Computational Intelligent Data Analysis for Sustainable Development
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Going beyond performing simple analyses, researchers involved in the highly dynamic field of computational intelligent data analysis design algorithms that solve increasingly complex data problems in changing environments, including economic, environmental, and social data. This volume presents novel methodologies for automatically processing these types of data to support rational decision making for sustainable development. Through numerous case studies and applications, it illustrates important data analysis methods, including mathematical optimization, machine learning, signal processing,…mehr

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Produktbeschreibung
Going beyond performing simple analyses, researchers involved in the highly dynamic field of computational intelligent data analysis design algorithms that solve increasingly complex data problems in changing environments, including economic, environmental, and social data. This volume presents novel methodologies for automatically processing these types of data to support rational decision making for sustainable development. Through numerous case studies and applications, it illustrates important data analysis methods, including mathematical optimization, machine learning, signal processing, and temporal and spatial analysis, for quantifying and describing sustainable development problems.
Autorenporträt
Ting Yu, Ph.D., is an honorary research fellow in the Integrated Sustainability Analysis Group at the University of Sydney. He is also a transport modeler for the Transport for NSW. His research interests include machine learning, data mining, parallel computing, applied economics, and sustainability analysis. He earned a Ph.D. in computing science from the University of Technology, Sydney. Nitesh Chawla, Ph.D., is an associate professor in the Department of Computer Science and Engineering, director of the Interdisciplinary Center for Network Science and Applications, and director of the Data Inference Analysis and Learning Lab at the University of Notre Dame. A recipient of multiple awards for research and teaching, Dr. Chawla is chair of the IEEE Computational Intelligence Society Data Mining Technical Committee and associate editor of IEEE Transactions on Systems, Man and Cybernetics (Part B) and Pattern Recognition Letters. His research focuses on machine learning, data mining, and network science. Simeon Simoff, Ph.D., is dean of the School of Computing, Engineering and Mathematics at the University of Western Sydney. He is also a founding director and fellow of the Institute of Analytics Professionals of Australia. He serves on the American Society of Civil Engineering Technical Committees on Data and Information Management and on Intelligent Computing and is an editor of the Australian Computer Society's Conferences in Research and Practice in Information Technology.