Pub Date : 2023-11-01DOI: 10.26599/fie.2023.9270025
N. M. Bekhit, O. E. Emam, Laila Abd Elhamid
The aim of this paper is to propose an algorithm to solve and enhance a multi-level multi-objective integer quadratic programming problem (MLMOIQPP) under a single-valued Pentagonal Neutrosophic environment applied to the objective functions. The suggested solution takes advantage of multi-objective optimization in addition to the fuzzy approach as well as the branch and bound technique, which are implemented at each decision level to develop a generalized Maximization-Minimization model for obtaining the integer satisfactory solution after applying the score and accuracy function in the first phase of the solution methodology to singlevalued Pentagonal Neutrosophic parameters to be converted into an equal crisp form. An illustrative example is demonstrated to validate the proposed solution algorithm.
{"title":"A Multi-Level Multi-Objective Integer Quadratic Programming Problem under Pentagonal Neutrosophic Environment","authors":"N. M. Bekhit, O. E. Emam, Laila Abd Elhamid","doi":"10.26599/fie.2023.9270025","DOIUrl":"https://doi.org/10.26599/fie.2023.9270025","url":null,"abstract":"The aim of this paper is to propose an algorithm to solve and enhance a multi-level multi-objective integer quadratic programming problem (MLMOIQPP) under a single-valued Pentagonal Neutrosophic environment applied to the objective functions. The suggested solution takes advantage of multi-objective optimization in addition to the fuzzy approach as well as the branch and bound technique, which are implemented at each decision level to develop a generalized Maximization-Minimization model for obtaining the integer satisfactory solution after applying the score and accuracy function in the first phase of the solution methodology to singlevalued Pentagonal Neutrosophic parameters to be converted into an equal crisp form. An illustrative example is demonstrated to validate the proposed solution algorithm.","PeriodicalId":37623,"journal":{"name":"Fuzzy Information and Engineering","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135410205","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 : 2023-09-01DOI: 10.26599/fie.2023.9270016
Rupali Komatwar, Manesh Kokare
In recent years, there has been an enormous increase in the volume of malware generation and the classification of malware samples plays a crucial role in building and maintaining security. Hence, there is a need to explore new approaches to overcome the limitations of malware classification such as pre-combustion, peculiarity eradication, and categorization. To overcome these issues, this paper proposes a novel Conglomerate Stratum Model (CSM), which categorizes them into groups and identifies their respective families based on their behavior. Initially, the precombustion process used Triad Seeped Technique (TST) in which the image is first regularized by applying ripples. Secondly, we introduced a Quatrain Layer Method (QLM) to upgrade the robustness of malware image features in peculiarity eradication. Then the specific output of the quatrain layer is given to Acclimatized Patronage Scheme (APS) for categorization, and this process effectively classifies the malware types with greater accuracy. The results demonstrate that our model can achieve 99.41% accuracy in classifying malware samples. Also, the values of sensitivity, precision, negative predictive, and recall are higher than 0.9 with the false-negative rate of 0.04, and the false-positive rate 0.003 proving the model to be optimistic. The experimental comparison demonstrates its superior performance concerning state-of-the-art techniques.
