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Fourier series based automatic generation system and method for multi variable fuzzy systems

机译:基于傅立叶级数的多变量模糊系统自动生成系统及方法

摘要

A method of automatically generating a multi-variable fuzzy inference system using a Fourier series expansion. Sample sets are decomposed into a cluster of sample sets associated with given input variables. Fuzzy rules and membership functions are computed individually for each variable by solving a single input multiple outputs fuzzy system extracted from the set cluster. The resulting fuzzy rules and membership functions are composed and integrated back into the fuzzy system appropriate for the original sample set with a minimal computational cost. In addition, an overall system error can be related to errors at each stage of decomposition and composition, enabling error bounds or accuracy thresholds for each stage to be specified and ensuring the final precision of the resulting fuzzy system on the original sample set.
机译:一种使用傅立叶级数展开自动生成多变量模糊推理系统的方法。样本集被分解为与给定输入变量关联的样本集集群。通过求解从集合中提取的单个输入多输出模糊系统,分别为每个变量计算模糊规则和隶属函数。生成的模糊规则和隶属函数被组合,并以最小的计算成本重新集成到适用于原始样本集的模糊系统中。此外,整体系统误差可能与分解和合成各个阶段的误差有关,从而可以指定每个阶段的误差范围或准确度阈值,并确保最终模糊系统在原始样本集上的最终精度。

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