Application of ANNs approach for solving fully fuzzy polynomials system

Reza Novin, M. A. Araghi, M. Amirfakhrian
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Abstract

In processing indecisive or unclear information, the advantages of fuzzy logic and neurocomputing disciplines should be taken into account and combined by fuzzy neural networks. The current research intends to present a fuzzy modeling method using multi-layer fuzzy neural networks for solving a fully fuzzy polynomials system. To clarify the point, it is necessary to inform that a supervised gradient descent-based learning law is employed. The feasibility of the method is examined using computer simulations on a numerical example. The experimental results obtained from the investigation of the proposed method are valid and delivers very good approximation results.
人工神经网络方法在全模糊多项式系统中的应用
在处理不确定或不明确的信息时,应考虑模糊逻辑和神经计算学科的优势,并结合模糊神经网络进行处理。本研究拟提出一种利用多层模糊神经网络求解全模糊多项式系统的模糊建模方法。为了澄清这一点,有必要告知使用了基于监督梯度下降的学习律。通过一个算例的计算机仿真,验证了该方法的可行性。实验结果表明,所提出的方法是有效的,具有很好的近似结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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