-
1
-
-
79957992809
-
A review of data mining applications for quality improvement in manufacturing industry
-
KÖKSAL G, BATMAZ Ì, TESTIK M C. A review of data mining applications for quality improvement in manufacturing industry[J]. Expert Systems with Applications, 2011, 38: 13448-13467.
-
(2011)
Expert Systems with Applications
, vol.38
, pp. 13448-13467
-
-
Köksal, G.1
Batmaz, I.2
Testik, M.C.3
-
3
-
-
37349043624
-
Method of determining the importance ratings of customer requirements improvement for house of quality
-
TANG Jiafu, YAO Jianming, et al. Method of determining the importance ratings of customer requirements improvement for house of quality[J]. Chinese Journal of Mechanical Engineering, 2008, 43(11): 110-118.
-
(2008)
Chinese Journal of Mechanical Engineering
, vol.43
, Issue.11
, pp. 110-118
-
-
Tang, J.1
Yao, J.2
-
4
-
-
0035427895
-
QFD-Based optimization planning for process quality in NC machining
-
ZHENG Lianyu, TANG Xiaoqing, WANG Shuchun. QFD-Based optimization planning for process quality in NC machining[J]. Chinese Journal of Mechanical Engineering, 2001, 37(8): 38-42.
-
(2001)
Chinese Journal of Mechanical Engineering
, vol.37
, Issue.8
, pp. 38-42
-
-
Zheng, L.1
Tang, X.2
Wang, S.3
-
5
-
-
20444412298
-
Customer-oriented quality improvement in mass customization
-
TANG Xiaoqing, WANG Xuecong. Customer-oriented quality improvement in mass customization[J]. Chinese Journal of Mechanical Engineering, 2005, 41(5): 200-204.
-
(2005)
Chinese Journal of Mechanical Engineering
, vol.41
, Issue.5
, pp. 200-204
-
-
Tang, X.1
Wang, X.2
-
6
-
-
33646433948
-
Data mining for improving the quality of manufacturing: A feature set decomposition approach
-
ROKACH L, MAIMON O. Data mining for improving the quality of manufacturing: A feature set decomposition approach[J]. Journal of Intelligent Manufacturing, 2006, 17(3): 285-299.
-
(2006)
Journal of Intelligent Manufacturing
, vol.17
, Issue.3
, pp. 285-299
-
-
Rokach, L.1
Maimon, O.2
-
11
-
-
33748252478
-
Automatic clinical image segmentation using pathological modeling, PCA and SVM
-
LI S, FEVENS T, KRZYZAK A, et al. Automatic clinical image segmentation using pathological modeling, PCA and SVM[J]. Engineering Applications of Artificial Intelligence, 2006, 19(4): 403-410.
-
(2006)
Engineering Applications of Artificial Intelligence
, vol.19
, Issue.4
, pp. 403-410
-
-
Li, S.1
Fevens, T.2
Krzyzak, A.3
-
12
-
-
78650205211
-
Evaluation of face recognition techniques using PCA, wavelets and SVM
-
GUMUS E, KILIC N, SERTBAS A, et al. Evaluation of face recognition techniques using PCA, wavelets and SVM[J]. Expert Systems with Applications, 2010, 37(9): 6404-6408.
-
(2010)
Expert Systems with Applications
, vol.37
, Issue.9
, pp. 6404-6408
-
-
Gumus, E.1
Kilic, N.2
Sertbas, A.3
-
13
-
-
77958001182
-
The use of hybrid manifold learning and support vector machines in the prediction of business failure
-
LIN F, YEH C C, LEE M Y. The use of hybrid manifold learning and support vector machines in the prediction of business failure[J]. Knowledge-Based Systems, 2011, 24(1): 95-101.
-
(2011)
Knowledge-Based Systems
, vol.24
, Issue.1
, pp. 95-101
-
-
Lin, F.1
Yeh, C.C.2
Lee, M.Y.3
-
14
-
-
0034704222
-
Nonlinear dimensionality reduction by locally linear embedding
-
ROWEIS S, SAUL L. Nonlinear dimensionality reduction by locally linear embedding[J]. Science, 2000, 290(5500): 2323-2326.
-
(2000)
Science
, vol.290
, Issue.5500
, pp. 2323-2326
-
-
Roweis, S.1
Saul, L.2
-
15
-
-
0034704229
-
A global geometric framework for nonlinear dimensionality reduction
-
TENENBAUM J, SILVA V, LANGFORD J. A global geometric framework for nonlinear dimensionality reduction[J]. Science, 2000, 290(5500): 2319-2322.
-
(2000)
Science
, vol.290
, Issue.5500
, pp. 2319-2322
-
-
Tenenbaum, J.1
Silva, V.2
Langford, J.3
-
16
-
-
0003408420
-
-
Cambridge: The MIT Press
-
SCHÖLKOPF B, SMOLA A J. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond[M]. Cambridge: The MIT Press, 2002.
-
(2002)
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
-
-
SchÖlkopf, B.1
Smola, A.J.2
|