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49 results on '"Shang, Xiaobing"'

9. Nonparametric Modelling of Ship Dynamics Using Puma Optimizer Algorithm-Optimized Twin Support Vector Regression.

Author

Jiang, Lichao, Zhang, Zhi, Lu, Lingyun, Shang, Xiaobing, and Wang, Wei

Subjects
SHIP models, STANDARD deviations, NAVAL architecture, WHITE noise, QUADRATIC programming
Abstract

Ship dynamic models serve as the foundation for designing ship controllers, trajectory planning, and obstacle avoidance. Support vector regression (SVR) is a commonly used nonparametric modelling method for ship dynamics. Achieving high accuracy SVR models requires a substantial amount of training samples. Additionally, as the number of training samples increases, the computational efficiency for solving the quadratic programming problem (QPP) of SVR decreases. Ship controllers demand dynamic models with both high accuracy and computational efficiency. Therefore, to enhance the prediction accuracy and computational efficiency of SVR, this paper proposes a nonparametric modelling method based on twin SVR (TSVR). TSVR replaces a large QPP with a set of smaller QPPs, significantly enhancing generalizability and computational efficiency. To further improve the predictive accuracy of TSVR, the puma optimizer algorithm is employed to determine the optimal hyperparameters. The performance of the proposed method is validated using a Mariner class vessel. Gaussian white noise is introduced into the modelling data to simulate measurement error. The TSVR model accurately predicts various zigzag and turning circle manoeuvring motions under disturbance conditions, demonstrating its robustness and generalizability. Compared to the SVR model, the TSVR model achieves lower root mean square error and computational time, confirming its superior predictive accuracy and computational efficiency. [ABSTRACT FROM AUTHOR]

Published
2024
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13. A Moment Independent Based Importance Measure with Hybrid Uncertainty

Author

Shang, Xiaobing, Chao, Tao, Ma, Ping, Barbosa, Simone Diniz Junqueira, Series editor, Chen, Phoebe, Series editor, Filipe, Joaquim, Series editor, Kotenko, Igor, Series editor, Sivalingam, Krishna M., Series editor, Washio, Takashi, Series editor, Yuan, Junsong, Series editor, Zhou, Lizhu, Series editor, Mohamed Ali, Mohamed Sultan, editor, Wahid, Herman, editor, Mohd Subha, Nurul Adilla, editor, Sahlan, Shafishuhaza, editor, Md. Yunus, Mohd Amri, editor, and Wahap, Ahmad Ridhwan, editor

Published
2017
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14. Design and Application of Exterior Ballistics Simulation and Data Analysis Tool for EMRG

Author

Qi, Dongxing, Ma, Ping, Shang, Xiaobing, Diniz Junqueira Barbosa, Simone, Series editor, Chen, Phoebe, Series editor, Du, Xiaoyong, Series editor, Filipe, Joaquim, Series editor, Kara, Orhun, Series editor, Kotenko, Igor, Series editor, Liu, Ting, Series editor, Sivalingam, Krishna M., Series editor, Washio, Takashi, Series editor, Zhang, Lin, editor, Song, Xiao, editor, and Wu, Yunjie, editor

Published
2016
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21. A Method of Parameter Calibration with Hybrid Uncertainty

Author

Shang XiaoBing, Wang Songyan, Chao Tao, and Liu Bo

Subjects
020301 aerospace & aeronautics, 0209 industrial biotechnology, Optimal matching, Calibration (statistics), Cumulative distribution function, Value (computer science), Sample (statistics), 02 engineering and technology, 020901 industrial engineering & automation, 0203 mechanical engineering, Genetic algorithm, Decomposition (computer science), Applied mathematics, Uncertainty quantification, Mathematics
Abstract

A method, which combines the cumulative distribution function and modified Kolmogorov–Smirnov test, is proposed to solve parameter calibration problem with genetic algorithm seeking the optimal result, due to the hybrid uncertainty in model. The framework is built on comparing the difference between cumulative distribution functions of some target observed values and that of sample values. First, an auxiliary variable method is used to decomposition hybrid parameters into sub-parameters with only one kind of uncertainty, which is aleatory or epistemic, because only epistemic uncertainty can be calibrated. Then we find optimal matching values with genetic algorithm according to the index of difference of joint cumulative distribution functions. Finally, we demonstrate that the proposed model calibration method is able to get the approximation values of the unknown true value of epistemic parameters, in mars entry dynamics profile. The example illustrates the rationality and efficiency of the method of this paper.

