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Title: An intelligent system for risk classification of stock investment projects
Authors: Serguieva, A
Kalganova, T
Khan, T
Keywords: Finance;Bidirectional incremental evolution;Multimodel knowledge representation
Issue Date: 2003
Publisher: Cambridge University Press
Citation: Journal of Applied Systems Studies. 4 (2) 236-261
Abstract: The proposed paper demonstrates that a hybrid fuzzy neural network can serve as a risk classifier of stock investment projects. The training algorithm for the regular part of the network is based on bidirectional incremental evolution proving more efficient than direct evolution. The approach is compared with other crisp and soft investment appraisal and trading techniques, while building a multimodel domain representation for an intelligent decision support system. Thus the advantages of each model are utilised while looking at the investment problem from different perspectives. The empirical results are based on UK companies traded on the London Stock Exchange.
Appears in Collections:Electronic and Computer Engineering
Dept of Electronic and Computer Engineering Research Papers

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