Incorporation, characterization, and conversion of negative rules into fuzzy inference systems
Incorporation, characterization, and conversion of negative rules into fuzzy inference systems
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DOI：
10.1109/91.919247
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发表时间：
2001-04
期刊：
影响因子：
--
通讯作者：
J. Branson;J. Lilly
中科院分区：
文献类型：
--
作者：
J. Branson;J. Lilly
本文考虑将反例纳入模糊推理系统（FIS）。提出了一种新的去模糊化方法--网点衰减法。这是一个传统的去模糊化的泛化，它能够将否定的例子纳入FIS推理过程。点衰减的几种变化，包括点积衰减（DPA），点最小衰减，和点差衰减（DDA），并纳入重心和中心平均去模糊化。DPA说明了倒立摆控制器，其中有一个负规则添加到其规则库。由于引入负规则的控制面的修改进行了研究。简单的转向控制的机器人在障碍物的存在下，使用DDA的演示。介绍了一种利用逆模将正反混合规则库转换为标准规则库的方法。专家和自动创建的负面规则进行了讨论。
This paper considers the incorporation of negative examples into fuzzy inference systems (FIS). A new method of defuzzification called dot attenuation is presented. This is a generalization of conventional defuzzification that has the ability to incorporate negative examples into the FIS reasoning process. Several variations of dot attenuation including dot product attenuation (DPA), dot minimum attenuation, and dot difference attenuation (DDA), are presented and incorporated into the center of gravity and center average defuzzification. DPA is illustrated with an inverted pendulum controller, which has a negative rule added to its rule base. The modification of the control surface due to the introduction of the negative rule is investigated. Simple steering control of a robot in the presence of obstructions using DDA is demonstrated. A method of conversion from a mixed positive/negative rule base into a standard rule base using modus tollens is introduced. Expert and automated creation of negative rules is discussed.