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Автор: Ziheng Sun, Nicoleta Cristea, Pablo Rivas
Издательство: Elsevier
Год: 2023
Страниц: 430
Язык: английский
Формат: pdf (true)
Размер: 42.9 MB
Artificial Intelligence in Earth Science: Best Practices and Fundamental Challenges provides a comprehensive, step-by-step guide to AI workflows for solving problems in Earth Science. The book focuses on the most challenging problems in applying AI in Earth system sciences, such as training data preparation, model selection, hyperparameter tuning, model structure optimization, spatiotemporal generalization, transforming model results into products, and explaining trained models. In addition, it provides full-stack workflow tutorials to help walk readers through the whole process, regardless of previous AI experience. Artificial Intelligence (AI) technologies have been aggressively experimented with in Earth system sciences and attempted to solve these urgent problems and provide a solution for those ultimate challenges of humanity. Deep Learning has become one of the most popular research areas and could almost be seen in every branch of Earth sciences today. The idea behind Deep Learning is based on adding more hidden layers to the neural network, using a series of methods to control the model regularization and balance between overfitting and underfitting.