This paper explores the defects in fuzzy (hyper) graphs (as complex (hyper) networks) and extends the fuzzy(hyper) graphs to fuzzy (quasi) superhypergraphs as a new concept.We have modeled the fuzzy superhypergraphsas...This paper explores the defects in fuzzy (hyper) graphs (as complex (hyper) networks) and extends the fuzzy(hyper) graphs to fuzzy (quasi) superhypergraphs as a new concept.We have modeled the fuzzy superhypergraphsas complex superhypernetworks in order to make a relation between labeled objects in the form of details andgeneralities. Indeed, the structure of fuzzy (quasi) superhypergraphs collects groups of labeled objects and analyzesthem in the form of the part to part of objects, the part of objects to the whole group of objects, and the whole tothe whole group of objects at the same time.We have investigated the properties of fuzzy (quasi) superhypergraphsbased on any positive real number as valued fuzzy (quasi) superhypergraphs, considering the complement of valuedfuzzy (quasi) superhypergraphs, the notation of isomorphism of valued fuzzy (quasi) superhypergraphs based onthe permutations, and we have presented the isomorphic conditions of (self complemented) valued fuzzy (quasi)superhypergraphs. The concept of impact membership value of fuzzy (quasi) superhypergraphs is introducedin this study and it is applied in designing the real problem in the real world. Finally, the problem of businesssuperhypernetworks is presented as an application of fuzzy valued quasi superhypergraphs in the real world.展开更多
Clustering is a crucial method for deciphering data structure and producing new information.Due to its significance in revealing fundamental connections between the human brain and events,it is essential to utilize cl...Clustering is a crucial method for deciphering data structure and producing new information.Due to its significance in revealing fundamental connections between the human brain and events,it is essential to utilize clustering for cognitive research.Dealing with noisy data caused by inaccurate synthesis from several sources or misleading data production processes is one of the most intriguing clustering difficulties.Noisy data can lead to incorrect object recognition and inference.This research aims to innovate a novel clustering approach,named Picture-Neutrosophic Trusted Safe Semi-Supervised Fuzzy Clustering(PNTS3FCM),to solve the clustering problem with noisy data using neutral and refusal degrees in the definition of Picture Fuzzy Set(PFS)and Neutrosophic Set(NS).Our contribution is to propose a new optimization model with four essential components:clustering,outlier removal,safe semi-supervised fuzzy clustering and partitioning with labeled and unlabeled data.The effectiveness and flexibility of the proposed technique are estimated and compared with the state-of-art methods,standard Picture fuzzy clustering(FC-PFS)and Confidence-weighted safe semi-supervised clustering(CS3FCM)on benchmark UCI datasets.The experimental results show that our method is better at least 10/15 datasets than the compared methods in terms of clustering quality and computational time.展开更多
Recently,research on uncertainty modeling has been progressing rapidly,and many essential and breakthrough studies have already been done.There are various ways to handle these uncertainties,such as fuzzy and intuitio...Recently,research on uncertainty modeling has been progressing rapidly,and many essential and breakthrough studies have already been done.There are various ways to handle these uncertainties,such as fuzzy and intuitionistic fuzzy sets.Although these concepts can take incomplete information in various real-world issues,they cannot address all types of uncertainty,such as indeterminate and inconsistent information.The neutrosophic theory founded by Florentin Smarandache in 1998 constitutes a further generalization of fuzzy set,intuitionistic fuzzy set,picture fuzzy set,Pythagorean fuzzy set,spherical fuzzy set,etc.Since then,this logic has been applied in various science and engineering domains.展开更多
Raw data are classified using clustering techniques in a reasonable manner to create disjoint clusters.A lot of clustering algorithms based on specific parameters have been proposed to access a high volume of datasets...Raw data are classified using clustering techniques in a reasonable manner to create disjoint clusters.A lot of clustering algorithms based on specific parameters have been proposed to access a high volume of datasets.This paper focuses on cluster analysis based on neutrosophic set implication,i.e.,a k-means algorithm with a threshold-based clustering technique.This algorithm addresses the shortcomings of the k-means clustering algorithm by overcoming the limitations of the threshold-based clustering algorithm.To evaluate the validity of the proposed method,several validity measures and validity indices are applied to the Iris dataset(from the University of California,Irvine,Machine Learning Repository)along with k-means and threshold-based clustering algorithms.The proposed method results in more segregated datasets with compacted clusters,thus achieving higher validity indices.The method also eliminates the limitations of threshold-based clustering algorithm and validates measures and respective indices along with k-means and threshold-based clustering algorithms.展开更多
