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Data Mining : Concepts, Methods and Applications in Management and Engineering Design / by Yong Yin, Ikou Kaku, Jiafu Tang, JianMing Zhu.

Por: Colaborador(es): Tipo de material: TextoTextoSeries Decision EngineeringEditor: London : Springer London : Imprint: Springer, 2011Edición: 1Descripción: xiv, 312 páginas 68 ilustraciones recurso en líneaTipo de contenido:
  • texto
Tipo de medio:
  • computadora
Tipo de portador:
  • recurso en línea
ISBN:
  • 9781849963381
Formatos físicos adicionales: Edición impresa:: Sin títuloClasificación LoC:
  • QA76.9.D343
Recursos en línea:
Contenidos:
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.
Resumen: 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: • market segmentation, • product design, • organization design, • manufacturing design, and • supply chain design. 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.
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Springer eBooks

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.

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: • market segmentation, • product design, • organization design, • manufacturing design, and • supply chain design. 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.

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