Abstract
This paper presents a systematic framework for the design of intelligent decision support systems based upon soft computing paradigms like neural networks, genetic algorithms, simulated annealing and fuzzy logic. The approach applies knowledge based systems techniques to support development and application of models in these computing paradigms. The long-term goal of this research is to automate the design of soft-computing systems from a domain expert’s description of the problem situation and a set of input data.
The original version of this chapter was revised: The copyright line was incorrect. This has been corrected. The Erratum to this chapter is available at DOI: 10.1007/978-0-387-35602-0_35
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© 2002 IFIP International Federation for Information Processing
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Ramachandran, S., Erraguntla, M., Benjamin, P. (2002). A Knowledge Based Framework for the Design of Soft-Computing Systems. In: Musen, M.A., Neumann, B., Studer, R. (eds) Intelligent Information Processing. IIP 2002. IFIP — The International Federation for Information Processing, vol 93. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-35602-0_12
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DOI: https://doi.org/10.1007/978-0-387-35602-0_12
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4757-1031-1
Online ISBN: 978-0-387-35602-0
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