This article aims to present new terms of single-valued neutrosophic notions in theˇSostak sense,known as singlevalued neutrosophic regularity spaces.Concepts such as r-single-valued neutrosophic semi￡-open,r-single...This article aims to present new terms of single-valued neutrosophic notions in theˇSostak sense,known as singlevalued neutrosophic regularity spaces.Concepts such as r-single-valued neutrosophic semi￡-open,r-single-valued neutrosophic pre-￡-open,r-single valued neutrosophic regular-￡-open and r-single valued neutrosophicα￡-open are defined and their properties are studied as well as the relationship between them.Moreover,we introduce the concept of r-single valued neutrosophicθ￡-cluster point and r-single-valued neutrosophicγ￡-cluster point,r-θ￡-closed,andθ￡-closure operators and study some of their properties.Also,we present and investigate the notions of r-single-valued neutrosophicθ￡-connectedness and r-single valued neutrosophicδ￡-connectedness and investigate relationship with single-valued neutrosophic almost￡-regular.We compare all these forms of connectedness and investigate their properties in single-valued neutrosophic semiregular and single-valued neutrosophic almost regular in neutrosophic ideal topological spaces inˇSostak sense.The usefulness of these concepts are incorporated to multiple attribute groups of comparison within the connectedness and separateness ofθ￡andδ￡.展开更多
Fuzzy models are present everywhere from natural to artificial structures,embodying the dynamic processes in physical,biological,and social systems.As real-life problems are often uncertain on account of inconsistent ...Fuzzy models are present everywhere from natural to artificial structures,embodying the dynamic processes in physical,biological,and social systems.As real-life problems are often uncertain on account of inconsistent and indeterminate information,it seems very demanding for an expert to solve those problems using a fuzzy model.In this regard,we develop a hybrid new model m-polar Diophantine neutrosophic N-soft set which is based on neutrosophic set and soft set.Additionally,we define several different sorts of compliments on the proposed set.A proposed set is a generalized form of fuzzy,soft,Pythagorean fuzzy,Pythagorean fuzzy soft,and Pythagorean fuzzy N-soft sets.In thismanner,m-polar Diophantine neutrosophic N-soft set is more proficient,a versatile model to oversee vulnerabilities as it likewise survives the downsides of existing models which are to be summed up.Furthermore,we give the application of the proposed set in multi-attribute decision-making problems by defining a new choice-value function.展开更多
In this study,the Five Facet Mindfulness Questionnaire which was adapted from the short form of the Five Facet Mindfulness Questionnaire was evaluated and this scale into neutrosophic form was converted and the result...In this study,the Five Facet Mindfulness Questionnaire which was adapted from the short form of the Five Facet Mindfulness Questionnaire was evaluated and this scale into neutrosophic form was converted and the results of the scale were compared for proposing new type confirmatory analysis procedure as well as developing neutrosophic scales.The exploratory factor analysis was used in the analysis of the data.Besides,test results were analyzed for Kaiser–Meyer–Olkin and Bartlett values,common factor variance values,scree plot graphs,and the principal component analysis results.The sample of the study consists of 194 students in mathematics departments at Bitlis Eren University and Igdır University in Turkey by convenience sampling method.A convenience sampling is a kind˘of non-probability sampling procedure in which the sample is obtained from a group of individuals easily accessible or reachable.The convenience sampling method was chosen in this study because the study aims to examine the structure of the measurement tool rather than the psychological characteristics of a particular population.First of all,it is observed that if any classical scale can be converted into a neutrosophic one.It is observed that the sub-dimensions of a neutrosophic scale as agree,disagree,and undecided might not have a similar factor structure to the classical one.Interestingly,in the factor analysis of the neutrosophic scale,both classical and the agreement part of the neutrosophic scales have the same factors,implying that the one-dimensional classical scale measures the agreement degree of the participants.When the factor analysis was conducted to disagreement and vagueness dimensions,it seemed that some factors were eliminated and even some new factors emerged,indicating that in human cognition those three dimensions can be taken as independent of each other,just as assumed by neutrosophic logic.The another important implication of the factor analysis is that the neutrosophic forms of any questionnaire can be used for the validity of the classical ones.Loads of items or their accumulation into factors are compared to the classical scale and the three-dimensional neutrosophic scale in the factor,so that the corresponding ones in the same factors and the items or factors that do not correspond to each other are eliminated.It is very similar to the Sieve of Eratosthenes,which is an ancient algorithm for finding prime numbers up to any given limit where each prime is taken as an independent base or dimension and multiples of the selected primes in a given interval are eliminated until there are only prime numbers left.Finally,the reliability of three independent dimensions of the neutrosophic forms of any questionnaire can also be used to check whether the measurement This work is licensed under a Creative Commons Attribution 4.0 International License,which permits unrestricted use,distribution,and reproduction in any medium,provided the original work is properly cited.954 CMES,2021,vol.129,no.2 tool is reliable.Low-reliability results in any dimensions may imply that the scale has some problems in terms of meaning,language,or other factors.展开更多
