改进的Elman神经网络预测模型及其在农业生产中的应用

2013 IEEE International Conference on Granular Computing (GrC) Pub Date : 2013-12-01 DOI:10.1109/GRC.2013.6740408

Liu Yi, Xu Ke, Song Junde, Zhao Yuwen, Bi Qiang

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引用次数: 1

摘要

在分析Elman神经网络动态特性的基础上，针对BP神经网络静态预测的缺陷，提出了一种改进的Elman神经网络用于农业生产区域预测的方法。我们使用水稻害虫- chilo的数据进行模拟。实验表明，改进的Elman神经网络比Elman神经网络和BP神经网络具有更好的可预测性和稳定性。

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Forecasting model based on an improved Elman neural network and its application in the agricultural production

On the base of analyzing the dynamic characteristics of Elman neural network, this paper proposes to use an improved Elman neural network to forecast in the agricultural production areas against to the BP neural network's static defects. We uses the data of rice pest-Chilo to simulate. The experiment shows that the improved Elman neural network has better predictability and stability than Elman neural network and BP neural network.

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2013 IEEE International Conference on Granular Computing (GrC)

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