CAJ | 학술논문

本文利用BP神经网络理论，构造一个预测轻型轿车排放的BP神经网络模型，经验证，预测模型能较好地对一般轻型轿车排放结果进行定性预测，可以作为简易稳态工况法（ASM）尾气检测前的参考，对节约检测成本、提高一次检测通过率有着较高的实用价值；同时以南京市为例，研究了轻型汽油车行驶里程、使用年限等参数对排放的影响，为有针对性的维修治理提供可靠的依据。
본문이용BP신경망락이론，구조일개예측경형교차배방적BP신경망락모형，경험증，예측모형능교호지대일반경형교차배방결과진행정성예측，가이작위간역은태공황법（ASM）미기검측전적삼고，대절약검측성본、제고일차검측통과솔유착교고적실용개치；동시이남경시위례，연구료경형기유차행사리정、사용년한등삼수대배방적영향，위유침대성적유수치리제공가고적의거。
A model to evaluate the emissions of the light-duty cars is established in this issue, based on the theory of BP neural network. After testing, the prediction model is proved can be used in the emission qualitative prediction of the light-duty cars, and can be used as the reference of the ASM testing in advance, the model can also save the cost of the testing, and is rather practicable in the testing. At the same time, the main effects on the emission of the light-duty vehicles, such as the total mileage and the age of the vehicles, are also studied, in order to provide the reliable basis to the maintenance.