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Fundamentals of Artificial Neural Networks
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Fundamentals of Artificial Neural Networks

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Fundamentals of Building Energy Dynamics assesses how and why buildings use energy,and how energy use and peak demand can be reduced. It provides a basis for integrating energyefficiency and solar approaches in ways that will allow building owners and designers to balance theneed to minimize initial costs, operating costs, and life-cycle costs with need to maintain reliablebuilding operations and enhance environmental quality both inside and outside the building. Chapterstrace the development of building energy systems and analyze the demand side of solar applicationsas a means for determining what portion of a building's energy requirements can potentially be metby solar energy.Following the introduction, the book provides an overview of energy use patterns inthe aggregate U.S. building population. Chapter 3 surveys work on the energy flows in an individualbuilding and shows how these flows interact to influence overall energy use. Chapter 4 presents theanalytical methods, techniques, and tools developed to calculate and analyze energy use inbuildings, while chapter 5 provides an extensive survey of the energy conservation and managementstrategies developed in the post-energy crisis period.The approach taken is a commonsensical one,starting with the proposition that the purpose of buildings is to house human activities, and thatconservation measures that negatively affect such activities are based on false economies. The goalis to determine rational strategies for the design of new buildings, and the retrofit of existingbuildings to bring them up to modern standards of energy use. The energy flows examined are bothlarge scale (heating systems) and small scale (choices among appliances).Solar Heat Technologies:Fundamentals and Applications, Volume 4

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Joshua D. Angrist is Ford Professor of Economics at MIT.

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