基于神经网络的空气质量采集系统的设计

Design of Air Quality Information-sampling System Based on BP Neural Network

空气质量采集对空气清新器的管理和控制起着关键的作用。经过对复杂非线性的空气流分析,结合信息采集及智能控制技术,本文提出一种新的空气质量信息采集系统设计方法。该方法利用多传感器力求准确采集空气质量信息,并通过神经网络建立起空气质量的预测模型,该预测模型的建立有助于空气清新器控制策略的优化。

Air quality information-sampling is very important to manage and control air cleaner. Because of complexity and nonlinear of air flow, this paper proposes a design method of air quality information-sampling system based on BP neural network, combined with information-sampling and intelligent-control technology . The method can build the prediction model of air quality from information-sampling system using multi-sensors, and this prediction model is a pre-requisite to optimize the control policy of air clea...