The cross-migrativity can be regarded as the weaker form of the commuting equation, which plays a crucial part in the framework of fuzzy connectives. This paper studies the cross-migrativity of continuous t-conorms ov...The cross-migrativity can be regarded as the weaker form of the commuting equation, which plays a crucial part in the framework of fuzzy connectives. This paper studies the cross-migrativity of continuous t-conorms over Ihimplications. We obtain full characterizations for the cross-migrativity of continuous t-conorms over Ihimplications.展开更多
Dual hesitant fuzzy set （DHFS） is a new generalization of fuzzy set （FS） consisting of two parts （i.e., the membership hesitancy function and the non-membership hesitancy fimction）, which confronts several diffe...Dual hesitant fuzzy set （DHFS） is a new generalization of fuzzy set （FS） consisting of two parts （i.e., the membership hesitancy function and the non-membership hesitancy fimction）, which confronts several different possible values indicating the epistemic degrees whether certainty or uncertainty. It encompasses fuzzy set （FS）, intuitionistic fuzzy set （IFS）, and hesitant fuzzy set （HFS） so that it can handle uncertain information more flexibly in the process of decision making. In this paper, we propose some new operations on dual hesitant fuzzy sets based on Einstein t-eonorm and t-norm, study their properties and relationships and then give some dual hesitant fuzzy aggregation operators, which can be considered as the generalizations of some existing ones under fuzzy, intuitionistic fuzzy and hesitant fuzzy environments. Finally, a decision making algorithm under dual hesitant fuzzy environment is given based on the proposed aggregation operators and a numerical example is used to demonstrate the effectiveness of the method.展开更多
Purpose-Gathering,analyzing and securing electronic data from various digital devices for use in legal or investigative procedures is the key process of computer forensics.Information retrieved from servers,hard drive...Purpose-Gathering,analyzing and securing electronic data from various digital devices for use in legal or investigative procedures is the key process of computer forensics.Information retrieved from servers,hard drives,cellphones,tablets and other devices is all included in this.This article tackles the challenging problem of how to prioritize different kinds of computer forensics and figure out which kind is most useful in cases of cybercrime,fraud,theft of intellectual property,harassment and espionage.Design/methodology/approach-Therefore,we first introduce enhanced versions of Hamacher power aggregation operators(AOs)within the framework of bipolar complex fuzzy(BCF)sets.These include BCF Hamacher power averaging(BCFHPA),BCF Hamacher power-weighted averaging(BCFHPWA),BCF Hamacher power-ordered weighted averaging(BCFHPOWA),BCF Hamacher power geometric(BCFHPG),BCF Hamacher power-weighted geometric(BCFHPWG)and BCF Hamacher power-ordered-weighted geometric(BCFHPOWG)operators.Employing the devised AOs,we devise a technique of decision-making(DM)for dealing with DM dilemmas with the BCF set(BCFS).Findings-We prioritize different types of computer forensic by taking artificial data in a numerical example and getting the finest computer forensic.Further,by this example,we reveal the applicability of the proposed theory.This work provides a more elaborate and versatile procedure for classifying computer forensics with dual aspects of criteria and extra fuzzy information.It allows for better and less biased DM in the more intricate digital investigations,which may lead to better DM and time-saving in real-life forensic scenarios.To demonstrate the significance and impression of the devised operators and techniques of DM,they are compared with existing ones.Originality/value-This research is the first to combine Hamacher and power AOs in BCFS for computer forensics DM.It presents new operators and a DM approach that is not encountered in the existing literature and is specifically designed to deal with the challenges and risks associated with the classification of computer forensics.The framework’s capacity to accommodate bipolar criteria and extra fuzzy information is a major development in the field of digital forensics and decision science.展开更多
Purpose-This research focuses on a very important research question of determining the appropriate feature selection methods for software defect prediction.The study is centered on the creation of a new method that wo...Purpose-This research focuses on a very important research question of determining the appropriate feature selection methods for software defect prediction.The study is centered on the creation of a new method that would enable the identification of both positive and negative selection criteria and the handling of ambiguous information in the decision-making process.Design/methodology/approach-To do so,we develop an improved method by extending the WASPAS assessment in the context of bipolar complex fuzzy sets,which leads to the bipolar complex fuzzy WASPAS method.The approach also uses Einstein operators to increase the accuracy of aggregation