Data mining : concepts, methods and applications in management and engineering design
著者
書誌事項
Data mining : concepts, methods and applications in management and engineering design
（Decision engineering）
Springer, c2011
大学図書館所蔵 全5件
注記
Includes bibliographical references and index
内容説明・目次
内容説明
Data Mining introduces in clear and simple ways how to use existing data mining methods to obtain effective solutions for a variety of management and engineering design problems.
Data Mining is organised into two parts: the first provides a focused introduction to data mining and the second goes into greater depth on subjects such as customer analysis. It covers almost all managerial activities of a company, including:
* supply chain design,
* product development,
* manufacturing system design,
* product quality control, and
* preservation of privacy.
Incorporating recent developments of data mining that have made it possible to deal with management and engineering design problems with greater efficiency and efficacy, Data Mining presents a number of state-of-the-art topics. It will be an informative source of information for researchers, but will also be a useful reference work for industrial and managerial practitioners.
目次
1. Decision Analysis and Cluster Analysis.- 2. Association Rules Mining in Inventory Data Base.- 3. Fuzzy Modeling and Optimization: Theory and Methods.- 4. Genetic Algorithm Based Fuzzy Nonlinear Programming.- 5. Neural Network and Self Organizing Maps.- 6. Privacy Preserving Data Mining.- 7. Supply Chain Design by Using Decision Analysis.- 8. Product Architecture and Product Development Process for Global Performance.- 9. Application of Cluster Analysis to Cellular Manufacturing.- 10. Manufacturing Cells Design by Cluster Analysis.- 11. Fuzzy Approach to Quality Function Deployment-based Product Planning.- 12. Decision Making with Consideration of Association in Supply Chains.- 13. Applying Self Organizing Maps to Master Data Making in Automatic Exterior Inspection.- 14. Application for Privacy Preserving Data Mining.
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