人工神经网络和计算智能

R. King
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引用次数: 25

摘要

人工神经网络已广泛应用于电力系统的控制、负荷预测、监测、诊断和分析等领域。它们在电力公用事业的文献和产品线中的流行几乎使“智能”这个描述符过度使用。然而,人工神经网络没有智商。它们表现出人类通常与智能联系在一起的属性:学习、交流、感知或推理的能力。本教程的目的是对人工神经网络和计算智能有一个基本的了解。这是通过讨论人工神经网络的历史和生物学基础,并从一个简单的人工神经网络分类中回顾两个代表性的体系结构来完成的。在本教程中,使用术语体系结构意味着网络拓扑和学习规则。还推荐进一步研究的资源和免费软件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial neural networks and computational intelligence
Artificial neural networks have been applied to power systems in such areas as control, load forecasting, monitoring, diagnosis, and analysis. Their prevalence in the literature and product lines of the electric utility industry has almost overworked the descriptor "intelligent". However, ANNs do not have an IQ. They exhibit attributes that humans often associate with intelligence: an ability to learn, to communicate, to perceive, or to reason. The objective of this tutorial is to give a basic understanding of ANNs and computational intelligence. This is accomplished by discussing the historical and biological basis of ANNs and reviewing two representative architectures from a simple taxonomy for ANNs. In this tutorial, the use of the term architecture is used to imply both a network topology and a learning rule. Resources for further studies and free software are also recommended.
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