南华大学学报(自然科学版)
南華大學學報(自然科學版)
남화대학학보(자연과학판)
JOURNAL OF NANHUA UNIVERSITY(SCIENCE AND TECHNOLOGY)
2014年
2期
89-93
,共5页
节能%能耗监控%数据挖掘%离群点检测%卡方分布
節能%能耗鑑控%數據挖掘%離群點檢測%卡方分佈
절능%능모감공%수거알굴%리군점검측%잡방분포
energy conservation%monitoring energy%data mining%outlier detection%chi-square distribution
节能是当今社会面临的重大课题,高校作为能源大户以及教书育人的基地,必须在能耗监控系统中起到领先示范的作用。在节能分析系统中,能耗的预警预测是关键,因此,异常点的发现与分析,为预警提供了直接的依据,是整个系统的基础。在数据挖掘中,离群点检测分析可以通过多种方法实现,本文应用了基于统计分布的离群点检测方法,但由于在实际情况中,能耗数据的变化与社会各类群体的生活习性、工作周期相关,这些复杂性决定了在数据分析中,只能根据实际的业务来检验分析结果的正确性。本文通过对某高校的能耗进行基于统计分布的离群点分析,并结合校园能耗规律,得出在高校中能耗的异常情况并报警,以达到节约能耗的目的。
節能是噹今社會麵臨的重大課題,高校作為能源大戶以及教書育人的基地,必鬚在能耗鑑控繫統中起到領先示範的作用。在節能分析繫統中,能耗的預警預測是關鍵,因此,異常點的髮現與分析,為預警提供瞭直接的依據,是整箇繫統的基礎。在數據挖掘中,離群點檢測分析可以通過多種方法實現,本文應用瞭基于統計分佈的離群點檢測方法,但由于在實際情況中,能耗數據的變化與社會各類群體的生活習性、工作週期相關,這些複雜性決定瞭在數據分析中,隻能根據實際的業務來檢驗分析結果的正確性。本文通過對某高校的能耗進行基于統計分佈的離群點分析,併結閤校園能耗規律,得齣在高校中能耗的異常情況併報警,以達到節約能耗的目的。
절능시당금사회면림적중대과제,고교작위능원대호이급교서육인적기지,필수재능모감공계통중기도령선시범적작용。재절능분석계통중,능모적예경예측시관건,인차,이상점적발현여분석,위예경제공료직접적의거,시정개계통적기출。재수거알굴중,리군점검측분석가이통과다충방법실현,본문응용료기우통계분포적리군점검측방법,단유우재실제정황중,능모수거적변화여사회각류군체적생활습성、공작주기상관,저사복잡성결정료재수거분석중,지능근거실제적업무래검험분석결과적정학성。본문통과대모고교적능모진행기우통계분포적리군점분석,병결합교완능모규률,득출재고교중능모적이상정황병보경,이체도절약능모적목적。
Energy conservation is a major issue in today’s society,as the teaching base of energy-hungry,colleges must play a leading role in energy consumption monitoring sys-tem. Early warning and forecast energy consumption is the key in the energy analysis, thus detection and analysis outliers is the foundation of the whole system and provides a direct basis for early warning. In data mining, outlier detection has several ways to a-chieve. This paper is based on the statistical distribution of outlier detection methods. However,as in reality,changes of energy consumption data related with the living habits of social groups and the working cycle,the correctness of these complexities determined that it can only be based on actual business results of tests and analysis in data analysis. This paper finds the abnormal situation of the universities’ energy consumption and then activates an alarm by the statistical distribution of outlier detection methods of the energy consumption combined with consumption pattern in the university,in order to achieve the purpose of saving energy.