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LDR04348cmm u22005537i 4500
001000000327891
003OCoLC
00520240307140819
006m d
007cr cnu---unuuu
008230901s2023 pau fob 001 0 eng d
020 ▼a 9781668467930 ▼q electronic book
020 ▼a 1668467933 ▼q electronic book
020 ▼a 9781668467947 ▼q (electronic bk.)
020 ▼a 1668467941 ▼q (electronic bk.)
020 ▼z 9781668467916 ▼q print
020 ▼z 1668467917 ▼q hardcover
0247 ▼a 10.4018/978-1-6684-6791-6 ▼2 doi
035 ▼a 3669454 ▼b (N$T)
035 ▼a (OCoLC)1396170118
040 ▼a IGIGL ▼b eng ▼e rda ▼c IGIGL ▼d YDX ▼d OCLCO ▼d OCLCQ ▼d N$T ▼d 248032
049 ▼a MAIN
050 4 ▼a TD430 ▼b .A785 2023
08204 ▼a 628.1/62 ▼2 23
24500 ▼a Artificial intelligence applications in water treatment and water resource management / ▼c Victor Shikuku, editor.
264 1 ▼a Hershey, PA : ▼b Engineering Science Reference (an imprint of IGI Global), ▼c [2023]
300 ▼a 1 online resource (xix, 270 pages).
336 ▼a text ▼b txt ▼2 rdacontent
337 ▼a computer ▼b c ▼2 rdamedia
338 ▼a online resource ▼b cr ▼2 rdacarrier
4901 ▼a Advances in environmental engineering and green technologies (AEEGT) book series
504 ▼a Includes bibliographical references and index.
5050 ▼a Foreword -- Preface -- Chapter 1. Machine Learning Applications in Adsorption of Water Pollutants -- Chapter 2. Artificial Intelligence in Wastewater Management -- Chapter 3. Integrating Machine Learning and AI for Improved Hydrological Modeling and Water Resource Management -- Chapter 4. Artificial Intelligence in Water Treatments and Water Resource Assessments -- Chapter 5. The Use and Awareness of ICT to Facilitate the Adoption of Artificial Intelligence in Agriculture -- Chapter 6. Artificial Intelligence, Internet of Things, and Machine-Learning: To Smart Irrigation and Precision Agriculture -- Chapter 7. A Study on Machine Learning-Based Water Quality Assessment and Wastewater Treatment -- Chapter 8. Explaining the Importance of Water Quality Parameters for Prediction of the Quality of Water Using SHAP Value -- Chapter 9. Classification of Quality of Water Using Machine Learning -- Compilation of References -- Related References -- About the Contributors -- Index.
5203 ▼a "The emergence of a plethora of water contaminants as a result of industrialization has introduced complexity to water treatment processes. Such complexity may not be easily resolved using deterministic approaches. Artificial intelligence (AI) has found relevance and applications in almost all sectors and academic disciplines, including water treatment and management. AI provides dependable solutions in the areas of optimization, suspect screening or forensics, classification, regression, and forecasting, all of which are relevant for water research and management.Artificial Intelligence Applications in Water Treatment and Water Resource Management explores the different AI techniques and their applications in wastewater treatment and water management. The book also considers the benefits, challenges, and opportunities for future research. Covering key topics such as water wastage, irrigation, and energy consumption, this premier reference source is ideal for computer scientists, industry professionals, researchers, academicians, scholars, practitioners, instructors, and students."-- ▼c Provided by publisher.
588 ▼a Description based on online resource; title from digital title page (viewed on September 15, 2023).
590 ▼a Added to collection customer.56279.3
650 0 ▼a Water ▼x Purification.
650 0 ▼a Artificial intelligence ▼x Industrial applications.
650 0 ▼a Water ▼x Purification ▼x Technological innovations.
650 6 ▼a Eau ▼x E?puration.
650 6 ▼a Intelligence artificielle ▼x Applications industrielles.
650 6 ▼a Eau ▼x E?puration ▼x Innovations.
7001 ▼a Shikuku, Victor, ▼d 1986-, ▼e editor.
7102 ▼a IGI Global, ▼e publisher.
77608 ▼i Print version: ▼z 1668467917 ▼z 9781668467916
830 0 ▼a Advances in environmental engineering and green technologies (AEEGT) book series.
85640 ▼3 EBSCOhost ▼u https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=3669454
938 ▼a EBSCOhost ▼b EBSC ▼n 3669454
990 ▼a 관리자
994 ▼a 92 ▼b N$T