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首页> 外文会议>2013 IEEE 11th International Conference on Dependable, Autonomic and Secure Computing >Study and Application of Dynamic Collocation of Variable Weights Combination Forecasting Model
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Study and Application of Dynamic Collocation of Variable Weights Combination Forecasting Model

机译：动态组合变权组合预测模型的研究与应用

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Short-term load forecasting plays a very important role in operating, controlling, and planning of power system. As the load forecasting is vulnerable to various environmental factors, the short-term load forecasting is uncertain and variable. The traditional single forecasting model used to forecast the load of power grid can't comply with the requirements of the power grid management. Combination forecasting model can largely make up for the one-sidedness of the single forecasting methods. In the implementation of combination model, the fixed load forecasting methods also make forecasting results inaccurate, and have a series of problems such as low credibility. In this paper, the thought of dynamic combination is applied in the orderly power consumption management platform, and a combined optimal forecasting model is constructed through automatic screening of the forecasting methods and dynamic collocation of weights. Practice has proved that the combined forecasting method has higher forecasting accuracy than the single forecasting method and it is not only has high forecasting accuracy, but also has good extendibility, quick speed of data processing, simplicity of operation and diversity of display mode.
机译：短期负荷预测在电力系统的运行，控制和规划中起着非常重要的作用。由于负荷预测容易受到各种环境因素的影响，因此短期负荷预测是不确定且可变的。传统的用于预测电网负荷的单一预测模型不能满足电网管理的要求。组合预测模型可以在很大程度上弥补单一预测方法的单一性。在组合模型的实现中，固定负荷的预测方法也使预测结果不准确，存在可信度低等一系列问题。本文将动态组合思想应用到有序的功耗管理平台中，通过自动筛选预测方法和权重动态配置，构建了组合的最优预测模型。实践证明，组合预测方法比单一预测方法具有更高的预测精度，不仅具有较高的预测精度，而且具有良好的可扩展性，数据处理速度快，操作简单和显示方式多样等优点。

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