A New BP Neural Network Model Based on the Random Fuzzy Theory

Yujuan Sun, Yilei Wang, Tao Li, Peng Liu
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引用次数: 2

Abstract

The field of neural networks can be thought of as being related to artificial intelligence, machine learning, parallel processing, statistics, and other fields. The attraction of neural networks is that they are best suited to solving the problems that are the most difficult to solve by traditional computational methods. In this paper, the author first stated the importance and the application of the neural network and then puts the emphasis on presenting the BP neural network that is widely used in many fields. In the second part, the author recommends the random fuzzy theory and gives some useful definition and theorem that will be used in the next part. In the part of this paper, the author put forward a new BP model based on the random fuzzy theory and gives the advantages of it.
基于随机模糊理论的BP神经网络模型
神经网络领域可以被认为与人工智能、机器学习、并行处理、统计学和其他领域有关。神经网络的吸引力在于它最适合解决传统计算方法最难解决的问题。在本文中,作者首先阐述了神经网络的重要性和应用,然后重点介绍了在许多领域得到广泛应用的BP神经网络。在第二部分中,作者介绍了随机模糊理论,并给出了一些有用的定义和定理,这些将在下一部分中用到。本文提出了一种新的基于随机模糊理论的BP模型,并给出了该模型的优点。
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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