模糊冢本隶属函数在水稻田可行性判断中的比较分析

Ummi Syafiqoh, A. Yudhana, S. Sunardi
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摘要

由梯形、三角形和线形组成的模糊集隶属度曲线的表示在模糊逻辑系统中具有重要作用。曲线形状的选择决定了可用的隶属函数,并影响模糊输出值。先前的研究通常使用先前或其他研究中使用的曲线,这些研究没有解释选择模糊成员曲线的原因。这种情况之所以成为问题,是因为没有为模糊过程中使用的参数选择合适的隶属函数模型的指南,因此大多数研究人员只使用以前研究中常用的或与他们的研究相同的隶属函数。本研究的目的是确定选择梯形和三角形曲线对Tsukamoto模糊逻辑用于确定稻田适宜性状态的性能的影响。研究方法包括三个主要阶段。第一阶段是数据收集,收集稻田中的土壤pH值、土壤湿度和空气温度。第二阶段是Tsukamoto模糊的实现。在这个阶段,使用了两条隶属函数曲线。第三阶段是对Tsukamoto的梯形和三角形曲线的模糊输出进行比较分析。结果表明,两种不同隶属度函数之间没有显著的性能差异。梯形隶属度函数的研究结果具有93%的较好准确率,而三角形隶属度函数具有90%的准确率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparative analysis of Fuzzy Tsukamoto's membership functions for determining irrigated rice field feasibility status
The representation of the fuzzy set membership curve consisting of trapezoidal, triangular, and linear shapes, has an important role in the fuzzy logic system. The selection of the curve's shapes determines the useable membership function and affects the fuzzy output value. Previous studies generally used curves that had been employed in predecessors or other studies that did not explain the reason for choosing a fuzzy member curve. This condition became problem because there was not a guide in selecting the appropriate membership function model for the parameters used in the fuzzy process so that most researchers only use membership functions that are commonly used in previous studies or in the same case as their research. The purpose of this study was to determine the effect of selecting trapezoidal and triangular curves on the performance of Tsukamoto's fuzzy logic for determining the rice-fields suitability status. The research methodology comprised 3 main stages. The first stage was data collecting, to collect soil pH values, soil moisture, and air temperature in rice fields. The second stage was the implementation of the Tsukamoto fuzzy. At this stage, two membership function curves were used. The third stage was a comparative analysis of Tsukamoto's fuzzy's output of trapezoidal and triangular curves. The results obtained indicate that there is no significant performance difference between the two different membership functions. The results of the research with the trapezoidal membership function have a better accuracy rate of 93% while the triangular membership function has an accuracy rate of 90%.
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