Application of Genetic Algorithm in data Visualization color matching realized by front-end
Authors: Chuyu You, Beibei Sun
Abstract: Aiming at the problems of low efficiency, difficulty in expansion and lack of standardization in the process of realizing data visualization in the front-end, a set of automatic color matching schemes suitable for various chart types is proposed. This method is implemented in combination with Genetic Algorithm. First, a color selection function is used to randomly select colors from qualified color intervals to construct multiple palettes to improve the efficiency of the algorithm. Then, the fitness function is constructed from the two aspects of perceptibility and harmony between colors to judge the quality of the palette, and to screen out the groups that can be inherited to the next generation. Finally, this method is combined with the front-end chart library (ECharts) to apply to the construction of charts with multiple indicators of fire risk indicators, and multi-dimensional surveys of users are carried out. The results show that the chart drawn by this method has higher recognition efficiency and color harmony.
Keywords: Automatic Color Matching, Genetic Algorithm, Front-End
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