Supplier selection is a common and relevant phase to initialize the supply chain processes and ensure its sustainability.The choice of supplier is a multicriteria decision making(MCDM)to obtain the optimal decision ba...Supplier selection is a common and relevant phase to initialize the supply chain processes and ensure its sustainability.The choice of supplier is a multicriteria decision making(MCDM)to obtain the optimal decision based on a group of criteria.The health care sector faces several types of problems,and one of the most important is selecting an appropriate supplier that fits the desired performance level.The development of service/product quality in health care facilities in a country will improve the quality of the life of its population.This paper proposes an integrated multi-attribute border approximation area comparison(MABAC)based on the best-worst method(BWM),plithogenic set,and rough numbers.BWM is applied to regulate the weight vector of the measures in group decision-making problems with a high level of consistency.For the treatment of uncertainty,a plithogenic set and rough number(RN)are used to improve the accuracy of results.Plithogenic set operations are used to deal with information in the desired manner that handles uncertainty and vagueness.Then,based on the plithogenic aggregation and the results of BWM evaluation,we use MABAC to find the optimal alternative according to defined criteria.To examine the proposed integrated algorithm,an empirical example is produced to select an optimal supplier within five options in the healthcare industry.展开更多
In this paper,we introduce a neutrosophic N-subalgebra,a(ultra)neutrosophic N-filter,level sets of these neutrosophic N-structures and their properties on a Sheffer stroke BL-algebra.By defining a quasi-subalgebra of ...In this paper,we introduce a neutrosophic N-subalgebra,a(ultra)neutrosophic N-filter,level sets of these neutrosophic N-structures and their properties on a Sheffer stroke BL-algebra.By defining a quasi-subalgebra of a Sheffer stroke BL-algebra,it is proved that the level set of neutrosophic N-subalgebras on the algebraic structure is its quasi-subalgebra and vice versa.Then we show that the family of all neutrosophic N-subalgebras of a Sheffer stroke BL-algebra forms a complete distributive lattice.After that a(ultra)neutrosophic N-filter of a Sheffer stroke BL-algebra is described,we demonstrate that every neutrosophic N-filter of a Sheffer stroke BL-algebra is its neutrosophic N-subalgebra but the inverse is generally not true.Finally,it is presented that a level set of a(ultra)neutrosophic N-filter of a Sheffer stroke BL-algebra is also its(ultra)filter and the inverse is always true.Moreover,some features of neutrosophic N-structures on a Sheffer stroke BL-algebra are investigated.展开更多
The shortest path problem has been one of the most fundamental practical problems in network analysis.One of the good algorithms is Bellman-Ford,which has been applied in network,for the last some years.Due to complex...The shortest path problem has been one of the most fundamental practical problems in network analysis.One of the good algorithms is Bellman-Ford,which has been applied in network,for the last some years.Due to complexity in the decision-making process,the decision makers face complications to express their view and judgment with an exact number for single valued membership degrees under neutrosophic environment.Though the interval number is a special situation of the neutrosophic,it did not solve the shortest path problems in an absolute manner.Hence,in this work,the authors have introduced the score function and accuracy function of trapezoidal interval valued neutrosophic numbers with their illustrative properties.These properties provide important theoretical base of the trapezoidal interval valued neutrosophic number.Also,they proposed an intelligent algorithm called trapezoidal interval valued neutrosophic version of Bellman’s algorithm to solve neutrosophic shortest path problem in network analysis.Further,comparative analysis has been made with the existing algorithm.展开更多
