School of Management, Harbin Institute of Technology, 150001 Harbin, China; School of Management, Changshu Institute of Technology, 215500 Changshu, China
A support vector machine is a machine learning method based on the statistical learning theory and structural risk minimization. The support vector machine is a much better method than ever, because it may solve some actual problems in small samples, high dimension, nonlinear and local minima etc. The article utilizes the theory and method of support vector machine (SVM) regression and establishes the regressive model based on the least square support vector machine (LS-SVM). Through predicting passenger flow on Hangzhou highway in 2000–2008, the paper shows that the regressive model of LS-SVM has much higher accuracy and reliability of prediction, and therefore may effectively predict passenger flow on the highway.
Hu, Y., Wu, C., & Liu, H. (2011). Prediction of passenger flow on the highway based on the least square suppoert vector machine. Transport, 26(2), 197-203. https://doi.org/10.3846/16484142.2011.593121
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.