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The Bipolar Flexible Neural Forecasting Model and Its Application

机译:双极柔性神经预测模型及其应用

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A flexible neural network which includes flexible, S parameter-varying function is proposed owing to the defect of the tradition neural network in order to enhance the study speed and generalization of the flexible neural network. Action function of flexible function is called S-type function that contains monopole and bipolar. There, The bipolar flexible neural S-type function is adopted. It gives the basic principle of flexible neural network and learning algorithm. To illustrate the effectiveness of the proposed flexible neural network, we get two application examples, one is forecasting power load of a certain electric network and another is forecasting floods of Taiyangtuo Rever, the results show that the model is accurate in forecast.
机译:由于传统神经网络的缺陷,提出了一种柔性神经网络,包括灵活,S的参数 - 变化功能,以提高柔性神经网络的研究速度和泛化。灵活功能的动作功能称为S型功能,包含单极和双极。在那里,采用双极柔性神经S型功能。它提供了灵活的神经网络和学习算法的基本原理。为了说明所提出的灵活神经网络的有效性,我们得到了两个应用实例,一个是预测某个电网的电力负载,另一个是预测TaiyangTuo Rever的洪水,结果表明该模型在预测中准确。

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