A first study of Fuzzy Cognitive Maps learning using cultural algorithm

Author

Ahmadi, Siavash ; Forouzideh, Nafiseh ; Chung-Hsing Yeh ; Martin, Rashad ; Papageorgiou, Elpiniki

Author_Institution

Fac. of Inf. Technol., Monash Univ., Melbourne, VIC, Australia

fYear

2014

fDate

9-11 June 2014

Firstpage

2023

Lastpage

2028

Abstract

In this paper a new algorithm for Fuzzy Cognitive Maps learning is introduced. The proposed approach is based on the cultural algorithm and it is used to build the weight matrices that allow the Fuzzy Cognitive Map algorithm to find the final steady states. A Fuzzy Cognitive Map (FCM) is a fuzzy signed directed graph with feedback and models complex systems as a collection of concepts and causal relations between concepts. An FCM can be constructed by using experts´ knowledge or historical data. In this paper we have developed an automated method FCM learning which uses a type of evolutionary algorithm known as a cultural algorithm. We explain the algorithm and demonstrate its performance advantages.

Keywords

cognitive systems; directed graphs; evolutionary computation; fuzzy set theory; learning (artificial intelligence); matrix algebra; automated FCM learning method; complex systems; cultural algorithm; evolutionary algorithm; expert knowledge; feedback; fuzzy signed directed graph; historical data; weight matrices; Aerospace electronics; Cultural differences; Evolutionary computation; Numerical models; Sociology; Time series analysis; Cultural Algorithm; FCM learning; Fuzzy cognitive maps (FCM);

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Electronics and Applications (ICIEA), 2014 IEEE 9th Conference on

Conference_Location

Hangzhou

Print_ISBN

978-1-4799-4316-6

Type

conf

DOI

10.1109/ICIEA.2014.6931502

Filename

6931502