Road Commercial Passenger Vehicles Ownership Forecast Based On Support Vector Machine

Road commercial passenger vehicles is the first prerequisite for production of roadpassenger transport enterprises, the road passenger transport, transport, road operationof passenger car ownership is decided the passenger transport companies to providecapacity to meet passenger demand, that is the extent to which highway operation of busownership in the future development and provide a reference for the configuration ofthe road passenger transport capacity to adjust and operating lines.First of all, from the status of road passenger transport, the development of roadpassenger demand, the proportion of road passenger transport in passenger transport, aswell as the future trend of development, analyze the development trend of the researchroad operation of bus ownership to keep abreast of the road passenger transport industrythe overall situation, the owner of the bus and highway operations, the analysis offactors affecting highway operation of bus ownership, and established the index systemof highway operation of bus ownership.Then it researches the home and abroad more common forecasting methods, studythe advantages and disadvantages of various methods and the applicable conditions toexplore for this article forecasting methods, and analyzed to build the regressionprediction model based on principal component analysis, application of the predictionmodel highway operation of bus ownership to predict and analyze the precision of themodel.With handed results and the basis from above it studies the ways and means tobuild road operation of passenger car ownership forecasting model based on supportvector machines, the impact of key model parameters on the prediction accuracy, theresearch parameter optimization in the parameter selection stage using the k-fold crossvalidation repeated trials, in order to determine tolerance value of the penalty parameterC and kernel parameters, determine the final form of the model and the modelpredictions were compared with the regression model predictions.Finally, it predicts the impact indicators for highway operation of bus ownership,and were applied to the support vector machine prediction model has been establishedand the regression prediction model to predict the Heilongjiang Province in2012and2020road operation of bus ownership, evaluation of model predictions credibility, andapply the predictions to infer the size and pace of development of HeilongjiangProvince future road operation of bus ownership.