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explanation tree
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  解释树
     In order to identify fuzzy objects, fuzzy explanation tree of concepts,FET, is presented. Then the paper presents an algorithm, FEBL, to identify object with fuzzy explanation. Finally the operationality of FEBM and FEBL is discussed.
     为了解决模糊概念的识别问题,引入了概念的模糊解释树FET.接着给出了对象的模糊识别算法FEBL.最后讨论了FEBM与FEBL的可操作性.
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  相似匹配句对
     TREE HOUSE
     树屋
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     The Trouble Tree
     烦恼树
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     6) explanation;
     6)解释;
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     Explanation to biennial
     解说双年展
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     A quantitative explanation of the juvenile effects of tree-ring δ~(13) C
     树木年轮δ~(13)C含量幼龄效应的定量化探讨
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  explanation tree
The response is an explanation tree in which the node is assumed to be satisfied.
      
The explanation tree for the tetracycline rule, for example, quickly gets into chemical bonding theory.
      
So, propagating this effect all over the explanation tree is needed to keep the tree consistent with the rule base.
      
In certain situations, these changes will affect the other branches of the explanation tree.
      
An explanation tree is a tree-like structure containing all the updated information the user received so far by asking above three questions.
      


One of the most important problems in AI is the expression of knowledge concepts. Explanation based learning(EBL) is an important topic in AI, but it is not always practical to explain a knowledge concept very strictly. As development of EBL, according to natural process of concepts formation this paper presents a new concept model——fuzzy explanation based model (FEBM). When the explanation predicate set of concept is fuzzy and the truth value of the predicates themselves is fuzzy either, formal expressions...

One of the most important problems in AI is the expression of knowledge concepts. Explanation based learning(EBL) is an important topic in AI, but it is not always practical to explain a knowledge concept very strictly. As development of EBL, according to natural process of concepts formation this paper presents a new concept model——fuzzy explanation based model (FEBM). When the explanation predicate set of concept is fuzzy and the truth value of the predicates themselves is fuzzy either, formal expressions is given to find truth value of “an object belonging to a concept”. In order to identify fuzzy objects, fuzzy explanation tree of concepts,FET, is presented. Then the paper presents an algorithm, FEBL, to identify object with fuzzy explanation. Finally the operationality of FEBM and FEBL is discussed.

作为EBL(ExplanationBasedLearning)的发展,从概念的自然形成过程出发,提出了一种新的概念模型FEBM(FuzzyExplanationBasedModel):当概念的解释谓词集为模糊集以及解释谓词取模糊逻辑值时,给出求概念真值的表达式;为了解决模糊概念的识别问题,引入了概念的模糊解释树FET.接着给出了对象的模糊识别算法FEBL.最后讨论了FEBM与FEBL的可操作性.

 
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