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Fuzzy inference method using the similarity of observation data and conditional part of rule base
Fuzzy inference method using the similarity of observation data and conditional part of rule base
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机译：利用观测数据与规则库条件部分相似度的模糊推理方法
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摘要
The present invention relates to a fuzzy inference method, and more particularly, to a fuzzy inference method using a similarity of observation data and a condition part of a rule base. A fuzzy inference method according to the present invention comprises a first step of measuring a fitness of each condition part of a rule base and an observation data by applying a maximum-minimum synthesis center method; A second step of measuring similarity between each condition part of the rule base and the observation data; A third step of calculating a degree of combination for each conclusion part of the rule base by multiplying the degree of similarity calculated in the first step and the degree of similarity measured in the second step, respectively; And a fourth step of calculating a non-fuzzy value by applying a maximum-minimum synthesis center method to the combination degree obtained in the third step and a plurality of concluding parts. Therefore, the present invention is effective in reducing the calculation time by measuring only the similarity between the observation data and each rule, and then combining only the conclusions that are equal to or greater than the average similarity. In addition, it can be applied to fuzzy reasoning of observation data and each rule, so that more accurate control can be achieved.
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