基于大数据的智能空气质量预测方法研究

Smart Prediction Method for Air Quality Based on Big Data Technology

本研究针对当前大数据环境,在Hadoop平台下提出了一种基于MapReduce和粒子群算法的并行BP神经网络预测模型(简称MR-PSO-BP模型),并将其用来进行空气质量指数预测。根据实验结果,该预测模型能较好地对城市的空气质量指数进行预测。

Under the Big Data environment,a parallel BP neural network prediction model based on MapReduce and particle swarm optimization algorithm,MR-PSO-BP model for short,is proposed on Hadoop platform,and it is used to predict air quality index.The experimental results show that the model can effectively predict the air quality index of the city.