The Economics of Livestock Disease Insurance Concepts, Issues and International Case Studies | 18.61 MB
Title: The Economics of Livestock Disease Insurance Concepts, Issues and International Case Studies
Author: Grannis, Jennifer L, Green, John W, Thilmany, Dawn D, Hoag, Dana L, Koontz, Stephen R
Category: Nonfiction, Science & Nature, Technology, Engineering, Environmental, Business & Finance
Language: English | 284 Pages | ISBN: 0851990770
Description:
This three-volume set delves into the intersection of cutting-edge technology and environmental science to address pressing challenges in the water sector and develop digitalization solutions that can have practical implementation in decision-making and management of wastewater treatment.
With special emphasis on the integration of big data, artificial intelligence (AI), and machine learning, Volume 1 provides theoretical, foundational, and practical insights for water systems optimization, resource conservation, and sustainable operations; Volume 2 explores pathways to a sustainable, low-carbon future by emphasizing predictive maintenance, energy-efficient operations, leak detection, and climate-adaptive planning; and Volume 3 pursues real-world applications in water supply, wastewater treatment, and flood management through a host of diverse and well-researched case studies.
Ideal for water engineers, researchers, policymakers, and sustainability practitioners, this handbook serves as an essential guide for professionals seeking to harness digitalization for smarter, data-driven water management. It is equally valuable for graduate students, academics, and technology innovators interested in bridging the gap between emerging AI capabilities and practical water sector applications.
This three-volume set delves into the intersection of cutting-edge technology and environmental science to address pressing challenges in the water sector and develop digitalization solutions that can have practical implementation in decision-making and management of wastewater treatment.
With special emphasis on the integration of big data, artificial intelligence (AI), and machine learning, Volume 1 provides theoretical, foundational, and practical insights for water systems optimization, resource conservation, and sustainable operations; Volume 2 explores pathways to a sustainable, low-carbon future by emphasizing predictive maintenance, energy-efficient operations, leak detection, and climate-adaptive planning; and Volume 3 pursues real-world applications in water supply, wastewater treatment, and flood management through a host of diverse and well-researched case studies.
Ideal for water engineers, researchers, policymakers, and sustainability practitioners, this handbook serves as an essential guide for professionals seeking to harness digitalization for smarter, data-driven water management. It is equally valuable for graduate students, academics, and technology innovators interested in bridging the gap between emerging AI capabilities and practical water sector applications.
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