Machine Learning with Metaheuristic Algorithms for Sustainable Water Resources Management

doi:10.3390/books978-3-0365-1719-3

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Hardback

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Keywords

groundwater; artificial intelligence; hydrologic model; groundwater level prediction; machine learning; principal component analysis; spatiotemporal variation; uncertainty analysis; hydroinformatics; support vector machine; big data; artificial neural network; nitrogen compound; nitrogen prediction; prediction models; neural network; non-linear modeling; PACF; WANN; SVM-LF; SVM-RF; Govindpur; streamflow forecasting; Bayesian model averaging; multivariate adaptive regression spline; M5 model tree; Kernel extreme learning machines; South Korea; artificial neural network; uncertainty; sustainability; prediction intervals; ungauged basin; machine learning; streamflow simulation; satellite precipitation; atmospheric reanalysis; ensemble modeling; additive regression; bagging; dagging; random subspace; rotation forest; flood routing; Muskingum method; extension principle; calibration; fuzzy sets and systems; particle swarm optimization; EEFlux; irrigation performance; CWP; water conservation; NDVI; water resources; Daymet V3; Google Earth Engine; improved extreme learning machine (IELM); sensitivity analysis; shortwave radiation flux density; sustainable development; n/a

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Machine Learning with Metaheuristic Algorithms for Sustainable Water Resources Management

Edited by

August 2021

254 pages

ISBN978-3-0365-1720-9 (Hardback)
ISBN978-3-0365-1719-3 (PDF)

https://doi.org/10.3390/books978-3-0365-1719-3

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This is a Reprint of the Special Issue Machine Learning with Metaheuristic Algorithms for Sustainable Water Resources Management that was published in

Business & Economics

Environmental & Earth Sciences

Social Sciences, Arts & Humanities

Summary

The main aim of this book is to present various implementations of ML methods and metaheuristic algorithms to improve modelling and prediction hydrological and water resources phenomena having vital importance in water resource management.

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