and manage complicated decision-making parameters.The methodology is designed for the processing of multi-criteria decision-making problems where criteria have positive and negative polarities as well as other ambiguous information.Findings-It is also shown that the proposed methodology outperforms the traditional weighted sum or product models when assessing feature selection methods.The incorporation of bipolar complex fuzzy sets with WASPAS improves the assessment of selection criteria by taking into account both positive and negative aspects of the criteria,which contributes to more accurate feature selection for software defect prediction.We investigate a case study related to the identification of feature selection techniques for software defect prediction by using the bipolar complex fuzzy WASPAS methodology.We compare the proposed methodology with certain prevailing ones to reveal the supremacy and the requirements of the proposed theory.Originality/value-This research offers the first integrated framework for handling bipolarity and uncertainty in feature selection for software defect prediction.The combination of Einstein operators with bipolar complex fuzzy sets improves the DM process,which will be useful for software engineers and help them select the best feature selection techniques.This work also helps to enhance the overall performance of software defect prediction systems.展开更多
As an generalization of hesitant fuzzy set, interval-valued hesitant fuzzy set and dual hesitant fuzzy set, interval-valued dual hesitant fuzzy set has been proposed and applied in multiple attribute decision making. ...As an generalization of hesitant fuzzy set, interval-valued hesitant fuzzy set and dual hesitant fuzzy set, interval-valued dual hesitant fuzzy set has been proposed and applied in multiple attribute decision making. Hamacher t-norm and t-conorm is an generalization of algebraic and Einstein t-norms and t-conorms. In order to combine interval-valued dual hesitant fuzzy aggregation operators with Hamacher t-norm and t-conorm. We first introduced some new Hamacher operation rules for interval-valued dual hesitant fuzzy elements. Then, several interval-valued dual hesitant fuzzy Hamacher aggregation operators are presented, some desirable properties and their special cases are studied. Further, a new multiple attribute decision making method with these operators is given,and an numerical example is provided to demonstrate that the developed approach is both valid and practical.展开更多
Motivated based on the trigonometric t-norm and t-conorm,the aims of this article are to present the trigonometric t-norm and t-conorm operational laws of SvNNs and then to propose the SvNN trigonometric weighted aver...Motivated based on the trigonometric t-norm and t-conorm,the aims of this article are to present the trigonometric t-norm and t-conorm operational laws of SvNNs and then to propose the SvNN trigonometric weighted average and geometric aggregation operators for the modelling of a multiple criteria decision making(MCDM)technique in an inconsistent and indeterminate circumstance.To realize the aims,this paper first proposes the trigonometric t-norm and t-conorm operational laws of SvNNs,which contain the hybrid operations of the tangent and arctangent functions and the cotangent and inverse cotangent functions,and presents the SvNN trigonometric weighted average and geometric operators and their properties.Next,an MCDM technique is proposed in view of the presented two aggregation operators in the circumstance of SvNNs.In the end,an actual case of the choice issue of slope treatment schemes is provided to indicate the practicability and effectivity of the proposed MCDM technique.展开更多
文摘The cross-migrativity can be regarded as the weaker form of the commuting equation, which plays a crucial part in the framework of fuzzy connectives. This paper studies the cross-migrativity of continuous t-conorms over Ihimplications. We obtain full characterizations for the cross-migrativity of continuous t-conorms over Ihimplications.
文摘Dual hesitant fuzzy set （DHFS） is a new generalization of fuzzy set （FS） consisting of two parts （i.e., the membership hesitancy function and the non-membership hesitancy fimction）, which confronts several different possible values indicating the epistemic degrees whether certainty or uncertainty. It encompasses fuzzy set （FS）, intuitionistic fuzzy set （IFS）, and hesitant fuzzy set （HFS） so that it can handle uncertain information more flexibly in the process of decision making. In this paper, we propose some new operations on dual hesitant fuzzy sets based on Einstein t-eonorm and t-norm, study their properties and relationships and then give some dual hesitant fuzzy aggregation operators, which can be considered as the generalizations of some existing ones under fuzzy, intuitionistic fuzzy and hesitant fuzzy environments. Finally, a decision making algorithm under dual hesitant fuzzy environment is given based on the proposed aggregation operators and a numerical example is used to demonstrate the effectiveness of the method.
基金funded by the Ningbo Natural Science Foundation(No:2023J101).
