基于多维度与QGA LSSVM算法的制造业用电量预测

Forecast on electricity consumption of manufacturing industry based on multi dimension and QGA LSSVM algorithm

中文关键词: 制造业用电量  多维度  QGA LSSVM  关键影响因素  用电量预测

英文关键词: manufacturing industry’s electricity consumption  multi dimension  QGA LSSVM  key influencing factors  electricity consumption forecast

中文摘要:

      制造业内部各微观行业出发，设计了与制造业用电密切相关的产品产量、行业投资和景气指数3个维度共35个指标，按相关性原则选取制造业用电量关键影响指标，并采用QGA LSSVM算法构建制造业用电量预测模型。安徽省制造业季度累计用电量预测实例结果表明，该方法预测结果准确可信，预测效果明显好于基于制造业经济总量和基于非关键影响因素方法，为电力市场和经济运行分析预测人员提供了一种有效手段。

英文摘要:

      This paper designs thirty five indicators from such three dimensions as product output, industry investment and boom index closely related to manufacturing industry’s electricity consumption through its each micro industry, selects key influencing indicators in accordance with relevance principle and establishes forecast model of manufacturing industry’s electricity consumption by adopting QGA LSSVM algorithm.A forecast instance of Anhui’s quarterly cumulative manufacturing industry’s electricity consumption demonstrates that the results of this method are accurate and reliable, which is significantly super to methods dependent on manufacturing industry’s output or non key influencing indicators, which can provide an effective tool for electricity market forecasters and economic operation analysts.