Residuated lattice is an important non-classical logic algebra, and L-fuzzy rough set based on residuated lattice can describe the information with incompleteness, fuzziness and uncomparativity in information systems....Residuated lattice is an important non-classical logic algebra, and L-fuzzy rough set based on residuated lattice can describe the information with incompleteness, fuzziness and uncomparativity in information systems. In this paper, the representation theorems of L-fuzzy rough sets based on residuated lattice are given. The properties and axiomatic definition of the lower and upper approximarion operators in L-fuzzy rough sets are discussed.展开更多
Rough set theory, proposed by Pawlak in 1982, is a tool for dealing with uncertainty and vagueness aspects of knowledge model. The main idea of rough sets corresponds to the lower and upper approximations based on equ...Rough set theory, proposed by Pawlak in 1982, is a tool for dealing with uncertainty and vagueness aspects of knowledge model. The main idea of rough sets corresponds to the lower and upper approximations based on equivalence relations. This paper studies the rough set and its extension. In our talk, we present a linear algebra approach to rough set and its extension, give an equivalent definition of the lower and upper approximations of rough set based on the characteristic function of sets, and then we explain the lower and upper approximations as the colinear map and linear map of sets, respectively. Finally, we define the rough sets over fuzzy lattices, which cover the rough set and fuzzy rough set,and the independent axiomatic systems are constructed to characterize the lower and upper approximations of rough set over fuzzy lattices,respectively,based on inner and outer products. The axiomatic systems unify the axiomization of Pawlak’s rough sets and fuzzy rough sets.展开更多
There is an intimate correlation between rough set theory and formal concept analysis theory, so rough set approximations can be realized by means of formal concept analysis. For any given multiple valued information ...There is an intimate correlation between rough set theory and formal concept analysis theory, so rough set approximations can be realized by means of formal concept analysis. For any given multiple valued information system, the realization of rough set approximation operation has two major steps, firstly convert the information system from multiple valued one to single valued formal context, secondly realize rough set approximation operations aided by concept lattice, which is equivalent to a query operation under some necessary conditions.展开更多
Fusing the structure feature of interval concept lattice and the actual needs of rough control rules,we have constructed the decision interval concept lattice,further more,we also have built a rules mining model of ro...Fusing the structure feature of interval concept lattice and the actual needs of rough control rules,we have constructed the decision interval concept lattice,further more,we also have built a rules mining model of rough control based on decision interval concept lattice,in order to achieve the optimality between rough control mining cost and control efficiency.Firstly,we have preprocessed the collected original data,so that we can transform it into Boolean formal context form,and then we have constructed the decision interval concept lattice in rough control;secondly,we have established the control rules mining algorithm based on decision interval concept lattice.By analyzing and judging redundant rules,we have formed the rough control association rule base in end.Analysis shows that under the premise of improving the reliability of rules,we have achieved the rough control optimization goal between cost and efficiency.Finally,the model of reservoir scheduling has verified its feasibility and efficiency.展开更多
Many real-life data sets are incomplete,or in different words,are affected by missing attribute values.Three interpretations of missing attribute values are discussed in the paper:lost values(erased values),attribute-...Many real-life data sets are incomplete,or in different words,are affected by missing attribute values.Three interpretations of missing attribute values are discussed in the paper:lost values(erased values),attribute-concept values(such a value may be replaced by any value from the attribute domain restricted to the concept),and "do not care" conditions(a missing attribute value may be replaced by any value from the attribute domain).For incomplete data sets three definitions of lower and upper approximations are discussed.Experiments were conducted on six typical data sets with missing attribute values,using three different interpretations of missing attribute values and the same definition of concept lower and upper approximations.The conclusion is that the best approach to missing attribute values is the lost value type.展开更多
To study the problem of knowledge translation in fuzzy approximation spaces, the concept of rough communication of crisp set in fuzzy approximation spaces is proposed. In a rough communication of crisp set in fuzzy ap...To study the problem of knowledge translation in fuzzy approximation spaces, the concept of rough communication of crisp set in fuzzy approximation spaces is proposed. In a rough communication of crisp set in fuzzy approximation spaces, the problem of uncertainty exists, for each agent has a different language and cannot provide precise communication to each other. By means of some concepts, such as CF rough communication cut, which is a bridge between fuzzy concept and crisp concept, cut analysis of CF rough communication is made, and the relation theorem between CF rough communication and rough communication of crisp concept is obtained. Finally, in order to give an intuitive analysis of the relation between CF rough communication and rough communication of crisp concept, an example is given.展开更多
