摘要
从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。
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 eonsumption 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.
出处
《电力需求侧管理》
2017年第1期17-21,28,共6页
Power Demand Side Management
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
manufacturing industry＇ s electricity consumption
multi-dimension
QGA-LSSVM
key influencing factors
electricity consumption forecast
