Study on Approximation Methods with Chebyshev Polynomial Models

Jian Jun Lin; Yang Sun; Yue Qiang Zhang

doi:10.4028/www.scientific.net/AMM.733.885

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A Kriging Model-Based Approximation Technique for Predictive Design
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Solving Computational Expensive Problems with a Response Surface Surrogate Models
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Surrogating for High Dimensional Computationally Expensive Multi-Modal Functions with Elliptical Basis Function Models
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Study on Approximation Methods with Chebyshev Polynomial Models
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Extraction of Inertial Parameters Based on 3D-Voxel Model of Equal Volume
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Application of the Combination Prediction Model in Forecasting the Short-Term Wind Power
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Application Research on Improved Fusion Algorithm Based on BP Neural Network and POS
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Group Synchronization Analysis of Network by Matrix Theory
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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 733Study on Approximation Methods with Chebyshev...

Study on Approximation Methods with Chebyshev Polynomial Models

Abstract:

Modern automobile design technology often employed finite element analysis and computational fluid dynamics, which are computational expense and highly time cost and need to employ approximation techniques. We herein study a Chebyshev Polynomial Model-based approximation technique, and employ it for predictive design. Firstly, we investigated the multi-valuable function prediction on the model precision. We also employed cross-validation as error analysis method. The computational results from expensive optimization of CEC 2014 tested our predictive methods. The experimental results showed that the proposed method is suitable for solving the low dimensional function prediction problems.