New variogram modeling method using MGGP and SVR-Reference-Cited by-同舟云学术

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New variogram modeling method using MGGP and SVR

Published:2016-02-16 Issue:2 Volume:9 Page:197-213
ISSN:1865-0473
Container-title:Earth Science Informatics
language:en
Short-container-title:Earth Sci Inform

Author:

Han Changik,Wang Jiyang,Zheng Mingguo,Wang Ende,Xia Jianming,Li GwangSu,Choe Sunchol

Funder

the Research of High-grade Iron Ore Formation Mechanism and Prediction of China

the Fundamental Research Funds for the Graduate Innovation State Education Ministry

Publisher

Springer Science and Business Media LLC

Subject

General Earth and Planetary Sciences

Link

http://link.springer.com/content/pdf/10.1007/s12145-016-0251-9.pdf

Reference81 articles.

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2. Atteia O, Dubois JP, Webster R (1994) Geostatistical analysis of contamination in the Swiss Jura. Environ Pollut 86:315–327

3. Basak S, Dixit U, Davim J (2007) Application of radial basis function neural networks in optimization of hard turning of AISI D2 cold-worked tool steel with a ceramic tool. Proc Inst Mech Eng B J Eng Manuf 221:987–998

4. Byvatov E, Schneider G (2003) Support vector machine applications in bioinformatics. Appl Bioinforma 2:67–77

5. Çaydas U, Ekici S (2012) Support vector machines models for surface roughness prediction in CNC turning of AISI 304 austenitic stainless steel. J Intell Manuf 23:639–650. doi: 10.1007/s10845-010-0415-2

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