Military Cockpit Color Design Method Based on Deep Representation Learning and Genetic Algorithm
The color design of military cockpits is a subjective part of industrial design for manned military equipment,and the rationality of the design is crucial. A military cockpit color matching method based on deep representation learning and genetic algorithm is proposed to improve the scientific nature of military cockpit color design. This method uses a deep representation learning model to predict the military cockpit color schemes and establishes a military cockpit color matching model based on color perception theory,which serves as a constraint condition for generating schemes. At the same time,an interactive genetic algorithm is introduced into the intelligent color matching system to optimize the parameters of neural network through manual guidance,and effectively iterate the predicted color matching schemes. The results show that the color matching schemes generated by the proposed method comply with the military cockpit color matching model,and the prediction accuracy of the proposed model combined with genetic algorithm is improved by 16％～18％ compared to a single deep representation model. Compared to manual color design schemes,the satisfaction of the color schemes generated by the military cockpit intelligent color matching method is slightly higher,the design cycle is shortened by 80％～88％,and the color stability is improved by 6％～12％.
military cockpit color matchingdeep representation learninginteractive genetic algorithmcolor perception
万方数据
维普