In this paper, a kind of multi-level formal concept is introduced. Based on the proposed multi-level formal concept,we present a pair of rough fuzzy set approximations within fuzzy formal contexts.By the proposed roug...In this paper, a kind of multi-level formal concept is introduced. Based on the proposed multi-level formal concept,we present a pair of rough fuzzy set approximations within fuzzy formal contexts.By the proposed rough fuzzy set approximations,we can approximate a fuzzy set according to different precision level.We discuss the properties of the proposed approximation operators in detail.展开更多
Solving complex problems by multi-agent systems in distributed environments requires new approximate reasoning methods based on new computing paradigms. One such recently emerging computing paradigm is Granular Comput...Solving complex problems by multi-agent systems in distributed environments requires new approximate reasoning methods based on new computing paradigms. One such recently emerging computing paradigm is Granular Computing(GC). We discuss the Rough-Granular Computing(RGC) approach to modeling of computations in complex adaptive systems and multiagent systems as well as for approximate reasoning about the behavior of such systems. The RGC methods have been successfully applied for solving complex problems in areas such as identification of objects or behavioral patterns by autonomous systems, web mining, and sensor fusion.展开更多
The rapid developments in the fields of telecommunication, sensor data, financial applications, analyzing of data streams, and so on, increase the rate of data arrival, among which the data mining technique is conside...The rapid developments in the fields of telecommunication, sensor data, financial applications, analyzing of data streams, and so on, increase the rate of data arrival, among which the data mining technique is considered a vital process. The data analysis process consists of different tasks, among which the data stream classification approaches face more challenges than the other commonly used techniques. Even though the classification is a continuous process, it requires a design that can adapt the classification model so as to adjust the concept change or the boundary change between the classes. Hence, we design a novel fuzzy classifier known as THRFuzzy to classify new incoming data streams. Rough set theory along with tangential holoentropy function helps in the designing the dynamic classification model. The classification approach uses kernel fuzzy c-means(FCM) clustering for the generation of the rules and tangential holoentropy function to update the membership function. The performance of the proposed THRFuzzy method is verified using three datasets, namely skin segmentation, localization, and breast cancer datasets, and the evaluated metrics, accuracy and time, comparing its performance with HRFuzzy and adaptive k-NN classifiers. The experimental results conclude that THRFuzzy classifier shows better classification results providing a maximum accuracy consuming a minimal time than the existing classifiers.展开更多
基金The National Natural Science Foundation of China (No60474022)
文摘Residuated lattice is an important non-classical logic algebra, and L-fuzzy rough set based on residuated lattice can describe the information with incompleteness, fuzziness and uncomparativity in information systems. In this paper, the representation theorems of L-fuzzy rough sets based on residuated lattice are given. The properties and axiomatic definition of the lower and upper approximarion operators in L-fuzzy rough sets are discussed.
文摘Rough set theory, proposed by Pawlak in 1982, is a tool for dealing with uncertainty and vagueness aspects of knowledge model. The main idea of rough sets corresponds to the lower and upper approximations based on equivalence relations. This paper studies the rough set and its extension. In our talk, we present a linear algebra approach to rough set and its extension, give an equivalent definition of the lower and upper approximations of rough set based on the characteristic function of sets, and then we explain the lower and upper approximations as the colinear map and linear map of sets, respectively. Finally, we define the rough sets over fuzzy lattices, which cover the rough set and fuzzy rough set,and the independent axiomatic systems are constructed to characterize the lower and upper approximations of rough set over fuzzy lattices,respectively,based on inner and outer products. The axiomatic systems unify the axiomization of Pawlak’s rough sets and fuzzy rough sets.
文摘There is an intimate correlation between rough set theory and formal concept analysis theory, so rough set approximations can be realized by means of formal concept analysis. For any given multiple valued information system, the realization of rough set approximation operation has two major steps, firstly convert the information system from multiple valued one to single valued formal context, secondly realize rough set approximation operations aided by concept lattice, which is equivalent to a query operation under some necessary conditions.