文摘Purpose-Gathering,analyzing and securing electronic data from various digital devices for use in legal or investigative procedures is the key process of computer forensics.Information retrieved from servers,hard drives,cellphones,tablets and other devices is all included in this.This article tackles the challenging problem of how to prioritize different kinds of computer forensics and figure out which kind is most useful in cases of cybercrime,fraud,theft of intellectual property,harassment and espionage.Design/methodology/approach-Therefore,we first introduce enhanced versions of Hamacher power aggregation operators(AOs)within the framework of bipolar complex fuzzy(BCF)sets.These include BCF Hamacher power averaging(BCFHPA),BCF Hamacher power-weighted averaging(BCFHPWA),BCF Hamacher power-ordered weighted averaging(BCFHPOWA),BCF Hamacher power geometric(BCFHPG),BCF Hamacher power-weighted geometric(BCFHPWG)and BCF Hamacher power-ordered-weighted geometric(BCFHPOWG)operators.Employing the devised AOs,we devise a technique of decision-making(DM)for dealing with DM dilemmas with the BCF set(BCFS).Findings-We prioritize different types of computer forensic by taking artificial data in a numerical example and getting the finest computer forensic.Further,by this example,we reveal the applicability of the proposed theory.This work provides a more elaborate and versatile procedure for classifying computer forensics with dual aspects of criteria and extra fuzzy information.It allows for better and less biased DM in the more intricate digital investigations,which may lead to better DM and time-saving in real-life forensic scenarios.To demonstrate the significance and impression of the devised operators and techniques of DM,they are compared with existing ones.Originality/value-This research is the first to combine Hamacher and power AOs in BCFS for computer forensics DM.It presents new operators and a DM approach that is not encountered in the existing literature and is specifically designed to deal with the challenges and risks associated with the classification of computer forensics.The framework’s capacity to accommodate bipolar criteria and extra fuzzy information is a major development in the field of digital forensics and decision science.
文摘Purpose-This research focuses on a very important research question of determining the appropriate feature selection methods for software defect prediction.The study is centered on the creation of a new method that would enable the identification of both positive and negative selection criteria and the handling of ambiguous information in the decision-making process.Design/methodology/approach-To do so,we develop an improved method by extending the WASPAS assessment in the context of bipolar complex fuzzy sets,which leads to the bipolar complex fuzzy WASPAS method.The approach also uses Einstein operators to increase the accuracy of aggregation and manage complicated decision-making parameters.The methodology is designed for the processing of multi-criteria decision-making problems where criteria have positive and negative polarities as well as other ambiguous information.Findings-It is also shown that the proposed methodology outperforms the traditional weighted sum or product models when assessing feature selection methods.The incorporation of bipolar complex fuzzy sets with WASPAS improves the assessment of selection criteria by taking into account both positive and negative aspects of the criteria,which contributes to more accurate feature selection for software defect prediction.We investigate a case study related to the identification of feature selection techniques for software defect prediction by using the bipolar complex fuzzy WASPAS methodology.We compare the proposed methodology with certain prevailing ones to reveal the supremacy and the requirements of the proposed theory.Originality/value-This research offers the first integrated framework for handling bipolarity and uncertainty in feature selection for software defect prediction.The combination of Einstein operators with bipolar complex fuzzy sets improves the DM process,which will be useful for software engineers and help them select the best feature selection techniques.This work also helps to enhance the overall performance of software defect prediction systems.
基金Supported by the Natural Science Foundation of Higher Education of Jiangsu Province(18KJB110024)the High Training Funded for Professional Leaders of Higher Vocational Colleges in Jiangsu Province(2018GRFX038)Science and Technology Research Project of Nantong Shipping College(HYKY/2018A03)
文摘As an generalization of hesitant fuzzy set, interval-valued hesitant fuzzy set and dual hesitant fuzzy set, interval-valued dual hesitant fuzzy set has been proposed and applied in multiple attribute decision making. Hamacher t-norm and t-conorm is an generalization of algebraic and Einstein t-norms and t-conorms. In order to combine interval-valued dual hesitant fuzzy aggregation operators with Hamacher t-norm and t-conorm. We first introduced some new Hamacher operation rules for interval-valued dual hesitant fuzzy elements. Then, several interval-valued dual hesitant fuzzy Hamacher aggregation operators are presented, some desirable properties and their special cases are studied. Further, a new multiple attribute decision making method with these operators is given,and an numerical example is provided to demonstrate that the developed approach is both valid and practical.
文摘Motivated based on the trigonometric t-norm and t-conorm,the aims of this article are to present the trigonometric t-norm and t-conorm operational laws of SvNNs and then to propose the SvNN trigonometric weighted average and geometric aggregation operators for the modelling of a multiple criteria decision making(MCDM)technique in an inconsistent and indeterminate circumstance.To realize the aims,this paper first proposes the trigonometric t-norm and t-conorm operational laws of SvNNs,which contain the hybrid operations of the tangent and arctangent functions and the cotangent and inverse cotangent functions,and presents the SvNN trigonometric weighted average and geometric operators and their properties.Next,an MCDM technique is proposed in view of the presented two aggregation operators in the circumstance of SvNNs.In the end,an actual case of the choice issue of slope treatment schemes is provided to indicate the practicability and effectivity of the proposed MCDM technique.
