期刊论文

Chen, Yuantao

英文

Cluster Computing

1386-7857

2019

22

3

7435-7445

10.1007/s10586-018-1772-4

This work is supported by the National Natural Science Foundation of China (Nos. 61772087, 61702052), the Science and Technology Service Platform of Hunan Province (No. 2012TP1001), the Open Research Fund of Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation (No. 2015TP1005), the Changsha Science and Technology Planning (Nos. KQ1703018, KQ1706064), the Research Foundation of Education Bureau of Hunan Province (Nos. 12C0010, 17A007), the ZOOMLION Intelligent Technology Limited Company (No. 2017zkhx130). We are grateful to anonymous referees for useful comments and suggestions.

本校为第一且通讯机构

In view of the long execution time and low execution efficiency of Support Vector Machine in large-scale training samples, the paper has proposed the online incremental and decremental learning algorithm based on variable support vector machine (VSVM). In deep understanding of the operation mechanism and correlation algorithms for VSVM, each sample has increased training datasets changes and it needs to update the classifier of learning algorithm. Firstly, they are given the online growth amount of learning algorithm taken full advantage of the...