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Prediction of macro city gas load on BP neural network theory

机译:基于BP神经网络的宏观城市燃气负荷预测。

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Gas transmission and distribution system, the gas load is the main parameter to impact the project planning, which determines the capacity of equipments and operation program. Therefore, accurate prediction of gas load is of extremely important significance for gas companies to improve safety and reliability of gas supply. The forecasting method of tradition gas load would not meet the requirement for accurate prediction. It is necessary to find a new method to forecast it. Multi-layer feed forward artificial neural network based on BP algorithm is selected to forecast macro city gas load and a predicted model is established by using MATLAB programming. In order to ensure the accuracy of the prediction model, the article focuses on the simulation error of the text model and judges these errors as the accuracy of the prediction models.
机译:输配气系统中,瓦斯负荷是影响项目计划的主要参数,它决定了设备的能力和运行方案。因此,准确预测燃气负荷对燃气公司提高燃气供应的安全性和可靠性具有极其重要的意义。传统瓦斯负荷的预测方法不能满足准确预测的要求。有必要找到一种新的预测方法。选择了基于BP算法的多层前馈人工神经网络对城市燃气的宏观负荷进行预测,并通过MATLAB编程建立了预测模型。为了确保预测模型的准确性,本文重点介绍文本模型的模拟误差,并将这些误差判断为预测模型的准确性。

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