scholarly journals Online Incremental Learning of the Terrain Traversal Cost in Autonomous Exploration

Author(s):  
Milos Pragr ◽  
Petr Cizek ◽  
Jan Bayer ◽  
Jan Faigl
2021 ◽  
Vol 105 ◽  
pp. 107255
Author(s):  
Si-si Zhang ◽  
Jian-wei Liu ◽  
Xin Zuo

2013 ◽  
Vol 765-767 ◽  
pp. 1451-1455 ◽  
Author(s):  
Jin Fan ◽  
Xian Kun Zhang ◽  
Xue Tian ◽  
Dong Liu

Topic crawler is a tool for collecting electronic public opinion from the internet. The identification method of topics relevance identification directly affects the acquisition rate of topic crawler. To improve the low information acquisition rate of existing topic crawlers strategy, a modified SVM classifier algorithm which is based on online incremental learning is proposed. The idea of algorithm is to remove samples that affect the training set greatly in the historical training set, and then to re-train the historical set and the incremental set to obtain a complete training set. A framework of topic crawler is constructed on the basis of this algorithm. The results of experiments show that, this method can effectively improve the acquisition rate of the crawler.


2021 ◽  
Author(s):  
Shipeng Yan ◽  
Jiale Zhou ◽  
Jiangwei Xie ◽  
Songyang Zhang ◽  
Xuming He

Author(s):  
Kirthanaa Raghuraman ◽  
Monisha Senthurpandian ◽  
Monisha Shanmugasundaram ◽  
Bhargavi ◽  
V. Vaidehi

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