
Computational Sustainability
Springer (Publisher)
Published on 29. April 2016
Book
Hardback
VI, 276 pages
978-3-319-31856-1 (ISBN)
Description
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.
More details
Product info
Book
Series
Edition
1st ed. 2016
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Illustrations
75
23 s/w Abbildungen, 75 farbige Abbildungen
VI, 276 p. 98 illus., 75 illus. in color.
Dimensions
Height: 241 mm
Width: 160 mm
Thickness: 21 mm
Weight
594 gr
ISBN-13
978-3-319-31856-1 (9783319318561)
DOI
10.1007/978-3-319-31858-5
Schweitzer Classification
Other editions
Additional editions

Jörg Lässig | Kristian Kersting | Katharina Morik
Computational Sustainability
Book
09/2018
Springer
€117.69
Shipment within 10-15 days

Jörg Lässig | Kristian Kersting | Katharina Morik
Computational Sustainability
E-Book
04/2016
Springer
€106.99
Available for download
Content
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.