Application of genetic algorithms in fuzzy design
遗传算法在模糊设计中的应用

A practical scheme of fuzzy design in CAD systems is developed, of which the environment is the currently collected data; the learning unit is the fuzzy optimization algorithm based on the genetic algorithms; the knowledge base is composed of design criteria; the executive part is the design unit. The fuzzy optimization learning algorithm of the regression equation is developed, and the corresponding flow chart is built. Then, the design criterion of a flash size is obtained by using this system; and the stability of the algorithm is verified through some examples. To evaluate the performances of the algorithm, we compare it with the least-squares method(LSM) and the immune-genetic algorithm(IGA); the result shows that our algorithm is faster, with higher precision and stability than the other algorithms.