A Novel SMOTE-Based Classification Approach to Online Data Imbalance Problem

In many practical engineering applications, data are usually collected in online pattern. However, if the classes of these data are severely imbalanced, the classification performance will be restricted. In this paper, a novel classification approach is proposed to solve the online data imbalance problem by integrating a fast and efficient learning algorithm, that is, Extreme Learning Machine (ELM), and a typical sampling strategy, that is, the synthetic minority oversampling technique (SMOTE). To reduce the severe imbalance, the granulation division for major-class samples is made according to the samples’ distribution characteristic, and the original samples are replaced by the obtained granule core to prepare a balanced sample set. In online stage, we firstly make granulation division for minor-class and then conduct oversampling using SMOTE in the region around granule core and granule border. Therefore, the training sample set is gradually balanced and the online ELM model is dynamically updated. We also theoretically introduce fuzzy information entropy to prove that the proposed approach has the lower bound of model reliability after undersampling. Numerical experiments are conducted on two different kinds of datasets, and the results demonstrate that the proposed approach outperforms some state-of-the-art methods in terms of the generalization performance and numerical stability

Kernel Parameter Optimization for Kriging Based on Structural Risk Minimization Principle

An improved kernel parameter optimization method based on Structural Risk Minimization (SRM) principle is proposed to enhance the generalization ability of traditional Kriging surrogate model. This article first analyses the importance of the generalization ability as an assessment criteria of surrogate model from the perspective of statistics and proves the applicability to Kriging. Kernel parameter optimization method is used to improve the fitting precision of Kriging model. With the smoothness measure of the generalization ability and the anisotropy kernel function, the modified Kriging surrogate model and its analysis process are established. Several benchmarks are tested to verify the effectiveness of the modified method under two different sampling states: uniform distribution and nonuniform distribution. The results show that the proposed Kriging has better generalization ability and adaptability, especially for nonuniform distribution sampling

Three-Dimensional CST Parameterization Method Applied in Aircraft Aeroelastic Analysis

Class/shape transformation (CST) method has advantages of adjustable design variables and powerful parametric geometric shape design ability and has been widely used in aerodynamic design and optimization processes. Three-dimensional CST is an extension for complex aircraft and can generate diverse three-dimensional aircraft and the corresponding mesh automatically and quickly. This paper proposes a parametric structural modeling method based on gridding feature extraction from the aerodynamic mesh generated by the three-dimensional CST method. This novel method can create parametric structural model for fuselage and wing and keep the coordination between the aerodynamic mesh and the structural mesh. Based on the generated aerodynamic model and structural model, an automatic process for aeroelastic modeling and solving is presented with the panel method for aerodynamic solver and NASTRAN for structural solver. A reusable launch vehicle (RLV) is used to illustrate the process for aeroelastic modeling and solving. The result shows that this method can generate aeroelastic model for diverse complex three-dimensional aircraft automatically and reduce the difficulty of aeroelastic analysis dramatically. It provides an effective approach to make use of the aeroelastic analysis at the conceptual design phase for modern aircraft

Design and Simulations of a Guide-screw Hand-spike Nose Deflecting Mechanism

AbstractThe nose deflecting mechanism is important in the development of deflectable nose control technology. In this paper,drawbacks of several existing deflection mechanisms are analyzed, and design requirements of the nose deflection mechanism are summarized. Then a Screw-Spike nose deflecting mechanism is established to meet the design requirements. After that, the relationships between nose deflecting angles and rotation of motors are deduced. At last,the ADAMS-MATLAB\Simulink co-simulations are employed to validate that the Screw-Spike mechanism which is of high precision, fast response, large achievable deflecting angles can meet the design requirements