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|a 9783319333281
|9 978-3-319-33328-1
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|a 10.1007/978-3-319-33328-1
|2 doi
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|a 333.7
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|a Khazaii, Javad.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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|a Advanced Decision Making for HVAC Engineers
|h [electronic resource] :
|b Creating Energy Efficient Smart Buildings /
|c by Javad Khazaii.
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|a 1st ed. 2016.
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|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2016.
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|a XVII, 191 p. 40 illus. in color.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
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|a online resource
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|a text file
|b PDF
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|a Introduction -- Heat Transfer in a Nutshell -- Load Calculation and Energy Modeling -- Data Centers -- Healthcare Facilities -- Laboratories -- Cleanrooms -- Commercial Kitchens and Dining Facilities -- Introduction -- Analytical Hierarchy Process -- Genetic Algorithm Optimization -- Pareto Base Optimization -- Decision making under uncertainty -- Agent Based Modeling -- Artificial Neural Network -- Fuzzy Logic -- Game Theory -- Buildings of the Future.
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|a This book focuses on some of the most energy-consuming HVAC systems; illuminating huge opportunities for energy savings in buildings that operate with these systems. The main discussion is on, cutting-edge decision making approaches, and algorithms in: decision making under uncertainty, genetic algorithms, fuzzy logic, artificial neural networks, agent based modeling, and game theory. These methods are applied to HVAC systems, in order to help designers select the best options among the many available pathways for designing and the building of HVAC systems and applications. The discussion further evolves to depict how the buildings of the future can incorporate these advanced decision-making algorithms to become autonomous and truly 'smart'.
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|a Energy policy.
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|a Energy and state.
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|a Buildings-Environmental engineering.
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|a Electric power production.
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|a Operations research.
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|a Energy Policy, Economics and Management.
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|a Building Physics, HVAC.
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|a Electrical Power Engineering.
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|a Mechanical Power Engineering.
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|a Operations Research and Decision Theory.
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|a SpringerLink (Online service)
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|t Springer Nature eBook
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|i Printed edition:
|z 9783319333274
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|i Printed edition:
|z 9783319333298
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|i Printed edition:
|z 9783319814865
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|u https://doi.uam.elogim.com/10.1007/978-3-319-33328-1
|z Texto Completo
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|a ZDB-2-ENE
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|a ZDB-2-SXEN
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|a Energy (SpringerNature-40367)
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950 |
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|a Energy (R0) (SpringerNature-43717)
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