Pub Date : 2021-10-02DOI: 10.1080/16168658.2021.1993668
M. Mohseni Takallo, R. Borzooei, Y. Jun
The concept of Sup-hesitant fuzzy p-ideal in BCK/BCI-algebras is introduced, and related properties are investigated. A characterisation of Sup-hesitant fuzzy p-ideal of BCK/BCI-algebras is provided. Relations between Sup-hesitant fuzzy p-ideal and Sup-hesitant fuzzy ideal are investigated. Conditions for a Sup-hesitant fuzzy ideal to be a Sup-hesitant fuzzy p-ideal are provided. Characterisation of p-semisimple BCI-algebra is considered. Extension property for Sup-hesitant fuzzy p-ideal is established.
{"title":"Sup-Hesitant Fuzzy p-Ideals of BCI-Algebras","authors":"M. Mohseni Takallo, R. Borzooei, Y. Jun","doi":"10.1080/16168658.2021.1993668","DOIUrl":"https://doi.org/10.1080/16168658.2021.1993668","url":null,"abstract":"The concept of Sup-hesitant fuzzy p-ideal in BCK/BCI-algebras is introduced, and related properties are investigated. A characterisation of Sup-hesitant fuzzy p-ideal of BCK/BCI-algebras is provided. Relations between Sup-hesitant fuzzy p-ideal and Sup-hesitant fuzzy ideal are investigated. Conditions for a Sup-hesitant fuzzy ideal to be a Sup-hesitant fuzzy p-ideal are provided. Characterisation of p-semisimple BCI-algebra is considered. Extension property for Sup-hesitant fuzzy p-ideal is established.","PeriodicalId":37623,"journal":{"name":"Fuzzy Information and Engineering","volume":"10 1","pages":"460 - 469"},"PeriodicalIF":1.2,"publicationDate":"2021-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73611867","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 : 2021-09-02DOI: 10.1080/16168658.2021.1971143
Amal Kumar Adak, Davood Darvishi Salookolaei
Pythagorean fuzzy sets are advancements of the intuitionistic fuzzy sets and overcome their limitations. In this paper, we exploit the concept of full congruence relation of Pythagorean fuzzy sets and define the lower and upper approximations of Pythagorean fuzzy set. Using the concept of approximations of Pythagorean fuzzy set we introduce the concept of rough Pythagorean fuzzy set.
{"title":"Some Properties of Rough Pythagorean Fuzzy Sets","authors":"Amal Kumar Adak, Davood Darvishi Salookolaei","doi":"10.1080/16168658.2021.1971143","DOIUrl":"https://doi.org/10.1080/16168658.2021.1971143","url":null,"abstract":"Pythagorean fuzzy sets are advancements of the intuitionistic fuzzy sets and overcome their limitations. In this paper, we exploit the concept of full congruence relation of Pythagorean fuzzy sets and define the lower and upper approximations of Pythagorean fuzzy set. Using the concept of approximations of Pythagorean fuzzy set we introduce the concept of rough Pythagorean fuzzy set.","PeriodicalId":37623,"journal":{"name":"Fuzzy Information and Engineering","volume":"39 1","pages":"420 - 435"},"PeriodicalIF":1.2,"publicationDate":"2021-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75147035","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 : 2021-07-03DOI: 10.1080/16168658.2021.1952760
M. Sam’an, Y. Dasril, M. A. Muslim
The degree of type-1 fuzzy sets membership function cannot express the linguistic variable of a complex problem. The type-2 fuzzy sets as a problem solver such that more fuzziness for constructing membership functions can be handled. Recently, many multi-criteria decision making (MCDM) methods have been expanded using type-2 fuzzy sets. Analytical Hierarchy Process (AHP) is one of the well-known MCDM that can take into account multiple and conflicting criteria at the same time. Our goal is to develop an interval type-2 trapezoidal fuzzy AHP through the new proposed ranking i.e. the modified total integral value. Based on the illustrative examples for trapezoidal type-2 fuzzy sets, the new proposed ranking has a well-performance in ranking. Furthermore, we apply the new trapezoidal type-2 fuzzy AHP to a supplier selection problem. Based on the results of the application, the new fuzzy AHP has the same ranking results as the existing fuzzy AHP.
