基于BP神经网络的中国农民收入预测模型研究

Pei Wang, Tingyi Zhao, Yongjun Fan, Qinglu Hao
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引用次数: 4

摘要

由于中国农民收入预测的复杂性以及BP神经网络处理复杂问题的能力和自适应能力,将BP神经网络应用于中国农民收入预测是必要和可行的。本文建立了中国农民收入预测指标体系,引入神经网络并给出了BP神经网络算法的实现与优化,建立了基于BP神经网络的中国农民收入预测模型并对该模型进行了应用与分析,最后总结并提出了需要进一步研究的问题。将BP神经网络应用于中国农民收入预测预测,有助于解决预测复杂性和权重调整复杂带来的问题和困难,有助于提高预测的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Study of Chinese farmers income forecast model based on BP neural network
Because of the complexity of Chinese farmers income forecast and BP neural network's ability to handle complex problem and auto-adaptive ability, the application of BP neural network in Chinese farmers income forecast is necessary and feasible. This paper establishs Chinese farmers income forecast index system, introduces neural network and gives the realization and optimization of BP neural network algorithm, establishs Chinese farmers income based on BP neural network and carry on the application and analysis of this model, Finally summarize and propose required further study question. the application of BP neural network in Chinese farmers income forecast forecast is helpful to solve the problems and difficulties brought by complexity in the forecast and complex weight adjustment and is helpful to improve the accuracy of forecast.
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