Automated classification of rainfall systems using statistical characterization
- 出版日期：2003.
- 页数：195 p. :
- 第一责任说明：Michael Eugene Baldwin.
- 分类号：a130
MARC全文
02h0020790 20101216112227.0 cr un||||||||| 101018s2003 xx ||||f|||d||||||||eng | CNY371.35 (UnM)AAI3085711 UnM UnM NGL a130 Baldwin, Michael Eugene. Automated classification of rainfall systems using statistical characterization [electronic resource] / Michael Eugene Baldwin. 2003. 195 p. : digital, PDF file. Source: Dissertation Abstracts International, Volume: 64-03, Section: B, page: 1290. ; Adviser: Frederick H. Carr. Thesis (Ph.D.) -- The University of Oklahoma, 2003. A general, completely automated procedure for classifying rainfall systems is developed. The technique is flexible and universally applicable, in that any rainfall system can be classified regardless of size, location, time of day or year, degree of organization, etc. The knowledge obtained from previous research was used to develop a relatively straightforward and unique classification system. To test the performance of the method, results were validated against a subjective classification based upon objective criteria. From an independent random sample, the automated classification system accurately placed events into stratiform, linear, and cellular classes 85% of the time. Rain and rainfall. ; Precipitation (Meteorology) ; Data mining. aCarr, Frederick H. aCN bNGL http://proquest.calis.edu.cn/umi/detail_usmark.jsp?searchword=pub_number%3DAAI3085711&singlesearch=no&channelid=%CF%B8%C0%C0&record=1 NGL Bs651 rCNY371.35 ; h1 xhbs1003