A driver test appointment examination room recommendation method based on a seasonal index smoothing prediction model

Abstract

The application relates to a driver test appointment test site recommendation method based on a seasonal index smoothing prediction model. The application comprises the following steps: periodically constructing a standardized time sequence according to historical test plan data sets and test appointment data sets of each test site, and performing data completion and abnormal value correction; constructing a seasonal index smoothing prediction model, determining an optimal smoothing coefficient, and training seasonal index smoothing model parameters; predicting estimated appointment numbers and estimated priority interval values of a target test date; determining a test site appointment success rate estimation value of the target test date; correcting the estimated appointment numbers to obtain corrected estimated appointment numbers; determining a scale weight; determining a test site recommendation value, and outputting a test site recommendation result in descending order of the test site recommendation value. The application can improve the perceptibility of the appointment success probability, guide test takers to reasonably distribute among different test sites, and improve test resource utilization.