Pub Date : 1900-01-01DOI: 10.5899/2012/JFSVA-00105
M. Otadi, M. Mosleh
In this paper, the main is to develop a method to solve an arbitrary inconsistent fuzzy linear system by using the embedding approach. Considering the existing of minimal solution to $mtimes n$ linear fuzzy system is done. To illustrate the proposed model numerical examples are given and obtained results are discussed.
{"title":"Minimal Solution of Non-square Fuzzy Linear Systems","authors":"M. Otadi, M. Mosleh","doi":"10.5899/2012/JFSVA-00105","DOIUrl":"https://doi.org/10.5899/2012/JFSVA-00105","url":null,"abstract":"In this paper, the main is to develop a method to solve an arbitrary inconsistent fuzzy linear system by using the embedding approach. Considering the existing of minimal solution to $mtimes n$ linear fuzzy system is done. To illustrate the proposed model numerical examples are given and obtained results are discussed.","PeriodicalId":308518,"journal":{"name":"Journal of Fuzzy Set Valued Analysis","volume":"16 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":"122121341","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-00287
R. Pakzad, M. Keshavarz, M. Pakzad
Many mathematical models have presented for preventing different diseases such as cancers. But the question often asked is why the suggested models are not effective for all people suffering from a special disease. Researchers have mentioned patients' mental and physical conditions not considered by such models. In this article by consideration of special fuzzy factors, we attempt to present a model which can show the progress and dis-progress of cancer cells with attention to anatomical and physiological conditions of the body.
{"title":"Multiscale fuzzy modeling and Mathematical problems Related To Tumor Evolution and Medical Therapy","authors":"R. Pakzad, M. Keshavarz, M. Pakzad","doi":"10.5899/2016/JFSVA-00287","DOIUrl":"https://doi.org/10.5899/2016/JFSVA-00287","url":null,"abstract":"Many mathematical models have presented for preventing different diseases such as cancers. But the question often asked is why the suggested models are not effective for all people suffering from a special disease. Researchers have mentioned patients' mental and physical conditions not considered by such models. In this article by consideration of special fuzzy factors, we attempt to present a model which can show the progress and dis-progress of cancer cells with attention to anatomical and physiological conditions of the body.","PeriodicalId":308518,"journal":{"name":"Journal of Fuzzy Set Valued Analysis","volume":"1 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":"128683960","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-00229
F. Razmi, R. Moghaddam, A. Rowhanimanesh
In this paper a single input fuzzy controller is applied on autonomous drug-encapsulated nanoparticles (ADENPs) to restrict the cancer growth. The proposed ADENPs, swarmly release the drug in local cancerous tissue and effectively decreases the destruction of normal tissue. The amount of released drug is defined considering to feed backed values of tumor growth rate and the used drug. Some significant characteristics of Nano particles compared to Nano-robots is their ability to recognize the cancerous tissue from the normal one and their simple structure. Nano particles became an attractive topic in Nano science and many efforts have been done to manufacture these particles. Simulation results show that the proposed controlling method not only decreases the cancerous tissue effectively but also reduces the side effects of drug impressively.
{"title":"Control of cancer growth using single input autonomous fuzzy Nano-particles","authors":"F. Razmi, R. Moghaddam, A. Rowhanimanesh","doi":"10.5899/2015/jfsva-00229","DOIUrl":"https://doi.org/10.5899/2015/jfsva-00229","url":null,"abstract":"In this paper a single input fuzzy controller is applied on autonomous drug-encapsulated nanoparticles (ADENPs) to restrict the cancer growth. The proposed ADENPs, swarmly release the drug in local cancerous tissue and effectively decreases the destruction of normal tissue. The amount of released drug is defined considering to feed backed values of tumor growth rate and the used drug. Some significant characteristics of Nano particles compared to Nano-robots is their ability to recognize the cancerous tissue from the normal one and their simple structure. Nano particles became an attractive topic in Nano science and many efforts have been done to manufacture these particles. Simulation results show that the proposed controlling method not only decreases the cancerous tissue effectively but also reduces the side effects of drug impressively.","PeriodicalId":308518,"journal":{"name":"Journal of Fuzzy Set Valued Analysis","volume":"58 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":"129363314","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-00196
A. Amiri
A numerical method for solving the fuzzy generalized pantograph equation under fuzzy initial value conditions is presented. This technique provides a sequence of functions which converges to the exact solution to the problem and is based on the use of Lagrange multipliers for identification of optimal value of a parameter in a functional. To display the validity and applicability of the numerical method two illustrative examples are presented.
