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

王宝; 叶彬; 马静; 葛斐; 奚振乾; 杜海红

doi:10.3969/j.issn.1009-1831.2017.01.006

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

更新时间：2026-03-05

- Forecast on electricity consumption of manufacturing industry based on multi dimension and QGA LSSVM algorithm
- Vol. 19, Issue 1, (2017)
- 作者机构：
  
  1. 国网安徽省电力公司经济技术研究院,合肥,230022
  2. 国网安徽省电力公司,合肥,230061
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.1009-1831.2017.01.006
  CLC：
- Published：2017
- 稿件说明：
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王宝, 叶彬, 马静, et al. Forecast on electricity consumption of manufacturing industry based on multi dimension and QGA LSSVM algorithm[J]. 2017, 19(1).
DOI：

王宝, 叶彬, 马静, et al. Forecast on electricity consumption of manufacturing industry based on multi dimension and QGA LSSVM algorithm[J]. 2017, 19(1). DOI： 10.3969/j.issn.1009-1831.2017.01.006.

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。

Abstract

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.

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