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Artificial Neural Networks and Genetic Algorithms in Energy Applications in Buildings

机译:建筑物能源应用中的人工神经网络和遗传算法

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The major objective of this chapter is to illustrate how artificial neural networks (ANNs) and genetic algorithms (GAs) may play an important role in modelling and prediction of the performance of various energy systems in buildings. The chapter initially presents artificial neural networks and genetic algorithms and outlines an understanding of how they operate by way of presenting a number of problems in the different disciplines of energy applications in buildings including environmental parameters, renewable energy systems, naturally ventilated buildings, energy consumption and conservation, and HVAC systems. The various applications are presented in a thematic rather than a chronological or any other order. Results presented in this chapter are testimony of the potential of artificial neural networks and genetic algorithms as design tools in many areas of energy applications in buildings.
机译:本章的主要目的是说明人工神经网络(ANN)和遗传算法(GA)如何在建筑物的各种能源系统的性能建模和预测中发挥重要作用。本章首先介绍了人工神经网络和遗传算法,并通过介绍建筑物能源应用的不同学科中的许多问题(包括环境参数,可再生能源系统,自然通风的建筑物,能耗和保护和HVAC系统。各种应用程序是按主题而不是按时间顺序或任何其他顺序显示的。本章介绍的结果证明了人工神经网络和遗传算法作为建筑物能源应用的许多领域中的设计工具的潜力。

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