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Combination model of load forecasting has been a new directing of developing research.

负荷预测组合模型成为研究新发展。

The hybrid algorithm can be effectively used in short time load forecasting of the power system.

该算法可有效用于电力系统的短期负荷预测。

As a part of Energy Management System (EMS), daily load forecasting is very important for safety and economy operation of the power system.

日负荷预测作为能量管理系统（EMS）的重要组成部分，是电力系统安全、经济运行的保证。

Predicted results show that the improved control method to improve the air-conditioning system load forecasting is effective and feasible.

预测结果表明这种改进的控制方式在空调系统的负荷预测方面是有效的、可行的。

The proposed algorithms have been applied to short-term load forecasting and local pattern analysis of spatial associations.

我们将所提出的方法用于负荷预测和空间模式分析，取得了较好的效果。

This paper studies Bayesian neural network in power load forecasting, load forecasting power of the basic concepts and methods.

本文主要研究贝叶斯神经网络在电力负荷预测中的利用，论述了电力负荷预测的根本概念和措施。

The core of this paper is to use combined forecasting to improve the accuracy of short-term electric power load forecasting.

本文研究的核心就是利用组合预测提高短期电力负荷预测的准确率。

From the traditional predictive technology to today's artificial intelligence technology, various load forecasting technology have emerged.

从传统的预测技术，到现在的人工智能技术，各式各样的负荷预测技术不断涌现。

The forecasted peak load can be obtained by wavelet reconstruction with the forecasted linear part and non-linear part.

将预测所得线性分量及非线性分量进行小波重构得到最终的高峰负荷预测结果。