{"title":"Conglomerate Stratum Model for Categorization of Malware Family in Image Processing","authors":"Rupali Komatwar, Manesh Kokare","doi":"10.26599/fie.2023.9270016","DOIUrl":"https://doi.org/10.26599/fie.2023.9270016","url":null,"abstract":"In recent years, there has been an enormous increase in the volume of malware generation and the classification of malware samples plays a crucial role in building and maintaining security. Hence, there is a need to explore new approaches to overcome the limitations of malware classification such as pre-combustion, peculiarity eradication, and categorization. To overcome these issues, this paper proposes a novel Conglomerate Stratum Model (CSM), which categorizes them into groups and identifies their respective families based on their behavior. Initially, the precombustion process used Triad Seeped Technique (TST) in which the image is first regularized by applying ripples. Secondly, we introduced a Quatrain Layer Method (QLM) to upgrade the robustness of malware image features in peculiarity eradication. Then the specific output of the quatrain layer is given to Acclimatized Patronage Scheme (APS) for categorization, and this process effectively classifies the malware types with greater accuracy. The results demonstrate that our model can achieve 99.41% accuracy in classifying malware samples. Also, the values of sensitivity, precision, negative predictive, and recall are higher than 0.9 with the false-negative rate of 0.04, and the false-positive rate 0.003 proving the model to be optimistic. The experimental comparison demonstrates its superior performance concerning state-of-the-art techniques.","PeriodicalId":37623,"journal":{"name":"Fuzzy Information and Engineering","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134917204","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 : 2023-09-01DOI: 10.26599/fie.2023.9270019
Iqra Nawaz, Uzma Ahmad
A directed rough fuzzy graph (DRFG) is a unique and innovative hybrid model because it deals with more complex problems of uncertainty in the presence of incomplete data information or rough universe. A DRFG can be obtained from two given DRFGs by union, Cartesian product and composition. When we study operations for DRFGs with a large number of vertices, the degree of vertices in a DRFG presents a confusing picture. Therefore, a mechanism for determining the degree of vertices for DRFG operations is needed. The main objective of this study is to analyze and investigate the degree of vertices in DRFGs formed by certain operations, which will provide clear explanations of operations on DRFGs and their effects on vertex degrees with examples. In this paper, we find the degree of a vertex in DRFGs formed by these operations in terms of the degree of vertices in the given DRFGs in some special cases. We explain these operations with some examples. In addition, we provide an application to the corporate merger problem to test our approach and obtain an optimal result. We have developed two algorithms to elaborate the procedure for our application. Finally, we created a comparison table comparing our results for Algorithms 1 and 2 for the same enterprise merger network.
{"title":"Certain Concepts in Directed Rough Fuzzy Graphs and Application to Mergers of Companies","authors":"Iqra Nawaz, Uzma Ahmad","doi":"10.26599/fie.2023.9270019","DOIUrl":"https://doi.org/10.26599/fie.2023.9270019","url":null,"abstract":"A directed rough fuzzy graph (DRFG) is a unique and innovative hybrid model because it deals with more complex problems of uncertainty in the presence of incomplete data information or rough universe. A DRFG can be obtained from two given DRFGs by union, Cartesian product and composition. When we study operations for DRFGs with a large number of vertices, the degree of vertices in a DRFG presents a confusing picture. Therefore, a mechanism for determining the degree of vertices for DRFG operations is needed. The main objective of this study is to analyze and investigate the degree of vertices in DRFGs formed by certain operations, which will provide clear explanations of operations on DRFGs and their effects on vertex degrees with examples. In this paper, we find the degree of a vertex in DRFGs formed by these operations in terms of the degree of vertices in the given DRFGs in some special cases. We explain these operations with some examples. In addition, we provide an application to the corporate merger problem to test our approach and obtain an optimal result. We have developed two algorithms to elaborate the procedure for our application. Finally, we created a comparison table comparing our results for Algorithms 1 and 2 for the same enterprise merger network.","PeriodicalId":37623,"journal":{"name":"Fuzzy Information and Engineering","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134915623","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 : 2023-09-01DOI: 10.26599/fie.2023.9270018
Mathavan Priya, Ramasamy Uthayakumar
This work constitutes classical Hutchinson-Barnsley theory on the product intuitionistic fuzzy fractal space with the aid of iterated function system, in which a finite number of intuitionistic fuzzy B-contractions and intuitionistic fuzzy Edelstein contractions are enclosed. A fixed point theorem is exhibited by proving that the Hutchinson-Barnsley operator is an intuitionistic fuzzy B-contraction and intuitionistic fuzzy Edelstein contraction. To show the primary goal of the article, the Hausdorff product intuitionistic fuzzy metric space is constructed, then the notion of product intuitionistic fuzzy metric space on complete and compact spaces in the sense of intuitionistic fuzzy B-contraction and the intuitionistic fuzzy Edelstein contraction are defined.
