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FUZZY MOVES USING COMPENSATORY GRANULAR REASONING

机译:利用补偿粒度推理进行模糊运动

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摘要

In this paper, compensatory granular reasoning methods are proposed based on fuzzy logic, neural networks, genetic algorithms, compensatory computing and granular computing. The compensatory operation can be reduced to the relevant general compensatory AND operations which replace the traditional AND operations in the compensatory granular reasoning. Different compensatory AND operations such as fuzzy compensatory AND, neural compensatory AND, genetic compensatory AND, linear compensatory AND, and exponential compensatory AND are defined. The compensatory granular reasoning methods can be used to make more reliable decisions. For example, the compensatory granular reasoning methods can make more fault-tolerant Fuzzy moves in a fuzzy game if a player carefully chooses a reasonable compensatory operation. In the future, different compensatory granular reasoning methods will be used in different decision-making applications.
机译:本文提出了一种基于模糊逻辑,神经网络,遗传算法,补偿计算和粒度计算的补偿粒度推理方法。补偿性操作可以简化为相关的一般性补偿性AND操作,以取代补偿性粒度推理中的传统AND运算。定义了不同的补偿“与”运算,例如模糊补偿“与”,神经补偿“与”,遗传补偿“与”,线性补偿“与”和指数补偿“与”。补偿性粒度推理方法可用于做出更可靠的决策。例如,如果玩家仔细选择合理的补偿性操作,则补偿性粒度推理方法可以在模糊游戏中做出更多的容错模糊动作。将来,将在不同的决策应用程序中使用不同的补偿性粒度推理方法。

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