Predicting the trends of future color is a crucial task in the study of color application, which is also of great importance to the business economy and has received increasing attention in the design field in recent years. More advanced quantitative computational methods are expected to make the prediction more accurate, and thus help designers to avoid the interference of subjective factors when carrying out the design. In this article, a hybrid model based on genetic algorithm and extreme learning machine is developed to predict color trends. The accuracy is improved through the optimal solution of hidden bias and input weights of the extreme learning machine searched by a genetic algorithm. By using a real historical dataset of smartphone appearance color, the prediction results of the genetic algorithm-extreme learning machine model are compared with those of several commonly used models in the past. The accuracy of the model is evaluated in terms of absolute error and mean absolute error values. The results show that the method proposed in this article can maintain higher accuracy when predicting the trends of smartphone appearance color.

中文翻译：

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基于遗传算法和极限学习机的色彩趋势预测方法

预测未来色彩的趋势是色彩应用研究中的一项重要任务，对商业经济也具有重要意义，近年来在设计领域受到越来越多的关注。更先进的定量计算方法有望使预测更加准确，从而帮助设计人员在进行设计时避免主观因素的干扰。在本文中，开发了一种基于遗传算法和极限学习机的混合模型来预测颜色趋势。通过遗传算法搜索的极限学习机的隐藏偏差和输入权重的最优解，提高了精度。通过使用智能手机外观颜色的真实历史数据集，将遗传算法-极限学习机模型的预测结果与以往几种常用模型的预测结果进行对比。模型的准确性根据绝对误差和平均绝对误差值进行评估。结果表明，本文提出的方法在预测智能手机外观颜色趋势时可以保持较高的准确性。