基于VMD-SSA-LSSVM组合的汽车NO排放预测研究

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【关键词】VMD算法；SSA-LSSVM；组合预测模型；排放预测； NOx ；鲁棒性图分类号：U468.3 文献标识码：A 文章编号：1003-8639（2025）07-0114-03

Research on Automotive NO Emission Prediction Based on the Combination of VMD-SSA-LSSVM*

Tuerxun Maimaitiab，Liu Yaloua.b，Cheng Siyiab，Zu Shaopenga，b，Zhao Jiangtaoab lollege of Transportation and Logistics Engineering；b.Intellgent Transportation Engineering Research Center， Xinjiang Agricultural University，Urumqi 830o52，China）

【Abstract】Automobile exhaust emissions are oneof the main sources of urban air polution.To improve the accuracyand robustnessof theemission prediction model，thisarticle proposes toconstructacombined predictionmodel of VMDnoisereductionandSSA-LSSVM.Firstly，theemisiondataofNationalVlight gasoline vehiclesonthe Hetan Expressay in Urumqi were collected through the OBEAS10oO vehicle exhaust gas analysis system.After preprocessing， the VMD algorithm wasused toreduce the noise of the emission sequence.Combinedwith SSAtooptimize the parameters of the LSSVM model，the VMD-SSA-LSSVMcombined model was constructed.And compare it with the LSSVM，SSA-LSSVMand VMD-LSSVM models.The results show that thecombined model hasan RMSEof 0.00220， aMAEofO.00172，andanMAPEof 2.25% inNOxprediction.The accuracyis significantlyimproved compared with the single model，and it can effectively analyze the transient fluctuation characteristics of emissions.

【Key Words】VMD algorithm；SSA-LSSVM；combined prediction model；emisson forecasting；NOx；robustness

汽车尾气排放是城市大气污染的主要来源，其排放的CO、HC、NO和PM占比超 90%[1] 。（剩余2743字）