The Application of Support Vector Machines in the Potentiality Evaluation for Revegetation of Dump of Coal Mine
نویسندگان
چکیده
The problem of abandoned land from mining activities is aggravated since the coal boom. Activities of excavating coal exscind natural vegetation and deposit stone on the natural land that modified the natural land contribute to waste farmlands. This paper presents the comparableness of SVMs method to artificial neural networks in the outlier detection problem of high dimensions. Experiments performed on real dataset show that the performance of this method is mostly superior to that of artificial neural networks. The proposed method, SVMs served to exemplify that kernel-based learning algorithms can be employed as an efficient method for evaluating the revegetation potentiality of abandoned lands from coal mining activities. Key-Words: Support Vector Machine, Potentiality Evaluation, Revegetation, dump of coal mine 1 This work was supported by the Sino-Greek Science & Technology cooperation program(2003DF000004) and Asia IT & C project(CN/ASIA IT&C/006(89870) * corresponding author: Daoliang Li (Prof.), Tel: +86-10-62736717, Fax:+86-10-62737679, E-mail:[email protected]
منابع مشابه
Potentiality Evaluation for Revegetation of abandoned lands from coal mining activities based on Support Vector Machine
Activities of excavating coal exscind natural vegetation and deposit stone on the natural land that modified the natural land contribute to waste farmlands. Additionally, pollution of environment, losses of human life, human settlements and the infrastructure are also rising, which certainly demands urgent attention. Revegetation had been considered as a kind of cost-effective means. A reasonab...
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