Implementation of Schema Learning Optimized Cultural Algorithms in Ceramic Art Innovative Design

Abstract

Current ceramic art design mode has not realized the all-round advancement of network technology, which has caused multiple classical ceramic problems, and hindered the future development of ceramic art design mode to a large extent. Aiming at the shortcomings of genetic algorithm and drawing lessons from the idea of cultural algorithm, a cultural genetic algorithm based on Schema learning is proposed. This algorithm incorporates GA algorithm into the framework of cultural algorithm, and constitutes the main group space and belief space based on GA. The two spaces have their own groups, and the lower main group space will each generation. Excellent individuals pass on to the upper belief space, and the global optimum model obtained by Schema extraction from the upper belief space is passed on to the lower main group space. Such method strengthens the extraction of information performed by the optimal individual and improves the convergence speed of the algorithm. At the same time, genetic compensation is used to expand the search space when initializing the population, which also effectively prevents premature convergence.