Wind Tunnel Mach Number Prediction Based on the Pruned Feature Subsets Ensemble Method
Publication: Journal of Aerospace Engineering
Volume 30, Issue 4
Abstract
In a wind tunnel, the Mach number in the test section is an important parameter that should be predicted quickly and accurately. In building a Mach number prediction model, large-scale and high-dimensional data is the main issue. To solve the issue, the feature subsets ensemble (FSE) method has been proposed. However, a major drawback of the FSE method is that a large number of submodels are necessarily combined. In this paper, the maximum entropy pruning (MEP) method is proposed to overcome this drawback in the FSE Mach number prediction model. The MEP method refers to finding a subset of submodels that best approximates the entire submodels, while maximizing the quadratic Rényi entropy criterion. Experiments demonstrate that, with much fewer submodels than the FSE and other Mach number models, the MEP-FSE Mach number model can improve the prediction performance (i.e., the generalization), and meet the requirements of the forecasting speed and the root mean square error (less than 0.002).
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Acknowledgments
The authors would like to acknowledge China Aerodynamics Research and Development Center for providing the data. This work is supported by the National Natural Science Foundation of China (Nos. 61672121, 61572093, 61425002, 61402066, 61402067, 61370005, 31370778, 613700057, 61300015, 31170797, 61103057), the Program for Changjiang Scholars and Innovative Research Team in University (No. IRT_15R07), the Program for Liaoning Innovative Research Team in University (No. LT2015002), the Basic Research Program of the Key Lab in Liaoning Province Educational Department (Nos. LZ2014049, LZ2015004), Natural Science Foundation of Liaoning Province (No. 2014020132), Scientific Research Fund of Liaoning Provincial Education (Nos. L2015015, L2014499), and the Program for Liaoning Key Lab of Intelligent Information Processing and Network Technology in University.
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Published In
Journal of Aerospace Engineering
Volume 30 • Issue 4 • July 2017
Copyright
©2017 American Society of Civil Engineers.
History
Received: Jun 8, 2015
Accepted: Oct 19, 2016
Published online: Feb 10, 2017
Published in print: Jul 1, 2017
Discussion open until: Jul 10, 2017
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