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The Usage of Artificial Neural Networks for Intelligent Lighting Control Based on Resident's Behavioural Pattern

机译:基于居民行为模式的人工神经网络在智能照明控制中的应用

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Learning from the behavior of the resident is essential in order to adapt the lightning system and to provide intelligent lighting control based on behavior patterns. Different homes have different conditions and habits which have to be taken into account for the intelligent system to be useful. However, with passage of time even deeply ingrained habits are subject to change. Therefore, a truly intelligent system has to respond to the changing and diverse environment. An intelligent lighting control system that employs artificial neural networks for on-line learning and adaptation and is based on resident's behavioural patterns is presented in this paper. In order to manage problems related to constant increase of data and dynamic environments, a group of algorithms have been improved by implementing a similarity threshold based data replacement algorithm that has been experimentally tested and compared with alternative algorithms.
机译:为了适应闪电系统并根据行为模式提供智能的照明控制,从居民的行为中学习是必不可少的。不同的家庭有不同的条件和习惯,必须使用这些条件和习惯才能使智能系统发挥作用。但是,随着时间的流逝,即使是根深蒂固的习惯也可能会发生变化。因此,真正的智能系统必须应对不断变化的多样化环境。本文提出了一种基于人的行为模式的,采用人工神经网络进行在线学习和自适应的智能照明控制系统。为了管理与数据不断增加和动态环境有关的问题,通过实现基于相似度阈值的数据替换算法,对一组算法进行了改进,该算法已通过实验测试并与替代算法进行了比较。

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