%0 Journal Article
%T Ergodicity analysis based on system clustering for temperature variation process of Beijing<br>基于系统聚类的北京气温变化过程遍历特征分析
%A WANG Hong-rui
%A LIN Xin
%A LIU Qiong
%A FENG Qi-lei
%A LIU Chang-ming
%A <br>王红瑞
%A 林欣
%A 刘琼
%A 冯启磊
%A 刘昌明
%J 系统工程理论与实践
%D 2010
%I 
%X The ergodicity analysis of temperature variation is significant for medium and long-term weather forecast.The ergodicity of the month-highest temperature,month- lowest temperature,and month- average temperature in Beijing was discussed in this study.Firstly,each kind of temperature was clustered applying the systematic clustering method by taking a month as the individual.Based on this,autocorrelogram was used to eliminate the periodicity series and ADF(Advanced Dickey & Fuller) was employed to test the sta...
%K Beijing temperature
%K ergodicity
%K systematic clustering
%K stationary test
%K neural networks<br>遍历性
%K 系统聚类
%K 平稳性检验
%K 神经网络
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=01BA20E8BA813E1908F3698710BBFEFEE816345F465FEBA5&cid=962324E222C1AC1D&jid=1D057D9E7CAD6BEE9FA97306E08E48D3&aid=E88C8766800F645A9D8B2901043E2FF9&yid=140ECF96957D60B2&vid=340AC2BF8E7AB4FD&iid=0B39A22176CE99FB&sid=23104246A5FCFCEF&eid=1E41DF9426604740&journal_id=1000-6788&journal_name=系统工程理论与实践&referenced_num=0&reference_num=26