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Applying least squares support vector machines to the airframe wing-box structural design cost estimation

Applying least squares support vector machines to the airframe wing-box structural design cost estimation,10.1016/j.eswa.2010.05.038,Expert Systems Wi

Applying least squares support vector machines to the airframe wing-box structural design cost estimation  
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This research used the least squares support vector machines (LS-SVM) method to estimate the project design cost of an airframe wing-box structure. We also compared the estimation performance using back-propagation neural networks (BPN) and statistical response surface methodology (RSM). The solution mechanism of the LS-SVM involved a simultaneous searched for the maximal margin as the target, taking into account the error calculated during training phase to determine the estimation problem models. Two case studies involving the wing-box structure was investigated the separate structural parts case and the mixed structural parts case. The test results verified the feasibility of using the LS-SVM as well as its ability to make accurate estimations.
Journal: Expert Systems With Applications - ESWA , vol. 37, no. 12, pp. 8417-8423, 2010
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