{"title":"A Study on Hutchinson-Barnsley Theory in Product Intuitionistic Fuzzy Fractal Space","authors":"Mathavan Priya, Ramasamy Uthayakumar","doi":"10.26599/fie.2023.9270018","DOIUrl":"https://doi.org/10.26599/fie.2023.9270018","url":null,"abstract":"This work constitutes classical Hutchinson-Barnsley theory on the product intuitionistic fuzzy fractal space with the aid of iterated function system, in which a finite number of intuitionistic fuzzy <i>B</i>-contractions and intuitionistic fuzzy Edelstein contractions are enclosed. A fixed point theorem is exhibited by proving that the Hutchinson-Barnsley operator is an intuitionistic fuzzy <i>B</i>-contraction and intuitionistic fuzzy Edelstein contraction. To show the primary goal of the article, the Hausdorff product intuitionistic fuzzy metric space is constructed, then the notion of product intuitionistic fuzzy metric space on complete and compact spaces in the sense of intuitionistic fuzzy <i>B</i>-contraction and the intuitionistic fuzzy Edelstein contraction are defined.","PeriodicalId":37623,"journal":{"name":"Fuzzy Information and Engineering","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134917194","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 : 2023-09-01DOI: 10.26599/fie.2023.9270020
Hugo Cruz-Suárez, Raúl Montes-de-Oca, R. Israel Ortega-Gutiérrez
The article concerns a study of infinite-horizon deterministic Markov decision processes (MDPs) for which the fuzzy environment will be presented through considering these MDPs with both fuzzy rewards and fuzzy costs. Specifically, these rewards and costs will be assumed of a suitable trapezoidal type. For both classes of MDPs, i.e., MDPs with fuzzy rewards and MDPs with fuzzy costs, the fuzzy total discounted function will be taken into account as the objective function, and the corresponding optimal decision problems will be considered with respect to the max order of the fuzzy numbers. For each optimal decision problem, the optimal policy and the optimal value function are related and obtained as a solution of a convenient standard MDP (i.e., a standard MDP is an MDP with a non-fuzzy reward function or a non-fuzzy cost function). Moreover, an economic growth model (EGM), a deterministic version of the linear-quadratic model (LQM), and an optimal consumption model (OCM) in order to clarify the theory presented are given, and it is remarked that these models have uncountable state spaces, and the corresponding non-fuzzy version of both the EGM and the OCM has an unbounded reward function, and the corresponding non-fuzzy version of the LQM has an unbounded cost function.
{"title":"Deterministic Discounted Markov Decision Processes with Fuzzy Rewards/Costs","authors":"Hugo Cruz-Suárez, Raúl Montes-de-Oca, R. Israel Ortega-Gutiérrez","doi":"10.26599/fie.2023.9270020","DOIUrl":"https://doi.org/10.26599/fie.2023.9270020","url":null,"abstract":"The article concerns a study of infinite-horizon deterministic Markov decision processes (MDPs) for which the fuzzy environment will be presented through considering these MDPs with both fuzzy rewards and fuzzy costs. Specifically, these rewards and costs will be assumed of a suitable trapezoidal type. For both classes of MDPs, i.e., MDPs with fuzzy rewards and MDPs with fuzzy costs, the fuzzy total discounted function will be taken into account as the objective function, and the corresponding optimal decision problems will be considered with respect to the max order of the fuzzy numbers. For each optimal decision problem, the optimal policy and the optimal value function are related and obtained as a solution of a convenient standard MDP (i.e., a standard MDP is an MDP with a non-fuzzy reward function or a non-fuzzy cost function). Moreover, an economic growth model (EGM), a deterministic version of the linear-quadratic model (LQM), and an optimal consumption model (OCM) in order to clarify the theory presented are given, and it is remarked that these models have uncountable state spaces, and the corresponding non-fuzzy version of both the EGM and the OCM has an unbounded reward function, and the corresponding non-fuzzy version of the LQM has an unbounded cost function.","PeriodicalId":37623,"journal":{"name":"Fuzzy Information and Engineering","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134917205","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 : 2023-09-01DOI: 10.26599/fie.2023.9270021
Nagalakshmi Soma, Grande Suresh Kumar, Ravi Prakash Agarwal, Chao Wang, Madhunapantula Surya Narayana Murty
This paper considers fuzzy boundary value problems associated with second-order fuzzy differential equations under granular differentiability. Using a horizontal membership function, we present the notion of second-order granular differentiability for fuzzy functions. Using the granular differentiability concept, we interpret two kinds of two-point boundary value problems for second-order fuzzy differential equations. Sufficient conditions are established for the existence and uniqueness of solutions to these fuzzy boundary value problems. An algorithm is presented for solving non-linear fuzzy boundary value problems under granular differentiability. We provide one example and two engineering applications to demonstrate the algorithm’s effectiveness and results.
