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Software Implementation Methodology of Intelligent Information Systems of Learning and Knowledge Control (IISLKC) Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Neural Network-Based Approach for Design and Modeling Evolution Processes of Economic Clusters

Authors : E. A. Babkin, N. A. Klimova, O. R. Kozyrev

Published in: Recent Developments and New Direction in Soft-Computing Foundations and Applications

Publisher: Springer International Publishing

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Abstract

We present here the new approach for design and modeling evaluation of economic clusters based on artificial neural networks platform. We show here the basic principles and discuss the application of the approach for Hopfield networks.

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previous chapter Analytical Models of WLAN Standard IEEE 802.11
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Literature
1.
Klimova, N., Litvintseva, M.: Universities innovation clusters: approaches for national competitiveness paradigm. Eur. J. Soc. Sci. 19(1), 160–162 (2011)
2.
Klimova, N.: Innovative Clusters in Regional Economy. Int. Res. J. Finance Econ. 65, 6–10 (2011)
3.
Klimova, N., Malyzhenkov, P.: Spin-off phenomenon as a factor of university clusters competitiveness increasing: a methodological proposal. In: 11th International Conference on Perspectives in Business Informatics Research BIR 2012, Springer, Nizhny Novgorod, Russia, 24–26 Sept 2012
4.
Jones, T.M.: AI Application Programming. Charles River Media Inc, Hingham (2003)
5.
Peterson, C.: Combinatorial optimization with feedback artificial neural networks. University of Lund, Lund (2002)
6.
Feng, G., Douligeris, C.: Using hopfield networks to solve traveling salesman problems based on stable state analysis technique. IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN’00), vol. 6 (2000)
Metadata
Title
Neural Network-Based Approach for Design and Modeling Evolution Processes of Economic Clusters
Authors
E. A. Babkin
N. A. Klimova
O. R. Kozyrev
Copyright Year
2016
Book
Recent Developments and New Direction in Soft-Computing Foundations and Applications

Print ISBN: 978-3-319-32227-8

Electronic ISBN: 978-3-319-32229-2

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-32229-2_33

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