Evolutionary algorithms and allied fields are getting more visibility as well as familiarity due to their numerous flexibilities such as handling high-dimensional non-linear problems and more. This book will help budding researchers to formulate their research problems, and comprises 10 chapters: three on optimization, five on machine learning algorithms, one on Internet of Things, and one on remote sensing.

In Focus – a book series that showcases the latest accomplishments in water research. Each book focuses on a specialist area with papers from top experts in the field. It aims to be a vehicle for in-depth understanding and inspire further conversations in the sector.

Editorial: Evolutionary Algorithms in Water Resources
Dasika Nagesh Kumar & Komaragiri Srinivasa Raju

Evolutionary algorithms, swarm intelligence methods, and their applications in water resources engineering: a state-of-the-art review
M. Janga Reddy & D. Nagesh Kumar

Multi-objective fuzzy optimization for sustainable irrigation planning
Jyotiba B. Gurav & D. G. Regulwar

Application of artificial neural network for predicting water levels in Hooghly estuary, India
Kalyan Kumar Bhar & Susmita Bakshi

Decision tree-based reduction of bias in monthly IMERG satellite precipitation dataset over India
Shushobhit Chaudhary, C. T. Dhanya

Comparative performance evaluation of self-adaptive differential evolution with GA, SCE and DE algorithms for the automatic calibration of a computationally intensive distributed hydrological model
Saswata Nandi & M. Janga Reddy

Quantifying natural organic matter concentration in water from climatological parameters using different machine learning algorithms
Sina Moradi, Anthony Agostino, Ziba Gandomkar, Seokhyeon Kim, Lisa Hamilton, Ashish Sharma, Rita Henderson & Greg Leslie

Modelling hydrological responses under climate change using machine learning algorithms – semi-arid river basin of peninsular India
G. Sireesha Naidu, M. Pratik & S. Rehana

Real-time monitoring of water level and storage dynamics of irrigation tank using IoT
Muthiah Krishnaveni, S. K. Praveen Kumar, E. Arul Muthusamy, J. Kowshick & K. G. Arunya

Development of algorithms for evaluating performance of flood simulation models with satellite-derived flood
Tushar Surwase, P. Manjusree, Sachin Prakash & Saikiran Kuntla

Modelling runoff in an arid watershed through integrated support vector machine
Sandeep Samantaray & Dillip K. Ghose

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