{"title":"Variational Iteration Method for Solving a Fuzzy Generalized Pantograph Equation","authors":"A. Amiri","doi":"10.5899/2014/JFSVA-00196","DOIUrl":"https://doi.org/10.5899/2014/JFSVA-00196","url":null,"abstract":"A numerical method for solving the fuzzy generalized pantograph equation under fuzzy initial value conditions is presented. This technique provides a sequence of functions which converges to the exact solution to the problem and is based on the use of Lagrange multipliers for identification of optimal value of a parameter in a functional. To display the validity and applicability of the numerical method two illustrative examples are presented.","PeriodicalId":308518,"journal":{"name":"Journal of Fuzzy Set Valued Analysis","volume":"9 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":"129682353","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-00346
S. Islam, Haridas Biswas
In this paper we have formulated a multi-item fuzzy inventory model with stock dependent demand rate and shortages are allowed with partial backlogging. The multi-item inventory model with demand dependent unit cost has been formulated alone with storage space constraints. The partial backlogging rate of unsatisfied demand is assumed to be decreasing exponential function for waiting time. Here the cost parameters, the objective function and constraint are imposed in fuzzy nature. The model has been solved by Fuzzy Goal Programming (FGP) method. Finally the model is expressed by numerical example.
{"title":"Fuzzy multi-item inventory model with time varying stock dependent demand under partial backlogging","authors":"S. Islam, Haridas Biswas","doi":"10.5899/2016/jfsva-00346","DOIUrl":"https://doi.org/10.5899/2016/jfsva-00346","url":null,"abstract":"In this paper we have formulated a multi-item fuzzy inventory model with stock dependent demand rate and shortages are allowed with partial backlogging. The multi-item inventory model with demand dependent unit cost has been formulated alone with storage space constraints. The partial backlogging rate of unsatisfied demand is assumed to be decreasing exponential function for waiting time. Here the cost parameters, the objective function and constraint are imposed in fuzzy nature. The model has been solved by Fuzzy Goal Programming (FGP) method. Finally the model is expressed by numerical example.","PeriodicalId":308518,"journal":{"name":"Journal of Fuzzy Set Valued Analysis","volume":"36 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":"123992280","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-00245
E. Ahmady
In this paper a numerical method for solving n-order fuzzy differential equations is considered. This method which called piecewise approximation method, is obtained by interpolating a polynomial on fuzzy determined values. The proposed method is compared to Allahviranloo's method in [6], and it is shown that this method in more accurate than Allahviranloo's method. The piecewise approximation method is illustrated by a comparative example.
{"title":"Piecewise Approximation Method for Nth-order Fuzzy Differential Equations","authors":"E. Ahmady","doi":"10.5899/2015/JFSVA-00245","DOIUrl":"https://doi.org/10.5899/2015/JFSVA-00245","url":null,"abstract":"In this paper a numerical method for solving n-order fuzzy differential equations is considered. This method which called piecewise approximation method, is obtained by interpolating a polynomial on fuzzy determined values. The proposed method is compared to Allahviranloo's method in [6], and it is shown that this method in more accurate than Allahviranloo's method. The piecewise approximation method is illustrated by a comparative example.","PeriodicalId":308518,"journal":{"name":"Journal of Fuzzy Set Valued Analysis","volume":"32 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":"114328092","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-00220
T. Pathinathan, K. Ponnivalavan
In this paper we define diamond fuzzy number with the help of triangular fuzzy number. We include basic arithmetic operations like addition, subtraction of diamond fuzzy numbers with examples. We define diamond fuzzy matrix with some matrix properties. We have defined Nested diamond fuzzy number and Linked diamond fuzzy number. We have further classified Right Linked Diamond Fuzzy number and Left Linked Diamond Fuzzy number. Finally we have verified the arithmetic operations for the above mentioned types of Diamond Fuzzy Numbers.
