首页    期刊浏览 2024年11月28日 星期四
登录注册

文章基本信息

  • 标题:Evolution of new WARM using Likert Weight Measures(LWM)
  • 本地全文:下载
  • 作者:N. Sudha ; Santhosh Baboo
  • 期刊名称:International Journal of Computer Science and Network Security
  • 印刷版ISSN:1738-7906
  • 出版年度:2011
  • 卷号:11
  • 期号:5
  • 页码:70-75
  • 出版社:International Journal of Computer Science and Network Security
  • 摘要:The field of data mining draws upon several roots, including statistics, machine learning, databases and high performance computing. Supplier selection is an important process which needs more expertise to select a supplier as the technology complexity has increased. Frequently as there is a change in the market it will be better if flexibility is maintained. Choosing the right method for supplier selection effectively leads to a reduction in purchase risk and increases the number of JIT suppliers and TQM production. AHP is a widely accepted multi criteria decision making model, which is suitable for supplier selection process. But AHP is required high computation power. In order to reduce more computation power, in this paper we introduced a new model called Likert Weight Meaure (LWM), which is considered to be a light weight supplier selection model. Likert model is globally accepted scaling factor for psychometric feedback.
  • 关键词:Data Mining; Weighted Association Rule Mining; AHP; LWM
国家哲学社会科学文献中心版权所有