{"title":"Existence and Uniqueness of Solutions for Fuzzy Boundary Value Problems Under Granular Differentiability","authors":"Nagalakshmi Soma, Grande Suresh Kumar, Ravi Prakash Agarwal, Chao Wang, Madhunapantula Surya Narayana Murty","doi":"10.26599/fie.2023.9270021","DOIUrl":"https://doi.org/10.26599/fie.2023.9270021","url":null,"abstract":"This paper considers fuzzy boundary value problems associated with second-order fuzzy differential equations under granular differentiability. Using a horizontal membership function, we present the notion of second-order granular differentiability for fuzzy functions. Using the granular differentiability concept, we interpret two kinds of two-point boundary value problems for second-order fuzzy differential equations. Sufficient conditions are established for the existence and uniqueness of solutions to these fuzzy boundary value problems. An algorithm is presented for solving non-linear fuzzy boundary value problems under granular differentiability. We provide one example and two engineering applications to demonstrate the algorithm’s effectiveness and results.","PeriodicalId":37623,"journal":{"name":"Fuzzy Information and Engineering","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134917197","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 : 2023-09-01DOI: 10.26599/fie.2023.9270017
Xueyan Xu
This paper studies the resolution of the max-min compositional fuzzy relation equation with the constraint of . The solvability and the unique solvability of this constrained fuzzy relation equation are characterized. Furthermore, this paper presents a resolution of it and designs a corresponding tabular method. Finally, a numerical example is provided to illustrate the resolution procedure.
{"title":"Resolution of Fuzzy Relation Equations with Constraints","authors":"Xueyan Xu","doi":"10.26599/fie.2023.9270017","DOIUrl":"https://doi.org/10.26599/fie.2023.9270017","url":null,"abstract":"This paper studies the resolution of the max-min compositional fuzzy relation equation with the constraint of <inline-formula id=\"M1\"> <math id=\"mathml_M1\" display=\"inline\" overflow=\"scroll\"><munderover><mo movablelimits=\"false\">∑</mo><mrow class=\"MJX-TeXAtom-ORD\"><mi>i</mi><mo>=</mo><mn>1</mn></mrow><mi>n</mi></munderover><mrow class=\"MJX-TeXAtom-ORD\"><mrow class=\"MJX-TeXAtom-ORD\"><msub><mi>x</mi><mi>i</mi></msub></mrow></mrow><mo>=</mo><mn>1</mn></math></inline-formula>. The solvability and the unique solvability of this constrained fuzzy relation equation are characterized. Furthermore, this paper presents a resolution of it and designs a corresponding tabular method. Finally, a numerical example is provided to illustrate the resolution procedure.","PeriodicalId":37623,"journal":{"name":"Fuzzy Information and Engineering","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134917200","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 : 2023-06-01DOI: 10.26599/fie.2023.9270010
Eman A. AbuHijleh
{"title":"Complex Hesitant Fuzzy Graph","authors":"Eman A. AbuHijleh","doi":"10.26599/fie.2023.9270010","DOIUrl":"https://doi.org/10.26599/fie.2023.9270010","url":null,"abstract":"","PeriodicalId":37623,"journal":{"name":"Fuzzy Information and Engineering","volume":"75 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79984523","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 : 2023-06-01DOI: 10.26599/fie.2023.9270008
M. Danesh, S. Danesh, A. Maleki, T. Razzaghnia
{"title":"An Adaptive Fuzzy Inference System Model to Analyze Fuzzy Regression with Quadratic Programming and Fuzzy Weights Incorporating Uncertainty in the Observed Data","authors":"M. Danesh, S. Danesh, A. Maleki, T. Razzaghnia","doi":"10.26599/fie.2023.9270008","DOIUrl":"https://doi.org/10.26599/fie.2023.9270008","url":null,"abstract":"","PeriodicalId":37623,"journal":{"name":"Fuzzy Information and Engineering","volume":"1 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79109173","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 : 2023-06-01DOI: 10.26599/fie.2023.9270013
S. Onar, B. A. Ersoy, K. Hila, B. Davvaz
{"title":"T-Fuzzy Subhypernear-Modules","authors":"S. Onar, B. A. Ersoy, K. Hila, B. Davvaz","doi":"10.26599/fie.2023.9270013","DOIUrl":"https://doi.org/10.26599/fie.2023.9270013","url":null,"abstract":"","PeriodicalId":37623,"journal":{"name":"Fuzzy Information and Engineering","volume":"10 1","pages":""},"PeriodicalIF":1.2,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85625590","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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