Advanced Genetic Algorithm in the Problem of Linear Solver Parameters Optimization

Based on the study of SAE J1980-2008 and FMVSS 208, MADYMO7.1 is used to establish a Multi-body and FE model for two OOP children, and the statistic test is implemented to verify the accuracy of the model. The airbag parameters impacting OOP children greatly and their ranges are selected to determine the objective function. With the Latin Hypercube Sampling method, the Kring approximate model is constructed, and multi-island genetic algorithm is used in subsequently parameters optimization. The results show that the proposed optimization method can provide effective protection for 6-year-old OOP children.

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Multi-criteria control system parameters optimization based on genetic algorithm

Proceedings of the 3rd World Congress on Intelligent Control and Automation (Cat. No.00EX393) ◽

10.1109/wcica.2000.860053 ◽

2002 ◽

Author(s):

Yang Zhimin ◽

Wang Xu ◽

Zhuang Xianyi

Keyword(s):

Genetic Algorithm ◽

Control System ◽

Parameters Optimization ◽

System Parameters

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Study on high-speed cutting parameters optimization of AlMn1Cu based on neural network and genetic algorithm

Advances in Mechanical Engineering ◽

10.1177/1687814016644126 ◽

2016 ◽

Vol 8 (4) ◽

pp. 168781401664412 ◽

Cited By ~ 3

Author(s):

Zhenhua Wang ◽

Juntang Yuan ◽

Zengbin Yin ◽

Chao Li

Keyword(s):

Neural Network ◽

Genetic Algorithm ◽

High Speed ◽

Cutting Parameters ◽

Parameters Optimization ◽

High Speed Cutting ◽

Cutting Parameters Optimization

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A practical design sliding mode controller for DC–DC converter based on control parameters optimization using assigned poles associate to genetic algorithm

International Journal of Electrical Power & Energy Systems ◽

10.1016/j.ijepes.2013.05.043 ◽

2013 ◽

Vol 53 ◽

pp. 761-773 ◽

Cited By ~ 15

Author(s):

M. Bensaada ◽

A. Boudghene Stambouli

Keyword(s):

Genetic Algorithm ◽

Sliding Mode ◽

Parameters Optimization ◽

Sliding Mode Controller ◽

Control Parameters ◽

Practical Design

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PREDICTIVE MODELING OF SURFACE ROUGHNESS AND CUTTING PARAMETERS OPTIMIZATION IN ULTRA-PRECISION TURNING BASED ON GENETIC ALGORITHM

Journal of Mechanical Engineering ◽

10.3901/jme.2005.11.158 ◽

2005 ◽

Vol 41 (11) ◽

pp. 158 ◽

Cited By ~ 4

Author(s):

Zesheng Lu

Keyword(s):

Genetic Algorithm ◽

Surface Roughness ◽

Predictive Modeling ◽

Cutting Parameters ◽

Parameters Optimization ◽

Precision Turning ◽

Ultra Precision ◽

Cutting Parameters Optimization

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On-Line PID Parameters Optimization Control for Wind Power Generation System Based on Genetic Algorithm

IEEE Access ◽

10.1109/access.2020.3009240 ◽

2020 ◽

Vol 8 ◽

pp. 137094-137100

Author(s):

Jiasheng Li ◽

Wenguo Li

Keyword(s):

Genetic Algorithm ◽

Power Generation ◽

Wind Power ◽

Wind Power Generation ◽

Parameters Optimization ◽

Generation System ◽

Optimization Control ◽

On Line ◽

Power Generation System

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Application of genetic algorithm method for soil nailing parameters optimization

IOP Conference Series Materials Science and Engineering ◽

10.1088/1757-899x/800/1/012009 ◽

2020 ◽

Vol 800 ◽

pp. 012009

Author(s):

F Benayoun ◽

D Boumezerane ◽

S Rehab Bekkouche ◽

L Bendada

Keyword(s):

Genetic Algorithm ◽

Parameters Optimization ◽

Soil Nailing ◽

Genetic Algorithm Method

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Machining Parameters Optimization of Ultrasonically-Assisted Drilling Cortical Bone Based on Genetic Algorithm

2019 IEEE International Conference on Mechatronics and Automation (ICMA) ◽

10.1109/icma.2019.8816539 ◽

2019 ◽

Cited By ~ 1

Author(s):

Yahui Hu ◽

Huaiyu Zhang ◽

Longfei Wei ◽

Weihua Fu ◽

Chunqiu Zhang

Keyword(s):

Genetic Algorithm ◽

Cortical Bone ◽

Parameters Optimization ◽

Machining Parameters ◽

Machining Parameters Optimization

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Application of Genetic Algorithm in Cutting Parameter Optimization

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.1082.138 ◽

2014 ◽

Vol 1082 ◽

pp. 138-142

Author(s):

Li Feng Zhu ◽

Yan Zhang

Keyword(s):

Genetic Algorithm ◽

Mathematical Model ◽

Parameter Optimization ◽

Cutting Parameters ◽

Parameters Optimization ◽

Numerical Control ◽

Numerical Control Machining ◽

Factors Affecting ◽

Cutting Parameter ◽

Cutting Parameter Optimization

Process parameters optimization is an important problem in numerical control machining, through the analysis of various factors affecting the cutting effect in cutting process, a mathematical model of cutting parameter optimization in NC machining is established and the constraint conditions are also determined in the paper. The article puts forward using genetic algorithm to realize the optimization of mathematical model, and the optimization analysis results are verified in practical processing. The experimental results show that the optimized cutting parameters can satisfy machining requests and improve the cutting efficiency.

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