Neural networks and regressive KPI metamodels for business corporate management: Methodology and case study

Business Performance Measurement and Management: New Contexts, Themes and Challenges

Volumn , Issue , 2010, Pages 343-356

  Revetria, Roberto ^a   Tonelli, Flavio ^a  

^a UNIVERSITY OF GENOA   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84873412365     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1007/978-3-642-04800-5_22     Document Type: Chapter

References (7)

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2. Kamath M, Dalal N, Sivaraman E, Kolarik W (March 2004) Toward an integrated framework for modeling enterprise processes. CACM 47(3):83-87
3. Merkuryeva G (2000) Regression metamodels as an approximation of the input/output relations implied by simulation, IIpobjieMHi YnpaBieHHa Be3onacHoCTbio CioKHbix CHCTCM
4. Revetria R, Mosca R, Schenone M (2005) Improve supply chain management using neural networks and regressive KPI relationship metamodels. IJCAS, CHAOS, ISSN 1373-5411
5. Sarle WS (1994) Neural networks and statistical models. Proceedings of the Nineteenth Annual SAS Users Group International Conference, SAS Institute, Cary, NC, pp 1538-1550
6. Simchi-Levi D, Kaminsky P, Simchi-Levi E (2000) Design and managing the supply chain:concepts, strategies & case studies. McGraw-Hill, Boston, ISBN 0-07-235756-8
7. Steppan DD, Werner J, Yeater RP (1998) Essential regression and experimental design for chemists and engineers, Gibsonia, PA, Bethel Park, PA, Moundsville, WV, June 1998