Evolutionary Machine Learning in Science and Engineering
摘要
Evolutionary machine learning (EML) has been increasingly applied to solving diverse science and engineering problems due to the global search, optimization, and multi-objective optimization capabilities of evolutionary algorithms and the strong modeling capability of complex functions and processes by machine learning (ML) and especially deep neural network models. They are widely used to solve modeling, prediction, control, and pattern detectionPattern detection problems. Especially EML algorithms are used for solving inverse designInverse design problems ranging from neural network architecture search, inverse materials design, control system design, and discoveryMaterials discovery of differential equations.