基于BP神经网络的智能家居灯光照明控制方法

ntelligent Home Lighting Control Method Based on BP Neural Network

现有控制灯光的方法存在调节光照误差过大的问题,本文基于此引入BP神经网络,开展智能家居环境中灯光控制方法研究。建立智能家居光环境模型,利用BP神经网络对模型进行训练,实现对灯光亮度的自动调整。通过对比实验证明,新的控制方法调节光照与习惯光照更接近,调节误差得到有效控制,具备极高控制精度。

The existing methods of controlling lighting have the problem of excessive illumination error,and this paper introduces BP neural network to carry out the research on lighting control methods in smart home environment.Establish a smart home light environment model,and use BP neural network to train the model to realize automatic adjustment of light brightness.Through comparative experiments,it is proved that the new control method is closer to the conventional light,and the adjustment error is effectively controlled,and the control accuracy is extremely high.