Improving Decision Support Systems' Quality Through Machine Learning Based Model Manipulation

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概要

• 論文の詳細を見る

• In this paper, a machine learning based model manipulation approach is presented based on analyzing several new requirements in an Intelligent Decision Support System (IDSS) model subsystem development. Such an approach can effectively eliminate obstacles in model building, model selection and model execution under uncertain environment through accumulation of model manipulation knowledge. Aimed to enhance DSS's learning ability, a machine learning based IDSS framework of four structured learning components is given and a prototypical system is also implemented to illustrate how the components work in coordination.

• 日本情報経営学会の論文
• 1996-11-01

著者

• Hao Ying

  Harbin Institute Of Technology

• HAN SHIXIN

  Harbin Institute of Technology

• HUANG TIYUN

  Harbin Institute of Technology

関連論文

• Improving Decision Support Systems' Quality Through Machine Learning Based Model Manipulation
• Improving Decision Support Systems′ Quality Through Machine Learning Based Model Manipulation (The 2nd International Conference on OA & Information Management--The Current Information Technology and Office Automation,Proceedings,1st-3rd November 1996)

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