[1] 王显会, 佘磊, 郭启涛, 等. 基于抗冲击波响应的新型蜂窝夹层结构多目标优化设计 [J]. 车辆与动力技术, 2014(4): 25–30.

WANG X H, YAN L, GUO Q T, et al. Multi-objective optimization design of new honeycomb sandwich structure based on shock wave response [J]. Vehicle & Power Technology, 2014(4): 25–30.
[2] 张钱城, 郝方楠, 李裕春, 等. 爆炸冲击载荷作用下车辆和人员的损伤与防护 [J]. 力学与实践, 2014, 36(5): 527–539. DOI: 10.6052/1000-0879-13-539.

ZHANG Q C, HAO F N, LI Y C, et al. Damage and protection of vehicles and personnel under blast loading [J]. Mechanics in Engineering, 2014, 36(5): 527–539. DOI: 10.6052/1000-0879-13-539.
[3] KENDALE A, AMERICAS T, JATEGAONKAR R, et al. Study of occupant responses in a mine blast using MADYMO [C] // SAFE Symposium, 2009.
[4] 张中英, 何洋扬, 王乐阳, 等. 车底结构对爆炸冲击波响应特性影响研究[C] // 全国仿真技术学术会议. 九江, 2009. 123−126.
[5] 孙京帅. 蜂窝材料面内冲击吸能性能优化及在电动汽车耐撞性设计中的应用[D]. 大连: 大连理工大学, 2013.
[6] FENG H M. Self-generation RBFNs using evolutional PSO learning [J]. Neurocomputing, 2006, 70(1-3): 241–251. DOI: 10.1016/j.neucom.2006.03.007.
[7] 柳建容, 马咏梅, 黄巍. 基BP神经网络与遗传算法的减振器优化设计 [J]. 机械科学与技术, 2011(8): 1267–1271.

LIU J R, MA Y M, HUANG W. Optimal design of shock absorber based on bp neural network and genetic algorithm [J]. Mechanical Science and Technology, 2011(8): 1267–1271.
[8] 李利莎, 谢清粮, 郑全平, 等. 基于Lagrange、ALE和SPH算法的接触爆炸模拟计算 [J]. 爆破, 2011, 28(1): 18–22. DOI: 10.3963/j.issn.1001-487X.2011.01.005.

LI L S, XIE Q L, ZHENG Q P, et al. Simulation of contact explosion based on Lagrange, ALE and SPH algorithms [J]. Blasting, 2011, 28(1): 18–22. DOI: 10.3963/j.issn.1001-487X.2011.01.005.
[9] 方开泰. 均匀实验设计的理论、方法和应用——历史回顾 [J]. 数理统计与管理, 2004, 23(3): 69–80. DOI: 10.3969/j.issn.1002-1566.2004.03.016.

FANG K T. Theory, method and application of uniform experimental design—historical review [J]. Journal of Mathematical Statistics and Management, 2004, 23(3): 69–80. DOI: 10.3969/j.issn.1002-1566.2004.03.016.
[10] SOBOL I M. Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates [M]. Elsevier Science Publishers, 2001. DOI: 10.1016/S0378-4754(00)00270-6.
[11] CHEN S, WANG X X, BROWN D J. Sparse incremental regression modeling using correlation criterion with boosting search [J]. IEEE Signal Processing Letters, 2005, 12(3): 198–201. DOI: 10.1109/LSP.2004.842250.
[12] CHEN S, WOLFGANG A, HARRIS C J, et al. Symmetric RBF classifier for nonlinear detection in multiple-antenna-aided systems [J]. IEEE Transactions on Neural Networks, 2008, 19(5): 737. DOI: 10.1109/TNN.2007.911745.
[13] GONZALEZ J, ROJAS I, ORTEGA J, et al. Multiobjective evolutionary optimization of the size, shape, and position parameters of radial basis function networks for function approximation [J]. IEEE Transactions on Neural Networks, 2003, 14(6): 1478–1495. DOI: 10.1109/TNN.2003.820657.
[14] LEUNG F H F, LAM H K, LING S H, et al. Tuning of the structure and parameters of a neural network using an improved genetic algorithm [J]. IEEE Transactions on Neural Networks, 2003, 14(1): 79–88. DOI: 10.1109/TNN.2002.804317.
[15] BORS A G, PITAS I. Median radial basis function neural network [J]. IEEE Transactions on Neural Networks, 1996, 7(6): 1351–1364. DOI: 10.1109/72.548164.
[16] YIN H, ALLINSON N M. Self-organizing mixture networks for probability density estimation [J]. IEEE Transactions on Neural Networks, 2001, 12(2): 405–411. DOI: 10.1109/72.914534.
[17] RAJEEV S, KRISHNAMOORTHY C S. Genetic algorithm-based methodology for design optimization of reinforced concrete frames [J]. Computer-Aided Civil and Infrastructure Engineering, 2002, 13(1): 63–74. DOI: 10.1111/0885-9507.00086.
[18] 魏然, 王显会, 周云波, 等. 帕累托最优在车辆底部防护结构设计中的应用研究 [J]. 兵工学报, 2015, 36(6). DOI: 10.3969/j.issn.1000-1093.2015.06.013.

WEI R, WANG X H, ZHOU Y B, et al. Research on the application of Pareto optimality in the protection structure design of vehicle bottom [J]. Acta Armamentarii, 2015, 36(6). DOI: 10.3969/j.issn.1000-1093.2015.06.013.
[19] 蔡亚. 多目标遗传算法的改进及其变速箱参数优化设计研究[D]. 合肥: 合肥工业大学, 2014. DOI: CNKI:CDMD:2.1015.568685.