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Computational Sustainability [electronic resource] / edited by Jörg Lässig, Kristian Kersting, Katharina Morik.

Contributor(s): Lässig, Jörg [editor.] | Kersting, Kristian [editor.] | Morik, Katharina [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Studies in Computational Intelligence: 645Publisher: Cham : Springer International Publishing : Imprint: Springer, 2016Edition: 1st ed. 2016.Description: VI, 276 p. 98 illus., 75 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319318585.Subject(s): Computational intelligence | Application software | Energy policy | Energy and state | Software engineering | Technological innovations | Computational Intelligence | Computer and Information Systems Applications | Energy Policy, Economics and Management | Software Engineering | Innovation and Technology ManagementAdditional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online
Contents:
Sustainable Development and Computing - an Introduction -- Wind Power Prediction with Machine Learning -- Statistical Learning for Short-Term Photovoltaic Power Predictions -- Renewable Energy Prediction for Improved Utilization and Efficiency in Datacenters and Backbone Networks -- A Hybrid Machine Learning and Knowledge Based Approach to Limit Combinatorial Explosion in Biodegradation Prediction -- Feeding the World with Big Data: Uncovering Spectral Characteristics and Dynamics of Stressed Plants -- Global Monitoring of Inland Water Dynamics: State-of-the-art, Challenges, and Opportunities -- Installing Electric Vehicle Charging Stations City-Scale: How Many and Where? -- Computationally Efficient Design Optimization of Compact Microwave and Antenna Structures -- Sustainable Industrial Processes by Embedded Real-Time Quality Prediction -- Relational Learning for Sustainable Health -- ARM Cluster for Performant and Energy-efficient Storage.
In: Springer Nature eBookSummary: The book at hand gives an overview of the state of the art research in Computational Sustainability as well as case studies of different application scenarios. This covers topics such as renewable energy supply, energy storage and e-mobility, efficiency in data centers and networks, sustainable food and water supply, sustainable health, industrial production and quality, etc. The book describes computational methods and possible application scenarios.
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Sustainable Development and Computing - an Introduction -- Wind Power Prediction with Machine Learning -- Statistical Learning for Short-Term Photovoltaic Power Predictions -- Renewable Energy Prediction for Improved Utilization and Efficiency in Datacenters and Backbone Networks -- A Hybrid Machine Learning and Knowledge Based Approach to Limit Combinatorial Explosion in Biodegradation Prediction -- Feeding the World with Big Data: Uncovering Spectral Characteristics and Dynamics of Stressed Plants -- Global Monitoring of Inland Water Dynamics: State-of-the-art, Challenges, and Opportunities -- Installing Electric Vehicle Charging Stations City-Scale: How Many and Where? -- Computationally Efficient Design Optimization of Compact Microwave and Antenna Structures -- Sustainable Industrial Processes by Embedded Real-Time Quality Prediction -- Relational Learning for Sustainable Health -- ARM Cluster for Performant and Energy-efficient Storage.

The book at hand gives an overview of the state of the art research in Computational Sustainability as well as case studies of different application scenarios. This covers topics such as renewable energy supply, energy storage and e-mobility, efficiency in data centers and networks, sustainable food and water supply, sustainable health, industrial production and quality, etc. The book describes computational methods and possible application scenarios.

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