| 模糊规则的表示方法研究 |
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| 引用本文： | 张博锋,吴耿锋.模糊规则的表示方法研究[J].上海大学学报(英文版),2001,4(Z1). |
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| 作者姓名： | 张博锋 吴耿锋 |
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| 作者单位： | 1. 上海大学 计算机工程与科学学院，上海 200072
2. 上海大学 计算机工程与科学学院, |
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| 摘 要： | 在已有的各种推理方法中，所使用的产生式规则表示形式都不统一，其中含有的信息量也不一样，有的少，有的多，各有侧重
点，但都不全面，因而不能把它们作为模糊知识的统一表示形式.其根本的原因就是推理模型本身不完备.本文描述的通用模糊规
则，是建立在通用不确定模型和模糊集合理论的基础之上的知识统一表示形式，也是通用模糊推理算法的基础.这种方法采用可
能性分布理论来表示知识的模糊性，对一般规则表示进行全面的模糊化，全面考虑了知识的模糊性.它含有推理所需的丰富信息，
能用于表达各种情况的模糊性，有着广泛的适用性.已有的规则形式，如确定性知识的规则表示等，只是这种通用形式在忽略部分
模糊性情况下的特例.这种表示方法在飞机总体外形设计模糊专家系统(ACDS-FES)中得到了很好的运用.
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| 关 键 词： | 模糊推理 多阈值 加权因子 可能性分布 |
Research on Fuzzy Rule Representation |
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| ZHANG Bo-feng,WU Geng-feng.Research on Fuzzy Rule Representation[J].Journal of Shanghai University(English Edition),2001,4(Z1). |
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| Authors: | ZHANG Bo-feng WU Geng-feng |
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| Abstract: | The representing forms of the product rules, which are used in the various existing reasoning methods, are inconsistent, and
the information they contain is distinct. Unfortunately, none of them are all-sided and perfect, so they can not be regarded as the
uniform representing form of fuzzy knowledge. The essential reason causing these cases is that the reasoning models they based on are
not mature. Based on the fuzzy theory and the generalized uncertainty reasoning model (a self-contained reasoning model), the
generalized fuzzy rule representation is proposed in this paper as the base of the generalized fuzzy reasoning algorithm. In this method,
the fuzziness of knowledge is expressed using the possibility distribution theory by completely fuzzificating the normal rules and
completely considering the whole fuzziness of knowledge. The representation containing plentiful information required by reasoning
can represent various fuzziness and has an extensive applicability. The existing forms of rules only are the special cases of the
generalized fuzzy rule representation, when ignoring parts of fuzziness. The representation was applied in fuzzy expert system for
aircraft configuration design system (ACDS-FES); and this shows that it has a good ability of representing fuzzy knowledge. |
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