Metaheuristic Algorithms and Neural Networks in Hydrology is popular PDF and ePub book, written by Kuok King Kuok in 2024-08-28, it is a fantastic choice for those who relish reading online the Science genre. Let's immerse ourselves in this engaging Science book by exploring the summary and details provided below. Remember, Metaheuristic Algorithms and Neural Networks in Hydrology can be Read Online from any device for your convenience.
Metaheuristic Algorithms and Neural Networks in Hydrology Book PDF Summary
This book summarizes the latest research and developments related to the application of nature-inspired metaheuristic algorithms coupled with artificial neural networks (ANNs) in hydrology. The book covers the theoretical foundations, models and methods, structure, frameworks and analysis of applying novel ANNs in hydrology. It starts with the introduction of ANNs as a black box model, followed by the coupling of various metaheuristic algorithms with ANNs to form novel neural network models for solving real-world problems in hydrology, including Particle Swarm Optimization (PSO) for rainfall-runoff modeling, Bat Optimization (Bat) and Cuckoo Search Optimization (CSO) for future rainfall prediction, the Whale Optimization Algorithm (WOA) and Salp Swarm Optimization (SSO) for future water level prediction, Grey Wolf Optimization (GWO), Multi-Verse Optimization (MVO), the Sine Cosine Algorithm (SCA) and the Hybrid Sine Cosine and Fitness Dependent Optimizer (SC-FDO) for imputing missing rainfall data.
Detail Book of Metaheuristic Algorithms and Neural Networks in Hydrology PDF
- Author : Kuok King Kuok
- Release : 28 August 2024
- Publisher : Cambridge Scholars Publishing
- ISBN : 9781036408053
- Genre : Science
- Total Page : 231 pages
- Language : English
- PDF File Size : 19,7 Mb
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