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Three Domain Modelling and Uncertainty Analysis

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Three Domain Modelling and Uncertainty Analysis

Three Domain Modelling and Uncertainty Analysis: Applications in Long Range Infrastructure Planning
Springer | Business & Management | July 14 2015 | ISBN-10: 3319195719 | 206 pages | pdf | 9.94 mb

by Atom Mirakyan (Author), Roland de Guio (Author)

From the Back Cover
This book examines in detail the planning and modelling of local infrastructure like energy systems, including the complexities resulting from various uncertainties. Readers will discover the individual steps involved in infrastructure planning in cities and territories, as well as the primary requirements and supporting quality factors. Further topics covered concern the field of uncertainty and its synergies with infrastructure planning. Theories, methodological backgrounds and concrete case studies will not only help readers to understand the proposed methodologies for modelling and uncertainty analysis, but will also show them how these approaches are implemented in practice.

About the Author
Atom Mirakyan studied engineering at the Technical University in Erevan/Armenia (Dipl.-Ing.) and Energy economics (Dipl.-Energy economics) at University of apply science in Darmstadt/Germany. He works at Technical University in Darmstadt as scientist in the field of energy planning and modelling for 5 years. As energy consultant he does energy planning and regional development consultancy for cities and territories for 4 years. In 2007 he joined the European Institute for Energy Research working on energy planning and modelling. His research focus is techno-economic and ecological modelling and planning of energy systems, uncertainty analysis and life cycle assessment. He has also developed methods for innovative support of planning and system design. He has done his PhD about Methodological frameworks for uncertainty analysis in long range integrated energy planning for cities and territories (IEPCT) at University of Strasbourg in 2014. In his PhD frame developed uncertainty analysis approaches have been successfully implemented in megacity studies, in context of energy planning and modelling.

Roland De Guio is professor of Industrial and Systems Engineering at I.N.S.A Graduate School of Science and Technology, Strasbourg France. Since 2000, he manages research activities about applications of theory of inventive problem solving on technical and non-technical multidisciplinary problems. Among his activities he worked on long run technological forecast since 2004 and started his collaboration with EIFER in the area of energy planning in 2010.

Topics
Operation Research / Decision Theory
Energy Systems
Complex Systems
Regional Science