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Energy analysis of a building using artificial neural network: A review

机译:使用人工神经网络对建筑物进行能量分析:综述

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摘要

Artificial neural networks (ANNs) can be used to predict energy consumption more reliably than traditional simulation models and regression techniques. Artificial neural networks are nowadays accepted as an alternative technology offering a way to tackle complex and ill-defined problems. They are not programmed in the traditional way but they are trained using past history data representing the behaviour of a system. They have been used in a number of diverse applications. Results presented in this paper are testimony to the potential of artificial neural networks as a design tool in many areas of building services engineering.
机译:与传统的仿真模型和回归技术相比,人工神经网络(ANN)可以更可靠地预测能耗。如今,人工神经网络已被视为一种替代技术,它提供了一种解决复杂和不确定性问题的方法。它们不是以传统方式编程的,而是使用代表系统行为的过去历史数据进行训练。它们已用于许多不同的应用程序中。本文提出的结果证明了人工神经网络作为建筑服务工程许多领域中的一种设计工具的潜力。

著录项

  • 来源
    《Energy and Buildings》 |2013年第10期|352-358|共7页
  • 作者单位

    Department of Physics, Shoolini University, Bajhol, District Solan, HP 173212, India;

    Department of Environmental Science, Dr. Y S Parmar University of Horticulture & Forestry, Nauni, Solan, HP 173230, India;

    Department of Physics, Shoolini University, Bajhol, District Solan, HP 173212, India;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Artificial neural networks; Energy prediction; Building applications;

    机译:人工神经网络;能量预测;建筑应用;

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