Published
2018

28. A sequential experimental design for multivariate sensitivity analysis using polynomial chaos expansion.

Author

Shang, Xiaobing, Ma, Ping, Chao, Tao, and Yang, Ming

Subjects
*EXPERIMENTAL design, *MULTIVARIATE analysis, *POLYNOMIAL chaos, *SENSITIVITY analysis, *COVARIANCE matrices
Abstract

Multivariate output sensitivity analysis has gained much attention when the output of the computational model is a vector. A preferable strategy to deal with the multivariate output issue is the covariance decomposition approach based on the polynomial chaos expansion (PCE) metamodel. However, since the PCE construction depends on the quality of experimental design to some extent, the selection of design points is significant in determining the accuracy of the sensitivity estimator. In this article, a PCE-based sequential experimental design is proposed to estimate the multivariate output sensitivity index. In this method, the optimal design point is sequentially selected to minimize the determinant of covariance matrix of the sensitivity estimator. To validate the performance of the proposed method, several numerical examples are presented, which show that the sequential design approach performs better than other prevalent methods in terms of accuracy and robustness. [ABSTRACT FROM AUTHOR]

Published
2020
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29. An efficient local search-based genetic algorithm for constructing optimal Latin hypercube design.

Author

Shang, Xiaobing, Chao, Tao, Ma, Ping, and Yang, Ming

Subjects
*GENETIC algorithms, *SAMPLING methods, *MODEL-driven software architecture
Abstract

Latin hypercube design (LHD) is a multi-stratified sampling method, which has been frequently used in sampling-based analysis. To achieve good space-filling quality of LHD, an efficient method, termed local search-based genetic algorithm (LSGA), is proposed in this article for constructing an optimal LHD. LSGA adopts modified order crossover, probabilistic mutation and adaptive selection operators to enrich population diversity and speed up convergence. A local search strategy is also presented in the approach to enhance the search ability. The performance of the proposed method is compared with several established methods in three perspectives, namely space-filling quality, computational efficiency and predictive accuracy of the metamodel. Several numerical experiments with distinct dimensions and numbers of design points are studied, and the results demonstrate that the proposed method performs better than other methods when dealing with LHD construction issues with high dimension and a large number of sampling points. [ABSTRACT FROM AUTHOR]

Published
2020
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34. Reflective liquid crystal hybrid beam-steerer

Author

Willekens, Oliver, primary, Jia, Xiaoning, additional, Vervaeke, Michael, additional, Shang, Xiaobing, additional, Baghdasaryan, Tigran, additional, Thienpont, Hugo, additional, De Smet, Herbert, additional, Neyts, Kristiaan, additional, and Beeckman, Jeroen, additional

Published
2016
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37. Switchable circular beam deflectors

Author

Shang, Xiaobing, primary, Joshi, Pankaj, additional, Tan, Jin-Yi, additional, De Smet, Jelle, additional, Cuypers, Dieter, additional, Baghdasaryan, Tigran, additional, Vervaeke, Michael, additional, Thienpont, Hugo, additional, and De Smet, Herbert, additional

Published
2016
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41. Electrically Controllable Liquid Crystal Component for Efficient Light Steering

Author

Shang, Xiaobing, primary, Tan, Jin-Yi, additional, Willekens, Oliver, additional, De Smet, Jelle, additional, Joshi, Pankaj, additional, Cuypers, Dieter, additional, Islamaj, Esma, additional, Beeckman, Jeroen, additional, Neyts, Kristiaan, additional, Vervaeke, Michael, additional, Thienpont, Hugo, additional, and De Smet, Herbert, additional

Published
2015
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47. Smart Liquid Crystal Beam Deflector With Laser Ablated Polymer Micro Grating Structur.

Author

Shang, Xiaobing, Desmet, Andres, Joshi, Pankaj, De Smet, Jelle, Cuypers, Dieter, and De Smet, Herbert

Subjects
LIQUID crystals, LIGHT deflectors, LASER ablation
Abstract

LC beam steering devices are realized using the combination of liquid crystal and polymer micro grating structures. The micro gratings are fabricated by combining two major techniques: laser ablation for a master mold and soft lithography for replicas with the desired optical materials. The LC components demonstrate effective beam deflections with a steering angle of 2.6∘ for both polarized monochromatic light (deflection efficiency >40%) and unpolarized white light beam (deflection efficiency >30%). [ABSTRACT FROM AUTHOR]

Published
2016
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