车辆排放对大气污染的模糊监测及神经预测模型

以车辆排放对大气污染为研究对象，在综合考虑车辆排放对大气污染影响因素的基础上，构建车辆排放对大气污染的模糊监测指标体系。通过模糊集的相关理论，建立车辆排放对大气污染的监测模型，并采用熵权法确定指标权重系数，利用模糊可变模型计算监测值对各监测级别的综合相对隶属度，界定车辆排放对大气污染的等级程度。通过大数据分析，根据神经网络理论构建车辆排放对大气污染的预测模型，并利用MATLAB软件实现预测过程。应用结果表明，车辆排放对大气污染的监测模型可有效界定车辆排放对大气的污染程度，车辆排放预测模型能预测短时间内大气中污染物浓度，具有较高可信度，研究成果对解决车辆排放对大气污染有较好的指导意义和实用价值。

The fuzzy monitoring and neural prediction model of vehicle emissions on ai r pollution

This paper ,taking the vehicle emissions on air pollution as the research object , analyzes the influence factors ,constructs a fuzzy monitoring index system w hich applies to the vehicle emissions on air pollution ,and uses the related theory of fuzzy sets to establish the monitoring model of vehicle emissions on air pollution .In this model ,the entropy weight method is used to determine the index weight ,then to calculate the comprehensive relative membership degree of each monitoring value by the fuzzy variable model ,and finally ,defines the level of vehicle emissions on air pollution .Through the large data analysis , a forecasting model is built of vehicle emission on air pollution by neural network theory , and then complete with the forecasting progress by MATLAB .The application result shows that this monitoring model can define the degree of air pollution and has high credibility in concentration forecasting of air pollutant .Research result show s a very good guiding significance and practical value .