Handbook of HydroInformatics: Volume I: Classic Soft-Computing Techniques explores the difference between traditional computing, also known as hard computing and soft computing, which is based on the importance given to issues like precision, certainty and rigor. Chapters define fundamentally classic soft-computing techniques such as Artificial Neural Network, Fuzzy Logic, Genetic Algorithm, Supporting Vector Machine, Ant-Colony Based Simulation, Bat Algorithm, Decision Tree Algorithm, Firefly Algorithm, Fish Habitat Analysis, Game Theory, Hybrid Cuckoo-Harmony Search Algorithm, Honey-Bee Mating Optimization, Imperialist Competitive Algorithm, Relevance Vector Machine, and more. This volume is a true interdisciplinary work that will be useful to post graduates and above in the fields of Artificial Intelligence, Computer Science, Mathematical Science, Applied Science, Earth and Geoscience, Geography, Civil Engineering, Engineering, Water Science, Atmospheric Science, Social Science, Environment Science, Natural Resources and Chemical Engineering. Contains contributions from global contributors in the fields of data management research, climate change and resilience, insufficient data problem, and more Presents applied examples and case studies in each chapter, providing the reader with real-world scenarios for comparison Defines classic soft-computing techniques that are necessary for a range of disciplines

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