{"title":"Diamond Fuzzy Number","authors":"T. Pathinathan, K. Ponnivalavan","doi":"10.5899/2015/JFSVA-00220","DOIUrl":"https://doi.org/10.5899/2015/JFSVA-00220","url":null,"abstract":"In this paper we define diamond fuzzy number with the help of triangular fuzzy number. We include basic arithmetic operations like addition, subtraction of diamond fuzzy numbers with examples. We define diamond fuzzy matrix with some matrix properties. We have defined Nested diamond fuzzy number and Linked diamond fuzzy number. We have further classified Right Linked Diamond Fuzzy number and Left Linked Diamond Fuzzy number. Finally we have verified the arithmetic operations for the above mentioned types of Diamond Fuzzy Numbers.","PeriodicalId":308518,"journal":{"name":"Journal of Fuzzy Set Valued Analysis","volume":"46 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":"116291571","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-00225
D. S. Yadav, S. Thakur, S. S. Thakur
In the present paper, we extend some related fixed point theorems due to Gupta [5] for four fuzzy metric spaces. The results of Gupta are the special cases of the results established in this paper.
{"title":"Some Related Fixed Point Theorems for Four Fuzzy Metric Spaces","authors":"D. S. Yadav, S. Thakur, S. S. Thakur","doi":"10.5899/2015/JFSVA-00225","DOIUrl":"https://doi.org/10.5899/2015/JFSVA-00225","url":null,"abstract":"In the present paper, we extend some related fixed point theorems due to Gupta [5] for four fuzzy metric spaces. The results of Gupta are the special cases of the results established in this paper.","PeriodicalId":308518,"journal":{"name":"Journal of Fuzzy Set Valued Analysis","volume":"9 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":"126374563","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-00255
Mohammad Mohammadi Najafabadi, E. Eslami, Sara Mansouri
This article uses a specific hybrid evolutionary algorithmto solve the series parallel redundancy optimization problem which is in a fuzzy framework. Reliability optimization provides a means to help the reliability engineer achieve such a goal. Most methods of reliability optimization assume that systems have redundancy components in series and /or parallel systems and that alternative designs are available. Optimization concentrates on optimal allocation of redundancy components and optimalselection of alternative designs to meet system requirements. A fuzzy simulation-based evolutionary algorithm is then employed to solve these kinds of fuzzy programming with fuzzy goal and fuzzy constraints. Finally, numerical examples are also given.
{"title":"Operation of Hybrid Evolutionary Algorithm and Fuzzy Sets for Reliability Optimization of Engineering Systems","authors":"Mohammad Mohammadi Najafabadi, E. Eslami, Sara Mansouri","doi":"10.5899/2015/JFSVA-00255","DOIUrl":"https://doi.org/10.5899/2015/JFSVA-00255","url":null,"abstract":"This article uses a specific hybrid evolutionary algorithmto solve the series parallel redundancy optimization problem which is in a fuzzy framework. Reliability optimization provides a means to help the reliability engineer achieve such a goal. Most methods of reliability optimization assume that systems have redundancy components in series and /or parallel systems and that alternative designs are available. Optimization concentrates on optimal allocation of redundancy components and optimalselection of alternative designs to meet system requirements. A fuzzy simulation-based evolutionary algorithm is then employed to solve these kinds of fuzzy programming with fuzzy goal and fuzzy constraints. Finally, numerical examples are also given.","PeriodicalId":308518,"journal":{"name":"Journal of Fuzzy Set Valued Analysis","volume":"26 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":"126566353","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: 10.5899/2012/JFSVA-00108
S. Rahim, Saneifard Rasoul
When we deal with crisp data, it is very common to find the correlation between variables. Here, we propose a method to calculate the correlation coefficient for fuzzy data, but rather than defining the correlation on the intuitionistic fuzzy sets like most of the previous works, we adopt the method from central interval. This interval can be used as a crisp set approximation with respect to a fuzzy quantity. This indices can be applied for comparison of fuzzy numbers namely fuzzy correlations in fuzzy environments and expert's systems. Finally some of their applications are mentioned.
{"title":"Correlation Coefficient Between Fuzzy Numbers Based On Central Interval","authors":"S. Rahim, Saneifard Rasoul","doi":"10.5899/2012/JFSVA-00108","DOIUrl":"https://doi.org/10.5899/2012/JFSVA-00108","url":null,"abstract":"When we deal with crisp data, it is very common to find the correlation between variables. Here, we propose a method to calculate the correlation coefficient for fuzzy data, but rather than defining the correlation on the intuitionistic fuzzy sets like most of the previous works, we adopt the method from central interval. This interval can be used as a crisp set approximation with respect to a fuzzy quantity. This indices can be applied for comparison of fuzzy numbers namely fuzzy correlations in fuzzy environments and expert's systems. Finally some of their applications are mentioned.","PeriodicalId":308518,"journal":{"name":"Journal of Fuzzy Set Valued Analysis","volume":"69 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":"130064699","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：