Modern systems for information retrieval, fusion and management need to deal more and more with information coming from human experts usually expressed qualitatively in natural language with linguistic labels. In this...Modern systems for information retrieval, fusion and management need to deal more and more with information coming from human experts usually expressed qualitatively in natural language with linguistic labels. In this paper, we propose and use two new 2-Tuple linguistic representation models （i.e., a distribution function model （DFM） and an improved Herrera-Martinez＇s model） jointly with the fusion rules developed in Dezert-Smarandache Theory （DSmT）, in order to combine efficiently qualitative information expressed in term of qualitative belief functions. The two models both preserve the precision and improve the efficiency of the fusion of linguistic information expressing the global expert＇s opinion. However, DFM is more general and efficient than the latter, especially for unbalanced linguistic labels. Some simple examples are also provided to show how the 2-Tuple qualitative fusion rules are performed and their advantages.展开更多
文摘This paper explores the defects in fuzzy (hyper) graphs (as complex (hyper) networks) and extends the fuzzy(hyper) graphs to fuzzy (quasi) superhypergraphs as a new concept.We have modeled the fuzzy superhypergraphsas complex superhypernetworks in order to make a relation between labeled objects in the form of details andgeneralities. Indeed, the structure of fuzzy (quasi) superhypergraphs collects groups of labeled objects and analyzesthem in the form of the part to part of objects, the part of objects to the whole group of objects, and the whole tothe whole group of objects at the same time.We have investigated the properties of fuzzy (quasi) superhypergraphsbased on any positive real number as valued fuzzy (quasi) superhypergraphs, considering the complement of valuedfuzzy (quasi) superhypergraphs, the notation of isomorphism of valued fuzzy (quasi) superhypergraphs based onthe permutations, and we have presented the isomorphic conditions of (self complemented) valued fuzzy (quasi)superhypergraphs. The concept of impact membership value of fuzzy (quasi) superhypergraphs is introducedin this study and it is applied in designing the real problem in the real world. Finally, the problem of businesssuperhypernetworks is presented as an application of fuzzy valued quasi superhypergraphs in the real world.
基金This research is funded by Graduate University of Science and Technology under grant number GUST.STS.DT2020-TT01。
文摘Clustering is a crucial method for deciphering data structure and producing new information.Due to its significance in revealing fundamental connections between the human brain and events,it is essential to utilize clustering for cognitive research.Dealing with noisy data caused by inaccurate synthesis from several sources or misleading data production processes is one of the most intriguing clustering difficulties.Noisy data can lead to incorrect object recognition and inference.This research aims to innovate a novel clustering approach,named Picture-Neutrosophic Trusted Safe Semi-Supervised Fuzzy Clustering(PNTS3FCM),to solve the clustering problem with noisy data using neutral and refusal degrees in the definition of Picture Fuzzy Set(PFS)and Neutrosophic Set(NS).Our contribution is to propose a new optimization model with four essential components:clustering,outlier removal,safe semi-supervised fuzzy clustering and partitioning with labeled and unlabeled data.The effectiveness and flexibility of the proposed technique are estimated and compared with the state-of-art methods,standard Picture fuzzy clustering(FC-PFS)and Confidence-weighted safe semi-supervised clustering(CS3FCM)on benchmark UCI datasets.The experimental results show that our method is better at least 10/15 datasets than the compared methods in terms of clustering quality and computational time.
文摘Recently,research on uncertainty modeling has been progressing rapidly,and many essential and breakthrough studies have already been done.There are various ways to handle these uncertainties,such as fuzzy and intuitionistic fuzzy sets.Although these concepts can take incomplete information in various real-world issues,they cannot address all types of uncertainty,such as indeterminate and inconsistent information.The neutrosophic theory founded by Florentin Smarandache in 1998 constitutes a further generalization of fuzzy set,intuitionistic fuzzy set,picture fuzzy set,Pythagorean fuzzy set,spherical fuzzy set,etc.Since then,this logic has been applied in various science and engineering domains.
文摘Raw data are classified using clustering techniques in a reasonable manner to create disjoint clusters.A lot of clustering algorithms based on specific parameters have been proposed to access a high volume of datasets.This paper focuses on cluster analysis based on neutrosophic set implication,i.e.,a k-means algorithm with a threshold-based clustering technique.This algorithm addresses the shortcomings of the k-means clustering algorithm by overcoming the limitations of the threshold-based clustering algorithm.To evaluate the validity of the proposed method,several validity measures and validity indices are applied to the Iris dataset(from the University of California,Irvine,Machine Learning Repository)along with k-means and threshold-based clustering algorithms.The proposed method results in more segregated datasets with compacted clusters,thus achieving higher validity indices.The method also eliminates the limitations of threshold-based clustering algorithm and validates measures and respective indices along with k-means and threshold-based clustering algorithms.
