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2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery
Data Mining Modeling for Electromagnetic Scattering Computing
October 18-October 20
ISBN: 978-0-7695-3305-6
| ASCII Text | x | ||
| Weishi Chen, Huansheng Ning, Xia Mao, Baofa Wang, "Data Mining Modeling for Electromagnetic Scattering Computing," Fuzzy Systems and Knowledge Discovery, Fourth International Conference on, vol. 2, pp. 137-140, 2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery, 2008. | |||
| BibTex | x | ||
| @article{ 10.1109/FSKD.2008.578, author = {Weishi Chen and Huansheng Ning and Xia Mao and Baofa Wang}, title = {Data Mining Modeling for Electromagnetic Scattering Computing}, journal ={Fuzzy Systems and Knowledge Discovery, Fourth International Conference on}, volume = {2}, year = {2008}, isbn = {978-0-7695-3305-6}, pages = {137-140}, doi = {http://doi.ieeecomputersociety.org/10.1109/FSKD.2008.578}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - Fuzzy Systems and Knowledge Discovery, Fourth International Conference on TI - Data Mining Modeling for Electromagnetic Scattering Computing SN - 978-0-7695-3305-6 SP137 EP140 A1 - Weishi Chen, A1 - Huansheng Ning, A1 - Xia Mao, A1 - Baofa Wang, PY - 2008 KW - data mining KW - least square KW - support vector regression KW - RCS VL - 2 JA - Fuzzy Systems and Knowledge Discovery, Fourth International Conference on ER - | |||
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/FSKD.2008.578
Scattering computing of metal-media complex structure and structure with cavity has been one of the problems in electromagnetic (EM) scattering theoretical calculation field for many years. A novel method, substituting data mining modeling for original theoretical modeling, is proposed creatively in this paper, attempting to solve the problem by machine learning theory. Data mining modeling is to construct "EM scattering training model", applying regression analysis algorithm on measurement data, to achieve the effect superior to that theoretical modeling can have. Given an example of regressive estimation of some inlet backscattering RCS curve, both original least square algorithm and support vector regression are used, so an applicable data mining model is established initially for EM scattering computing.
Index Terms:
data mining, least square, support vector regression, RCS
Citation:
Weishi Chen, Huansheng Ning, Xia Mao, Baofa Wang, "Data Mining Modeling for Electromagnetic Scattering Computing," fskd, vol. 2, pp.137-140, 2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery, 2008
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