{"title":"The New Fuzzy Analytical Hierarchy Process with Interval Type-2 Trapezoidal Fuzzy Sets and Its Application","authors":"M. Sam’an, Y. Dasril, M. A. Muslim","doi":"10.1080/16168658.2021.1952760","DOIUrl":"https://doi.org/10.1080/16168658.2021.1952760","url":null,"abstract":"The degree of type-1 fuzzy sets membership function cannot express the linguistic variable of a complex problem. The type-2 fuzzy sets as a problem solver such that more fuzziness for constructing membership functions can be handled. Recently, many multi-criteria decision making (MCDM) methods have been expanded using type-2 fuzzy sets. Analytical Hierarchy Process (AHP) is one of the well-known MCDM that can take into account multiple and conflicting criteria at the same time. Our goal is to develop an interval type-2 trapezoidal fuzzy AHP through the new proposed ranking i.e. the modified total integral value. Based on the illustrative examples for trapezoidal type-2 fuzzy sets, the new proposed ranking has a well-performance in ranking. Furthermore, we apply the new trapezoidal type-2 fuzzy AHP to a supplier selection problem. Based on the results of the application, the new fuzzy AHP has the same ranking results as the existing fuzzy AHP.","PeriodicalId":37623,"journal":{"name":"Fuzzy Information and Engineering","volume":"1 1","pages":"391 - 419"},"PeriodicalIF":1.2,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89608012","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 : 2021-07-03DOI: 10.1080/16168658.2021.1938868
M. Borza, A. S. Rambely
Background: In the literature, there exists several approaches to address the multi-objective linear fractional programming problem (MOLFPP). However, there is a drawback to these methods. Aim: This paper presents an efficient method treating the MOLFPP. Methodology: To construct our approach,the membership functions of the objectives, suitable non-linear variable transformations, and max-min technique are used. Results: In our proposed method, the MOLFPP is finally changed into a linear programming problem (LPP). It is proven that the optimal solution of the LPP is an efficient solution for the MOLFPP. Conclusion: Numerical examples are solved, and the results demonstrate that our method with less computational expenses and cost reach the efficient solutions.
{"title":"A New Method to Solve Multi-Objective Linear Fractional Problems","authors":"M. Borza, A. S. Rambely","doi":"10.1080/16168658.2021.1938868","DOIUrl":"https://doi.org/10.1080/16168658.2021.1938868","url":null,"abstract":"Background: In the literature, there exists several approaches to address the multi-objective linear fractional programming problem (MOLFPP). However, there is a drawback to these methods. Aim: This paper presents an efficient method treating the MOLFPP. Methodology: To construct our approach,the membership functions of the objectives, suitable non-linear variable transformations, and max-min technique are used. Results: In our proposed method, the MOLFPP is finally changed into a linear programming problem (LPP). It is proven that the optimal solution of the LPP is an efficient solution for the MOLFPP. Conclusion: Numerical examples are solved, and the results demonstrate that our method with less computational expenses and cost reach the efficient solutions.","PeriodicalId":37623,"journal":{"name":"Fuzzy Information and Engineering","volume":"61 1","pages":"323 - 334"},"PeriodicalIF":1.2,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80574362","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 : 2021-07-03DOI: 10.1080/16168658.2021.1939632
Muhammad Jabir Khan, P. Kumam, W. Kumam, A. Al-kenani
This paper introduces the Euclidean, Hamming, and the generalized distance measures for picture fuzzy soft sets and discusses their properties. The numerical examples of decision-making and pattern recognition are focused. We also develop a robust VIKOR method for PFSSs. The relative and precise ideal picture fuzzy values (PFVs), robust factors and ranking indexes are defined. Different algorithmic procedures of robust VIKOR based on the relative and precise ideal PFVs, relative and precise robust factor, precise and picture fuzzy weights and relative and precise ranking indexes are proposed. In the end, the investment problem is solved by using the proposed method.
{"title":"Picture Fuzzy Soft Robust VIKOR Method and its Applications in Decision-Making","authors":"Muhammad Jabir Khan, P. Kumam, W. Kumam, A. Al-kenani","doi":"10.1080/16168658.2021.1939632","DOIUrl":"https://doi.org/10.1080/16168658.2021.1939632","url":null,"abstract":"This paper introduces the Euclidean, Hamming, and the generalized distance measures for picture fuzzy soft sets and discusses their properties. The numerical examples of decision-making and pattern recognition are focused. We also develop a robust VIKOR method for PFSSs. The relative and precise ideal picture fuzzy values (PFVs), robust factors and ranking indexes are defined. Different algorithmic procedures of robust VIKOR based on the relative and precise ideal PFVs, relative and precise robust factor, precise and picture fuzzy weights and relative and precise ranking indexes are proposed. In the end, the investment problem is solved by using the proposed method.","PeriodicalId":37623,"journal":{"name":"Fuzzy Information and Engineering","volume":"25 1","pages":"296 - 322"},"PeriodicalIF":1.2,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72599621","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 : 2021-06-28DOI: 10.1080/16168658.2021.1908819
M. Mohammadzaheri, Amirhosein Amouzadeh, M. Doustmohammadi, Mohammadreza Emadi, E. Jamshidi, M. Ghodsi, P. Soltani
Summary: A new inspection technique for complex mechanical structures is proposed in this paper, where a fuzzy inference system carries out structural inspection. The inputs to the fuzzy inference system are the elements of a fault signature, an array of numbers prepared with use of below 5 kHz resonance frequencies of faultless and a number of faulty specimens. Advantage: Below 5 kHz resonance frequencies are easier and less expensive to obtain compared to higher frequency ones. Limit: Due to high expenses of experiments, reliable finite element models were alternatively used to obtain resonance frequencies of the faulty specimens. Results: The developed fuzzy inference system in this research accurately located an under-surface fault in an engine cylinder block.
