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Rule acquisition of three-way semi-concept lattices in formal decision context
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作者 Jie Zhao Renxia Wan +1 位作者 Duoqian Miao Boyang Zhang 《CAAI Transactions on Intelligence Technology》 SCIE EI 2024年第2期333-347,共15页
Three-way concept analysis is an important tool for information processing,and rule acquisition is one of the research hotspots of three-way concept analysis.However,compared with three-way concept lattices,three-way ... Three-way concept analysis is an important tool for information processing,and rule acquisition is one of the research hotspots of three-way concept analysis.However,compared with three-way concept lattices,three-way semi-concept lattices have three-way operators with weaker constraints,which can generate more concepts.In this article,the problem of rule acquisition for three-way semi-concept lattices is discussed in general.The authors construct the finer relation of three-way semi-concept lattices,and propose a method of rule acquisition for three-way semi-concept lattices.The authors also discuss the set of decision rules and the relationships of decision rules among object-induced three-way semi-concept lattices,object-induced three-way concept lattices,classical concept lattices and semi-concept lattices.Finally,examples are provided to illustrate the validity of our conclusions. 展开更多
关键词 finer relation rule acquisition three-way concept analysis three-way semi-concept lattices
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Additive-Multiplicative Fuzzy Neural Network and Its Performance
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作者 翟东海 靳蕃 《Journal of Southwest Jiaotong University(English Edition)》 2003年第1期16-22,共7页
In view of the main weaknesses of current fuzzy neural networks such as low reasoning precision and long training time, an Additive Multiplicative Fuzzy Neural Network (AMFNN) model and its architecture are present... In view of the main weaknesses of current fuzzy neural networks such as low reasoning precision and long training time, an Additive Multiplicative Fuzzy Neural Network (AMFNN) model and its architecture are presented. AMFNN combines additive inference and multiplicative inference into an integral whole, reasonably makes use of their advantages of inference and effectively overcomes their weaknesses when they are used for inference separately. Here, an error back propagation algorithm for AMFNN is presented based on the gradient descent method. Comparisons between the AMFNN and six representative fuzzy inference methods shows that the AMFNN is characterized by higher reasoning precision, wider application scope, stronger generalization capability and easier implementation. 展开更多
关键词 fuzzy inference additive multiplicative fuzzy neural network fuzzy rule acquisition
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An Incremental Rule Acquisition Algorithm Based on Rough Set 被引量:4
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作者 YUHong YANGDa-chun 《The Journal of China Universities of Posts and Telecommunications》 EI CSCD 2005年第1期47-52,共6页
Rough Set is a valid mathematical theory developed in recent years, which hasthe ability to deal with imprecise, uncertain, and vague information. This paper presents a newincremental rule acquisition algorithm based ... Rough Set is a valid mathematical theory developed in recent years, which hasthe ability to deal with imprecise, uncertain, and vague information. This paper presents a newincremental rule acquisition algorithm based on rough set theory. First, the relation of the newinstances with the original rule set is discussed. Then the change law of attribute reduction andvalue reduction are studied when a new instance is added. Follow, a new incremental learningalgorithm for decision tables is presented within the framework of rough set. Finally, the newalgorithm and the classical algorithm are analyzed and compared by theory and experiments. 展开更多
关键词 incremental algorithm rule acquisition rough set theory decision table
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