Title :
On integrating fuzzy knowledge using a Novel Evolutionary Algorithm
Author :
Chowdhury, Nurul A. ; Khatun, Murshida ; Hashem, M.M.A.
Author_Institution :
Dept. of Comput. Sci. & Eng., Khulna Univ. of Eng. & Technol. (KUET), Khulna
Abstract :
Fuzzy systems may be considered as knowledge-based systems that incorporates human knowledge into their knowledge base through fuzzy rules and fuzzy membership functions. The intent of this study is to present a fuzzy knowledge integration framework using a novel evolutionary strategy (NES), which can simultaneously integrate multiple fuzzy rule sets and their membership function sets. The proposed approach consists of two phases: fuzzy knowledge encoding and fuzzy knowledge integration Four application domains, the hepatitis diagnosis, the sugarcane breeding prediction, Iris plants classification, and tic-tac-toe endgame were used to show the performance of the proposed knowledge approach. Results show that the fuzzy knowledge base derived using our approach performs better than genetic algorithm based approach.
Keywords :
evolutionary computation; fuzzy systems; knowledge based systems; evolutionary algorithm; fuzzy knowledge encoding; fuzzy knowledge integration; fuzzy rule sets; fuzzy systems; hepatitis diagnosis; knowledge-based systems; plants classification; sugarcane breeding prediction; tic-tac-toe endgame; Encoding; Evolutionary computation; Fuzzy sets; Fuzzy systems; Genetic algorithms; Genetic mutations; Humans; Knowledge based systems; Knowledge engineering; Liver diseases; Crossover; Evolutionary Algorithms (EA); Fuzzy knowledge; Membership function; Mutation; Novel Evolutionary Algorithm (NES); Rule set;
Conference_Titel :
Computer and information technology, 2007. iccit 2007. 10th international conference on
Conference_Location :
Dhaka
Print_ISBN :
978-1-4244-1550-2
Electronic_ISBN :
978-1-4244-1551-9
DOI :
10.1109/ICCITECHN.2007.4579352