光子学报, 2017, 46 (7): 0710003, 网络出版: 2017-08-09  

基于模糊支持向量机和D-S证据理论的钨矿石初选方法

Ungsten Ore Primary Selection Based on Fuzzy Support Vector Machine and D-S Evidence Theory
作者单位
1 南昌大学 机电工程学院, 南昌 330031
2 江西理工大学 机电工程学院, 江西 赣州 341000
引用该论文

胡发焕, 刘国平, 胡瑢华, 董增文. 基于模糊支持向量机和D-S证据理论的钨矿石初选方法[J]. 光子学报, 2017, 46(7): 0710003.

HU Fa-huan, LIU Guo-ping, HU Rong-hua, DONG Zeng-wen. Ungsten Ore Primary Selection Based on Fuzzy Support Vector Machine and D-S Evidence Theory[J]. ACTA PHOTONICA SINICA, 2017, 46(7): 0710003.

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胡发焕, 刘国平, 胡瑢华, 董增文. 基于模糊支持向量机和D-S证据理论的钨矿石初选方法[J]. 光子学报, 2017, 46(7): 0710003. HU Fa-huan, LIU Guo-ping, HU Rong-hua, DONG Zeng-wen. Ungsten Ore Primary Selection Based on Fuzzy Support Vector Machine and D-S Evidence Theory[J]. ACTA PHOTONICA SINICA, 2017, 46(7): 0710003.

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