{"title":"Fuzzy Analysis of Resonance Frequencies for Structural Inspection of an Engine Cylinder Block","authors":"M. Mohammadzaheri, Amirhosein Amouzadeh, M. Doustmohammadi, Mohammadreza Emadi, E. Jamshidi, M. Ghodsi, P. Soltani","doi":"10.1080/16168658.2021.1908819","DOIUrl":"https://doi.org/10.1080/16168658.2021.1908819","url":null,"abstract":"Summary: A new inspection technique for complex mechanical structures is proposed in this paper, where a fuzzy inference system carries out structural inspection. The inputs to the fuzzy inference system are the elements of a fault signature, an array of numbers prepared with use of below 5 kHz resonance frequencies of faultless and a number of faulty specimens. Advantage: Below 5 kHz resonance frequencies are easier and less expensive to obtain compared to higher frequency ones. Limit: Due to high expenses of experiments, reliable finite element models were alternatively used to obtain resonance frequencies of the faulty specimens. Results: The developed fuzzy inference system in this research accurately located an under-surface fault in an engine cylinder block.","PeriodicalId":37623,"journal":{"name":"Fuzzy Information and Engineering","volume":"7 1","pages":"266 - 276"},"PeriodicalIF":1.2,"publicationDate":"2021-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77819594","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 : 2021-06-28DOI: 10.1080/16168658.2021.1943187
U. Rehman, T. Mahmood
In this article, firstly, we describe picture fuzzy N-soft sets (PFN-SSs) as a generalization of picture fuzzy sets (PFSs) and N-soft sets (N-SS) by observing that one of the essential concept of neutral grade is missing in intuitionistic fuzzy N-SS (IFN-SS) theory. The concept of neutrality grade can be observed in the situation when we encounter human views including more answers of type: yes, abstain, no, refusal. For instance, in election the election commission or election council issues voting papers for the candidate. The voting outcomes are categorized into 4 groups with the number of papers namely, vote for, abstain, vote against, and refusal voting. Further, We define the fundamental properties of PFN-SS and introduce M-subset, F-subset, compliment, intersections, unions, of PFN-SS and give their examples. Secondly, we define an algorithm to cope with PFN-SS data which is more generalized then the algorithm defined for IFN-SS. To show the advantage and usefulness of the defined technique, we give two examples from real life by utilizing PFN-SS data. The result shows in the comparison that our initiated method is more general and suitable than the IFN-SS, fuzzy N-SS (FN-SS), and N-SS.
{"title":"Picture Fuzzy N-Soft Sets and Their Applications in Decision-Making Problems","authors":"U. Rehman, T. Mahmood","doi":"10.1080/16168658.2021.1943187","DOIUrl":"https://doi.org/10.1080/16168658.2021.1943187","url":null,"abstract":"In this article, firstly, we describe picture fuzzy N-soft sets (PFN-SSs) as a generalization of picture fuzzy sets (PFSs) and N-soft sets (N-SS) by observing that one of the essential concept of neutral grade is missing in intuitionistic fuzzy N-SS (IFN-SS) theory. The concept of neutrality grade can be observed in the situation when we encounter human views including more answers of type: yes, abstain, no, refusal. For instance, in election the election commission or election council issues voting papers for the candidate. The voting outcomes are categorized into 4 groups with the number of papers namely, vote for, abstain, vote against, and refusal voting. Further, We define the fundamental properties of PFN-SS and introduce M-subset, F-subset, compliment, intersections, unions, of PFN-SS and give their examples. Secondly, we define an algorithm to cope with PFN-SS data which is more generalized then the algorithm defined for IFN-SS. To show the advantage and usefulness of the defined technique, we give two examples from real life by utilizing PFN-SS data. The result shows in the comparison that our initiated method is more general and suitable than the IFN-SS, fuzzy N-SS (FN-SS), and N-SS.","PeriodicalId":37623,"journal":{"name":"Fuzzy Information and Engineering","volume":"150 1","pages":"335 - 367"},"PeriodicalIF":1.2,"publicationDate":"2021-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76415938","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 : 2021-06-24DOI: 10.1080/16168658.2021.1943887
C. Treesatayapun
A model-free adaptive control for non-affine discrete time systems is developed by utilising the output feedback and action-critic networks. Fuzzy rules emulated network (FREN) is employed as the action network and multi-input version (MiFREN) is implemented as the critic network. Both networks are constructed using human knowledge based on IF–THEN rules according to the controlled plant and the learning laws are established by reinforcement learning without any off-line learning phase. The theoretical derivation of the convergence of the tracking error and internal signal is demonstrated. The numerical simulation and the experimental system are given to validate the proposed scheme.
