Research and Construction of an Interactive Genetic Algorithm-Based Automatic Classification System for Environmental Art Effects in Exhibition Halls

Abstract

The increasing level of people and society's understanding of visual expressions has pushed the development of environmental art(EA) design expression techniques, and the increase and expansion of expression means has prompted designers to update their original concepts of design communication and to re-examine their choices of environmental art design expressions and means. In order to solve the problem of designers learning to refer to the expression techniques of mature design works, this paper introduces the SVM classifier into the environmental art design industry in this context of the times and constructs an automatic classification system for environmental art effects based on interactive genetic algorithm(IGA) to achieve accurate classification of environmental art design works and to enable people to be attracted by the effects of works when visiting environmental art design works in interactive showrooms. The accuracy of the classification system is verified by this paper. The accuracy verification of the classification system in this paper shows that the classification accuracy is the highest under the condition that the sample size is appropriate and the [−1, 1] normalization method is selected.