文摘This article aims to present new terms of single-valued neutrosophic notions in theˇSostak sense,known as singlevalued neutrosophic regularity spaces.Concepts such as r-single-valued neutrosophic semi￡-open,r-single-valued neutrosophic pre-￡-open,r-single valued neutrosophic regular-￡-open and r-single valued neutrosophicα￡-open are defined and their properties are studied as well as the relationship between them.Moreover,we introduce the concept of r-single valued neutrosophicθ￡-cluster point and r-single-valued neutrosophicγ￡-cluster point,r-θ￡-closed,andθ￡-closure operators and study some of their properties.Also,we present and investigate the notions of r-single-valued neutrosophicθ￡-connectedness and r-single valued neutrosophicδ￡-connectedness and investigate relationship with single-valued neutrosophic almost￡-regular.We compare all these forms of connectedness and investigate their properties in single-valued neutrosophic semiregular and single-valued neutrosophic almost regular in neutrosophic ideal topological spaces inˇSostak sense.The usefulness of these concepts are incorporated to multiple attribute groups of comparison within the connectedness and separateness ofθ￡andδ￡.
基金the Social Sciences Planning Projects of Zhejiang(21QNYC11ZD)Major Humanities and Social Sciences Research Projects in Zhejiang Universities(2018QN058)+1 种基金Fundamental Research Funds for the Provincial Universities of Zhejiang(SJWZ2020002)Longyuan Construction Financial Research Project of Ningbo University(LYYB2002).
文摘Fuzzy models are present everywhere from natural to artificial structures,embodying the dynamic processes in physical,biological,and social systems.As real-life problems are often uncertain on account of inconsistent and indeterminate information,it seems very demanding for an expert to solve those problems using a fuzzy model.In this regard,we develop a hybrid new model m-polar Diophantine neutrosophic N-soft set which is based on neutrosophic set and soft set.Additionally,we define several different sorts of compliments on the proposed set.A proposed set is a generalized form of fuzzy,soft,Pythagorean fuzzy,Pythagorean fuzzy soft,and Pythagorean fuzzy N-soft sets.In thismanner,m-polar Diophantine neutrosophic N-soft set is more proficient,a versatile model to oversee vulnerabilities as it likewise survives the downsides of existing models which are to be summed up.Furthermore,we give the application of the proposed set in multi-attribute decision-making problems by defining a new choice-value function.
文摘In this study,the Five Facet Mindfulness Questionnaire which was adapted from the short form of the Five Facet Mindfulness Questionnaire was evaluated and this scale into neutrosophic form was converted and the results of the scale were compared for proposing new type confirmatory analysis procedure as well as developing neutrosophic scales.The exploratory factor analysis was used in the analysis of the data.Besides,test results were analyzed for Kaiser–Meyer–Olkin and Bartlett values,common factor variance values,scree plot graphs,and the principal component analysis results.The sample of the study consists of 194 students in mathematics departments at Bitlis Eren University and Igdır University in Turkey by convenience sampling method.A convenience sampling is a kind˘of non-probability sampling procedure in which the sample is obtained from a group of individuals easily accessible or reachable.The convenience sampling method was chosen in this study because the study aims to examine the structure of the measurement tool rather than the psychological characteristics of a particular population.First of all,it is observed that if any classical scale can be converted into a neutrosophic one.It is observed that the sub-dimensions of a neutrosophic scale as agree,disagree,and undecided might not have a similar factor structure to the classical one.Interestingly,in the factor analysis of the neutrosophic scale,both classical and the agreement part of the neutrosophic scales have the same factors,implying that the one-dimensional classical scale measures the agreement degree of the participants.When the factor analysis was conducted to disagreement and vagueness dimensions,it seemed that some factors were eliminated and even some new factors emerged,indicating that in human cognition those three dimensions can be taken as independent of each other,just as assumed by neutrosophic logic.The another important implication of the factor analysis is that the neutrosophic forms of any questionnaire can be used for the validity of the classical ones.Loads of items or their accumulation into factors are compared to the classical scale and the three-dimensional neutrosophic scale in the factor,so that the corresponding ones in the same factors and the items or factors that do not correspond to each other are eliminated.It is very similar to the Sieve of Eratosthenes,which is an ancient algorithm for finding prime numbers up to any given limit where each prime is taken as an independent base or dimension and multiples of the selected primes in a given interval are eliminated until there are only prime numbers left.Finally,the reliability of three independent dimensions of the neutrosophic forms of any questionnaire can also be used to check whether the measurement This work is licensed under a Creative Commons Attribution 4.0 International License,which permits unrestricted use,distribution,and reproduction in any medium,provided the original work is properly cited.954 CMES,2021,vol.129,no.2 tool is reliable.Low-reliability results in any dimensions may imply that the scale has some problems in terms of meaning,language,or other factors.
