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
fDate :
6/24/1905 12:00:00 AM
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;
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
DOI :
10.1109/FUZZ.2002.1006640
