An adaptive rule extraction with the fuzzy self-organizing map and a comparison with other methods

T. Nomura, T. Miyoshi
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引用次数: 17

Abstract

For automatic rule extraction from a set of input-output data examples, decision tree generating methods such as ID3 and fuzzy ID3 play a major role. These methods, however, are difficult to apply when there is a tendency for the examples to change dynamically. This paper presents a new method for adaptive rule extraction with the fuzzy self-organizing map and the results of simulations in order to present its effectiveness by a comparison with other methods such as RBF (radial basis functions) and GA (genetic algorithms). We obtained the result that our method is superior to other methods for automatic and adaptive rule extraction.
一种基于模糊自组织映射的自适应规则提取方法,并与其他方法进行了比较
为了从一组输入输出数据示例中自动提取规则,ID3和模糊ID3等决策树生成方法发挥了主要作用。然而,当实例有动态变化的趋势时,这些方法很难应用。本文提出了一种基于模糊自组织映射的自适应规则提取方法,并通过仿真结果与径向基函数和遗传算法进行了比较,证明了该方法的有效性。结果表明,该方法在自动自适应规则提取方面优于其他方法。
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