文摘Supplier selection is a common and relevant phase to initialize the supply chain processes and ensure its sustainability.The choice of supplier is a multicriteria decision making(MCDM)to obtain the optimal decision based on a group of criteria.The health care sector faces several types of problems,and one of the most important is selecting an appropriate supplier that fits the desired performance level.The development of service/product quality in health care facilities in a country will improve the quality of the life of its population.This paper proposes an integrated multi-attribute border approximation area comparison(MABAC)based on the best-worst method(BWM),plithogenic set,and rough numbers.BWM is applied to regulate the weight vector of the measures in group decision-making problems with a high level of consistency.For the treatment of uncertainty,a plithogenic set and rough number(RN)are used to improve the accuracy of results.Plithogenic set operations are used to deal with information in the desired manner that handles uncertainty and vagueness.Then,based on the plithogenic aggregation and the results of BWM evaluation,we use MABAC to find the optimal alternative according to defined criteria.To examine the proposed integrated algorithm,an empirical example is produced to select an optimal supplier within five options in the healthcare industry.
文摘In this paper,we introduce a neutrosophic N-subalgebra,a(ultra)neutrosophic N-filter,level sets of these neutrosophic N-structures and their properties on a Sheffer stroke BL-algebra.By defining a quasi-subalgebra of a Sheffer stroke BL-algebra,it is proved that the level set of neutrosophic N-subalgebras on the algebraic structure is its quasi-subalgebra and vice versa.Then we show that the family of all neutrosophic N-subalgebras of a Sheffer stroke BL-algebra forms a complete distributive lattice.After that a(ultra)neutrosophic N-filter of a Sheffer stroke BL-algebra is described,we demonstrate that every neutrosophic N-filter of a Sheffer stroke BL-algebra is its neutrosophic N-subalgebra but the inverse is generally not true.Finally,it is presented that a level set of a(ultra)neutrosophic N-filter of a Sheffer stroke BL-algebra is also its(ultra)filter and the inverse is always true.Moreover,some features of neutrosophic N-structures on a Sheffer stroke BL-algebra are investigated.
文摘The shortest path problem has been one of the most fundamental practical problems in network analysis.One of the good algorithms is Bellman-Ford,which has been applied in network,for the last some years.Due to complexity in the decision-making process,the decision makers face complications to express their view and judgment with an exact number for single valued membership degrees under neutrosophic environment.Though the interval number is a special situation of the neutrosophic,it did not solve the shortest path problems in an absolute manner.Hence,in this work,the authors have introduced the score function and accuracy function of trapezoidal interval valued neutrosophic numbers with their illustrative properties.These properties provide important theoretical base of the trapezoidal interval valued neutrosophic number.Also,they proposed an intelligent algorithm called trapezoidal interval valued neutrosophic version of Bellman’s algorithm to solve neutrosophic shortest path problem in network analysis.Further,comparative analysis has been made with the existing algorithm.
基金supported by the National Natural Science Foundation of China under Grant No.60804063supported by the National Natural Science Foundation of China under GrantNo.60804063one subproject of Jiangsu Province Science and Technology Transformation Project under Grant No.B3A2007058
文摘Modern systems for information retrieval, fusion and management need to deal more and more with information coming from human experts usually expressed qualitatively in natural language with linguistic labels. In this paper, we propose and use two new 2-Tuple linguistic representation models （i.e., a distribution function model （DFM） and an improved Herrera-Martinez＇s model） jointly with the fusion rules developed in Dezert-Smarandache Theory （DSmT）, in order to combine efficiently qualitative information expressed in term of qualitative belief functions. The two models both preserve the precision and improve the efficiency of the fusion of linguistic information expressing the global expert＇s opinion. However, DFM is more general and efficient than the latter, especially for unbalanced linguistic labels. Some simple examples are also provided to show how the 2-Tuple qualitative fusion rules are performed and their advantages.
