| Title |
Development of a Modified Real-valued Genetic Algorithm with an Improved Crossover |
| Authors |
이덕규(Lee, Deog-Kyoo) ; 이성환(Lee, Sung-Hwan) ; 우천희(Woo, Chun-Hee) ; 김학배(Kim, Hag-Bae) |
| Keywords |
유전알고리즘 ; 지능형 신경망 ; 구조동정 ; 감수분열 유전알고리즘 ; |
| Abstract |
In this paper, a modified real-valued genetic algorithm is developed by using the meiosis for human's chromosome. Unlike common crossover methods adapted in the conventional genetic algorithms, our suggested modified real-valued genetic algorithm makes gametes by conducting the meiosis for individuals composed of chromosomes, and then generates a new individual through crossovers among those. Ultimately, when appling it for the gas data of Box-Jenkin, model and parameter identifications can be concurrently done to construct the optimal model of a neural network in terms of minimizing with the structure and the error. |