{"title":"Output Feedback Controller for a Class of Unknown Nonlinear Discrete Time Systems Using Fuzzy Rules Emulated Networks and Reinforcement Learning","authors":"C. Treesatayapun","doi":"10.1080/16168658.2021.1943887","DOIUrl":"https://doi.org/10.1080/16168658.2021.1943887","url":null,"abstract":"A model-free adaptive control for non-affine discrete time systems is developed by utilising the output feedback and action-critic networks. Fuzzy rules emulated network (FREN) is employed as the action network and multi-input version (MiFREN) is implemented as the critic network. Both networks are constructed using human knowledge based on IF–THEN rules according to the controlled plant and the learning laws are established by reinforcement learning without any off-line learning phase. The theoretical derivation of the convergence of the tracking error and internal signal is demonstrated. The numerical simulation and the experimental system are given to validate the proposed scheme.","PeriodicalId":37623,"journal":{"name":"Fuzzy Information and Engineering","volume":"5 1","pages":"368 - 390"},"PeriodicalIF":1.2,"publicationDate":"2021-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88770373","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 : 2021-06-19DOI: 10.1080/16168658.2021.1937903
Dimitrios S. Grammatikopoulos, B. Papadopoulos
In this paper, we revisit and study the basic properties of two families of fuzzy implications, the so-called and implications. More specific, we study when these fuzzy implications satisfy, or not, the neutrality property , the exchange principle , the identity principle and the ordering property . Moreover, a study is presented for the law of importation with respect to a t- norm. Also, we study the relation of conjugation in implications.
{"title":"A Study of (T, N)– and (N ′, T, N)– Implications","authors":"Dimitrios S. Grammatikopoulos, B. Papadopoulos","doi":"10.1080/16168658.2021.1937903","DOIUrl":"https://doi.org/10.1080/16168658.2021.1937903","url":null,"abstract":"In this paper, we revisit and study the basic properties of two families of fuzzy implications, the so-called and implications. More specific, we study when these fuzzy implications satisfy, or not, the neutrality property , the exchange principle , the identity principle and the ordering property . Moreover, a study is presented for the law of importation with respect to a t- norm. Also, we study the relation of conjugation in implications.","PeriodicalId":37623,"journal":{"name":"Fuzzy Information and Engineering","volume":"59 1","pages":"277 - 295"},"PeriodicalIF":1.2,"publicationDate":"2021-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73357473","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 : 2021-04-03DOI: 10.1080/16168658.2021.1915451
Nadji Hadroug, A. Hafaifa, Abdelhamid IRATNI, M. Guemana
Recently, the development of the industry requires monitoring and follow-up of the working conditions of the facilities, to determine the reliability, availability, and durability of these systems, for objectively estimating the service life of these installations with reduced maintenance costs. In this sense, this work proposes a novel approach to reliability modeling, to determine failure assessment indicators based on an adaptive neuro-fuzzy inference system applied on a gas turbine. This is in order to describe the behavior of this rotating machine and to estimate their operating safety parameters, to improve its performance in terms of maintainability, availability, and operational safety with effective durability. The application of fuzzy rules to reliability estimation with practical implementations is innovative, making it possible to provide solutions to problems of reliable identification of gas turbines in their complex operating environments.
{"title":"Reliability Modeling Using an Adaptive Neuro-Fuzzy Inference System: Gas Turbine Application","authors":"Nadji Hadroug, A. Hafaifa, Abdelhamid IRATNI, M. Guemana","doi":"10.1080/16168658.2021.1915451","DOIUrl":"https://doi.org/10.1080/16168658.2021.1915451","url":null,"abstract":"Recently, the development of the industry requires monitoring and follow-up of the working conditions of the facilities, to determine the reliability, availability, and durability of these systems, for objectively estimating the service life of these installations with reduced maintenance costs. In this sense, this work proposes a novel approach to reliability modeling, to determine failure assessment indicators based on an adaptive neuro-fuzzy inference system applied on a gas turbine. This is in order to describe the behavior of this rotating machine and to estimate their operating safety parameters, to improve its performance in terms of maintainability, availability, and operational safety with effective durability. The application of fuzzy rules to reliability estimation with practical implementations is innovative, making it possible to provide solutions to problems of reliable identification of gas turbines in their complex operating environments.","PeriodicalId":37623,"journal":{"name":"Fuzzy Information and Engineering","volume":"88 1","pages":"154 - 183"},"PeriodicalIF":1.2,"publicationDate":"2021-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73776942","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}
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