DocumentCode
1659520
Title
A neuro-fuzzy-evolutionary classifier of low-risk investments
Author
Serguieva, Antoaneta ; Kalganova, Tatiana
Author_Institution
Dept. of Electron. & Comput. Eng., Brunel Univ., Uxbridge, UK
Volume
2
fYear
2002
fDate
6/24/1905 12:00:00 AM
Firstpage
997
Lastpage
1002
Abstract
This paper demonstrates that a hybrid fuzzy neural network can serve as a classifier of low risk 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 applied to empirical data on UK companies traded on the LSE
Keywords
evolutionary computation; fuzzy neural nets; bidirectional incremental evolution; hybrid fuzzy neural network; low risk investment projects; low-risk investments; neuro-fuzzy-evolutionary classifier; Appraisal; Computer networks; Consumer electronics; Databases; Fuzzy neural networks; Genetic algorithms; Investments; Robustness; Stock markets; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems, 2002. FUZZ-IEEE'02. Proceedings of the 2002 IEEE International Conference on
Conference_Location
Honolulu, HI
Print_ISBN
0-7803-7280-8
Type
conf
DOI
10.1109/FUZZ.2002.1006640
Filename
1006640
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