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Computational intelligent data analysis for sustainable development / edited by Ting Yu, Nitesh Chawla, Simeon Simoff.

Contributor(s): Material type: TextTextSeries: Chapman & Hall/CRC data mining and knowledge discovery seriesPublication details: Boca Raton : Taylor & Francis, 2013.Description: xviii, 414 p. : ill., maps ; [ca. 23-29] cmISBN:
  • 9781439895948
Subject(s): LOC classification:
  • HC79.E5 C61244 2013
Available additional physical forms:
  • Also available as an electronic resource.
Contents:
section 1. Integrated sustainability analysis -- section 2. Computational intelligent data analysis for climate change -- section 3. Computational intelligent data analysis for biodiversity and species conservation -- section 4. Computational intelligent data analysis for smart grid and renewable energy -- section 5. Computational intelligent data analysis for sociopolitical sustainability.
Summary: "Intelligent data analysis techniques offer powerful solutions to collecting and analyzing vast quantities of environmental and economic data, which lead to better decision making for sustainable development. This volume is the first to discuss the treatment of intelligent data analysis techniques in sustainable development applications. The book describes the emerging use of data mining, machine learning, artificial neural networks, data visualization, knowledge discovery, GIS, and other technologies to tackle environmental, economic, and social issues, including climate change, risk management, and population growth"-- Provided by publisher.
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Includes bibliographical references and index.

section 1. Integrated sustainability analysis -- section 2. Computational intelligent data analysis for climate change -- section 3. Computational intelligent data analysis for biodiversity and species conservation -- section 4. Computational intelligent data analysis for smart grid and renewable energy -- section 5. Computational intelligent data analysis for sociopolitical sustainability.

"Intelligent data analysis techniques offer powerful solutions to collecting and analyzing vast quantities of environmental and economic data, which lead to better decision making for sustainable development. This volume is the first to discuss the treatment of intelligent data analysis techniques in sustainable development applications. The book describes the emerging use of data mining, machine learning, artificial neural networks, data visualization, knowledge discovery, GIS, and other technologies to tackle environmental, economic, and social issues, including climate change, risk management, and population growth"-- Provided by publisher.

Also available as an electronic resource.

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