Mining Time Series Data: Case of Predicting Consumtion Patterns in Steellndustry

摘要：

Analyzing and predicting with Time series is a method which used in different fields, including consumption patternanalyzing and predicting. In this paper, required amount of inventory items have been predicted with time series. At first, desired data mining process is designed and implemented using Clementine data mining tool. We evaluate this process using the dataset from Irans ZoabAhan steel company.Results show that by using this process not only we can model consumption patterns for the present time but also we can predict required stock items for future with adequate accuracy.

关键词： data mining time series modeling consumption patterns prediction

作者: Azar Fazel Mohammad Saraee Pirooz Shamsinejad

作者单位: Department of Electrical and Computer Engineering Isfahan University of Technology lsfahan, lran

会议类型: 国际会议

会议名称: The 2nd International Conference on Software Engineering and Data Mining(IEEE 第二届国际软件工程和数据挖掘学术大会 SEDM 2010)

会议地点: 成都

会议语种:英文

页码: 452-456

在线出版日期: 2010-06-23（万方平台首次上网日期，不代表论文的发表时间）