文摘Fusing the structure feature of interval concept lattice and the actual needs of rough control rules,we have constructed the decision interval concept lattice,further more,we also have built a rules mining model of rough control based on decision interval concept lattice,in order to achieve the optimality between rough control mining cost and control efficiency.Firstly,we have preprocessed the collected original data,so that we can transform it into Boolean formal context form,and then we have constructed the decision interval concept lattice in rough control;secondly,we have established the control rules mining algorithm based on decision interval concept lattice.By analyzing and judging redundant rules,we have formed the rough control association rule base in end.Analysis shows that under the premise of improving the reliability of rules,we have achieved the rough control optimization goal between cost and efficiency.Finally,the model of reservoir scheduling has verified its feasibility and efficiency.
文摘Many real-life data sets are incomplete,or in different words,are affected by missing attribute values.Three interpretations of missing attribute values are discussed in the paper:lost values(erased values),attribute-concept values(such a value may be replaced by any value from the attribute domain restricted to the concept),and "do not care" conditions(a missing attribute value may be replaced by any value from the attribute domain).For incomplete data sets three definitions of lower and upper approximations are discussed.Experiments were conducted on six typical data sets with missing attribute values,using three different interpretations of missing attribute values and the same definition of concept lower and upper approximations.The conclusion is that the best approach to missing attribute values is the lost value type.
基金supported by the Natural Science Foundation of Shandong Province (Y2006A12)the Scientific Research Development Project of Shandong Provincial Education Department (J06P01)+2 种基金the Science and Technology Foundation of Universityof Jinan (XKY0808 XKY0703)the Doctoral Foundation of University of Jinan (B0633).
文摘To study the problem of knowledge translation in fuzzy approximation spaces, the concept of rough communication of crisp set in fuzzy approximation spaces is proposed. In a rough communication of crisp set in fuzzy approximation spaces, the problem of uncertainty exists, for each agent has a different language and cannot provide precise communication to each other. By means of some concepts, such as CF rough communication cut, which is a bridge between fuzzy concept and crisp concept, cut analysis of CF rough communication is made, and the relation theorem between CF rough communication and rough communication of crisp concept is obtained. Finally, in order to give an intuitive analysis of the relation between CF rough communication and rough communication of crisp concept, an example is given.
文摘In this paper, a kind of multi-level formal concept is introduced. Based on the proposed multi-level formal concept,we present a pair of rough fuzzy set approximations within fuzzy formal contexts.By the proposed rough fuzzy set approximations,we can approximate a fuzzy set according to different precision level.We discuss the properties of the proposed approximation operators in detail.
基金The grant3 T11C 00226 from Min istroyf ScientifiRcesearchand InformationTechnologyoftheRepublicofPoland.
文摘Solving complex problems by multi-agent systems in distributed environments requires new approximate reasoning methods based on new computing paradigms. One such recently emerging computing paradigm is Granular Computing(GC). We discuss the Rough-Granular Computing(RGC) approach to modeling of computations in complex adaptive systems and multiagent systems as well as for approximate reasoning about the behavior of such systems. The RGC methods have been successfully applied for solving complex problems in areas such as identification of objects or behavioral patterns by autonomous systems, web mining, and sensor fusion.
基金supported by proposal No.OSD/BCUD/392/197 Board of Colleges and University Development,Savitribai Phule Pune University,Pune
文摘The rapid developments in the fields of telecommunication, sensor data, financial applications, analyzing of data streams, and so on, increase the rate of data arrival, among which the data mining technique is considered a vital process. The data analysis process consists of different tasks, among which the data stream classification approaches face more challenges than the other commonly used techniques. Even though the classification is a continuous process, it requires a design that can adapt the classification model so as to adjust the concept change or the boundary change between the classes. Hence, we design a novel fuzzy classifier known as THRFuzzy to classify new incoming data streams. Rough set theory along with tangential holoentropy function helps in the designing the dynamic classification model. The classification approach uses kernel fuzzy c-means(FCM) clustering for the generation of the rules and tangential holoentropy function to update the membership function. The performance of the proposed THRFuzzy method is verified using three datasets, namely skin segmentation, localization, and breast cancer datasets, and the evaluated metrics, accuracy and time, comparing its performance with HRFuzzy and adaptive k-NN classifiers. The experimental results conclude that THRFuzzy classifier shows better classification results providing a maximum accuracy consuming a minimal time than the existing classifiers.
基金Supported by the National Natural Science Foundation of China under Grant Nos.6057307470471003(国家自然科学基金)+1 种基金the Natural Science Foundation of Shanxi Province of China under Grant No.2007011040(山西省自然科学基金)the Foundation of Doctoral Program Research of the Ministry of Education of China under Grant No.20050108004(高等学校博士学科点专项科研基金)
