基于BP神经网络模型的森林空气质量评价

Evaluation of forest air quality based on BP neural network

摘要:

为解决森林地区的空气评价问题,基于BP神经网络技术进行建立森林空气质量评价模型的研究,根据森林空气低污染、负离子高含量的特点,以SO2、NO2、PM10、O3和负离子为评价指标建立模型,并运用MATLAB工具软件实现.以伊春五营森林和城镇空气质量数据为实例,对模型进行对比检测,评价结果分别为9.13和8.56分,表明模型实用且可行.

Abstract:

To solve the problem about the evaluation of forest air,an eveluation model based on BP neural network was studied.According to the characteristics of forest air with low pollution and high-volume negative ions,the model was constructed by MATLAB with the indices of SO2,NO2,PM10,O3 and negative ion.The evaluation results are 9.13 and 8.56 respectively by comparing the statistic data of air quality in forest with those in the town in Yichun,which proves the feasibility of the model.