摘要
针对遗传算法个体进化缺乏明确导向的缺点，该文提出了一种基于知识模型的改进遗传算法，将遗传算法和神经网络有效结合起来，利用神经网络的学习功能，构造知识模型，用来引导群体中某些个体的进化。模拟实验验证了该算法的有效性。
To overcome one disadvantage of genetic algorithms that there is no explicit element to guid individuals' evolution, we propose a knowledge-model-based genetic algorithm in this paper. This algorithm combines the ideas of genetic algorithms and neural network, using the learning feature of neural network to form a knowledge model which guides some individuals' evolution. Asimulation example proves this algorithm's efficiency.
出处
《计算机工程》
CAS
CSCD
北大核心
2000年第5期19-20,86,共3页
Computer Engineering
