Angielski
"Soft Computing and Machine Learning in Dam Engineering" is a comprehensive, edited Special Issue that explores the latest advances in the application of soft computing and machine learning techniques to dam engineering. This reprint covers a range of topics, including dam design, construction, monitoring, and maintenance, and provides readers with a deep understanding of the theoretical foundations and practical applications of these techniques.
Featuring contributions from leading experts in the field, the reprint presents a collection of 11 papers that offer insights into state-of-the-art approaches in dam engineering. The chapters cover topics such as fuzzy logic, genetic algorithms, artificial neural networks, and support vector machines, and provide practical examples of how these techniques can be applied to solve real-world dam engineering problems.
Whether you are a researcher, engineer, or student in the field of dam engineering, "Soft Computing and Machine Learning in Dam Engineering" provides a valuable resource for staying up-to-date with the latest techniques and approaches in the field.
