficiency of the method.","PeriodicalId":308518,"journal":{"name":"Journal of Fuzzy Set Valued Analysis","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127971610","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：