基于改进遗传算法和BP神经网络的天然气负荷预测

Yihan Tang
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引用次数: 0

摘要

在天然气负荷预测中,传统方法的预测精度较低。为了提高天然气负荷的预测精度,提出了一种新的改进方案。提出了一种基于改进遗传算法和BP神经网络的天然气负荷预测方法。与传统BP预测算法和GA-BP算法相比,本文方法的误差优化性能更好,平均误差为3.22%,具有一定的工程应用价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Natural Gas Load Forecasting Based on Improved Genetic Algorithm and BP Neural Network
The prediction accuracy of the traditional method is low in the natural gas load prediction. Thus, to improve the prediction accuracy of the natural gas load, a new improved scheme is came up with. A natural gas load predicting way is based on improved genetic algorithm and BP neural network. Compared with the traditional BP prediction algorithm and GA-BP algorithm, the error optimization performance by the proposed method is better, with an average error of 3.22%, which has a certain engineering application value.
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