The invention discloses a method and
system for intelligently analyzing the authenticity of motor vehicle
exhaust emission inspection data, and the method comprises the steps: receiving the detection data of motor vehicle
exhaust emission, obtaining multi-source detection data through the combination of the maintenance data of a vehicle and a calibration log of detection equipment, carrying out the
standardization processing of the multi-source detection data, and carrying out the
verification of the multi-source detection data; generating standardized multi-source detection data; wherein the detection data of motor vehicle
exhaust emission comprises a vehicle VIN code, detection time, a
pollutant concentration value and a detection
equipment serial number; based on the standardized multi-source detection data, constructing a detection mechanism association diagram, and detecting abnormal sub-diagrams in the detection mechanism association diagram by adopting an isolated forest model to obtain a mechanism collaborative anomaly recognition result; based on the trained first neural
network model, inputting target vehicle information in the standardized multi-source detection data into the first neural
network model to generate a theoretical emission curve, and calculating a time warping distance between actual measurement data of a target vehicle and the theoretical emission curve to obtain a vehicle trajectory anomaly analysis result; wherein the first neural
network model comprises an LSTM model and / or a pulse neural network; and generating detection
data authenticity early warning information according to a mechanism cooperation abnormity identification result and the vehicle track abnormity analysis result. According to the invention, through multi-
source data fusion and intelligent analysis, the authenticity behavior of the motor vehicle exhaust detection data is effectively identified.