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计算机系统应用英文版:2013,22(12):199-205
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区域工业能耗数据挖掘模型
(1.浙江工业大学 计算机科学与技术学院, 杭州 310032;2.浙江绍兴东越科技有限公司, 绍兴 312000)
Data Mining Model of Energy Consumption for Regional Industry
(1.School of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310032, China;2.Dongyue Technology Co., Ltd, Shaoxing 312000, China)
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Received:May 17, 2013    Revised:August 26, 2013
中文摘要: 针对区域能源监察工作中存在的有数据,却没有有效方法分析数据的问题,使用数据挖掘的方法建立一种新的区域工业能耗数据挖掘模型. 首先利用k-均值聚类分析区域各行业能耗特征;并对单个行业进行聚类,找出同行业高能耗,中能耗,低能耗企业;然后基于同类企业中相同产品工艺设备的相关性使用多维关联规则算法,找出同类产品中工艺、设备、能效的相关性,指导区域节能工作,该算法是apriori算法的改进,以适用于具体产品工艺设备的频繁谓词集挖掘. 通过实例分析表明,该模型有效、可行,为区域工业节能提供了一条新的途径.
Abstract:This paper proposes a new data mining model of energy consumption for regional industry, which is used? to solve the problem that there is no effective method on data analysis in regional energy monitor. First, it analyses the characteristics of regional energy consumption in different industries in k-means, clusters a single industry and finds out the high, middle, low energy consumption industrial enterprises. Then, multidimensional association rules are used to find the correlation of processes, equipments and energy efficiency to guide the energy conservation in regional energy monitor. The algorithm has been improved on the basis of apriori algorithm to find the frequent predicate set of specific product's processes and equipment. The analysis of the example shows the model is effective and feasible which provides a new way for energy saving of regional industry.
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基金项目:浙江省信息服务业发展专项资金(浙财企[2011]342号)
引用文本:
郝平,刘薇,王雨晨.区域工业能耗数据挖掘模型.计算机系统应用,2013,22(12):199-205
HAO Ping,LIU Wei,WANG Yu-Chen.Data Mining Model of Energy Consumption for Regional Industry.COMPUTER SYSTEMS APPLICATIONS,2013,22(12):199-205