An intelligent color design method for visual communication design for public crisis

Abstract During a crisis, people's emotions are dynamically affected by changes in the environment, and by the attributes of object and subject in ways that depend on an emotion's essential characteristics. Negative emotions can cause psychological harm to people, but specific visual colors can instantaneously dispel or reduce those negative emotions. We developed a color design method based on a hybrid intelligent algorithm to predict accurately the significant negative emotions of people during a public crisis, and to explore the relationship between color structure and negative emotions developed. A Fuzzy Bayesian Network prediction model was constructed of people's significant negative emotions during a public crisis. Then, the concept of color cube was proposed that related color combinations to particular emotions. Finally, based on the emotion arousal experiment and the BP neural network, the nonlinear mapping relationship between negative emotion and color cube was analyzed to predict the fading versus stimulating color structure of the significant negative emotions. This mapping provides a reference for the color design of visual communications during a public crisis. Our results show that the prediction model of emotions and color design method were effective.