Generative AI and optimization techniques for sustainable water management Mohamed Lahby, Rajae Gaamouche, editors

Format:

Book

Contributor:

Lahby, Mohamed, editor.

Series:

Springer optimization and its applications ; v. 236.

Springer optimization and its applications 1931-6836 volume 236

Language:

English

Subjects (All):

Water-supply--Management.

Water-supply.

Generative artificial intelligence--Industrial applications.

Generative artificial intelligence.

Physical Description:

1 online resource

Place of Publication:

Cham, Switzerland Springer [2026]

Summary:

"This book examines the transformative potential of Generative Artificial Intelligence (GenAI) in addressing one of the most urgent global challenges: sustainable water management. It investigates how GenAI provides innovative tools for predicting water demand, optimizing resource allocation, and reducing the impacts of climate change. The book includes state-of-the-art contributions from experts in GenAI, optimization techniques, and water management, offering a comprehensive and interdisciplinary approach to the subject. The book explores key concepts, including the integration of advanced algorithms with real-world case studies, bridging the gap between cutting-edge technological innovation and practical water management strategies. The chapters delve into topics like government policy impacts, optimization techniques for pollution control, and AI-powered predictive models for aquaculture. This book is a must-read for those seeking to understand the role of GenAI in creating a smart and resilient future for water management. Essential for researchers, policymakers, and professionals in environmental science, agriculture, and sustainability, this book provides valuable knowledge and innovative approaches to addressing global water challenges"-- Springer Nature Link

Contents:

Impact of government policy on sustainable water management in the light of generative AI in Vietnam / Van Chien Nguyen

Evaluating human expertise and generative AI (ChatGPT) responses to questions on water challenges : A quantitative study / Suha Khalil Assayed and Almoayied Assayed

Factors affecting sustainable water investment in the interactive effects of generative AI / Hong Thi Nguyen

Optimization techniques for water management

Optimization of water management for reducing health risks in the MENA region : A Lagrange multiplier approach / Ahmed Bouzit, Mariem Liouaeddine, and Said Tounsi

A lab-scale prototype : Determining the pipeline networks leakage point using fuzzy logic and IoT / Ching Yee Yong and Johnathan Anak Empawi

Hybrid spatio-temporal NSGA-II–TOPSIS optimization framework for intelligent urban water network management / J. Vijitha Ananthi and James Deva Koresh Hezekiah

Generative AI models for water management

AI-enhanced optimization of water management under climate uncertainty / J. Shanthini, J. Dhanalakshmi, R. Rajeswari, and C. S. Madhumathi

AI-powered generative models for predictive and optimized aquaculture water management / Md. Shoeab Akhter, Sakibul Islam Ratul, Upoma Chowdhury, M. Shohidullah Miah, M. Jabed Ali Mirza, and Ahamad Hossain

RivUNet : An attention-gated deep U-Net for water body segmentation in satellite imagery to enhance river encroachment monitoring / Mahin Montasir Afif, Abdullah Al Noman, K. M. Tahsin Kabir, Md. Mortuza Ahmmed, Md. Ashaful Babu, and Mohamed Lahby

Wastewater treatment based on GenAI / Surya Pratap Singh, Diwesh Kumar, Sudarshana Banerjee, and Shashi Shekhar Singh

LLM and metamodeling for model extraction from smart agriculture requirements / Hamza Abdelmalek, Mohammed Ait Oussouss, Abdeslam Jakimi, Rajae Gaamouche, Rachid Saadane, and Abdellah Chehri

Policy-ready digital-twin framework for hospital water resilience / Saud Khalid AlSamadani and Hamoud M. Alrougi

Optimization of agricultural production in the MENA region under resource constraints and water stress / Mohamed Idalfahim and Saad Elouardirhi

Water flow prediction in the Black River (USA) leveraging evolutionary feedforward artificial neural networks and crow search optimization / Walaa H. Elashmawi and Alaa Sheta

Estimation and prediction of hydrological variables using machine learning algorithms for groundwater management : ErfoudRadier Station in Morocco / Rachid El Ansari, Ahmed Regragui, Mohamed El Bouhaddioui, Jamal Elhassan, Youssef Rissouni, Hicham Boutracheh, Moulay Othman Aboutafail, and Aniss Moumen

Notes:

Includes bibliographical references

Online resource; title from PDF title page (Springer Nature Link, viewed June 2, 2026)

Other Format:

Print version Generative AI and optimization techniques for sustainable water management

ISBN:

9783032190123

3032190126

OCLC:

1591253678

Access Restriction:

Restricted for use by site license