[1] 付东,方程,王震雷. 作战能力与作战效能评估方法研究[J]. 军事运筹与系统工程, 2006,20(4):35-39.
[2] Iooss B, Lemaitre P. A review on global sensitivity analysis methods[M]// Operations Research/ Computer Science Interfaces Series(Vol.59). Springer, 2014:101-122.
[3] 罗鹏程,傅攀峰. 武器装备敏感性分析方法综述[J]. 计算机工程与设计, 2008,29(21):5546-5549.
[4] 张晓航. 防空导弹武器装备体系作战效能全局敏感性分析方法研究[D]. 长沙:国防科学技术大学, 2010.
[5] Nossent J, Elsen P, Bauwens W. Sobol’ sensitivity analysis of a complex environmental model[J]. Environmental Modelling and Software, 2011,26(12):1515-1525.
[6] Zhang Chi, Chu Jinggang, Fu Guangtao. Sobol’s sensitivity analysis for a distributed hydrological model of Yichun River Basin, China[J]. Journal of Hydrology, 2013,480:58-68.
[7] Mathieu A, Vidal T, Jullien A, et al. Sensitivity analysis to help individual plant model parameterization for winter oilseed rape[C]// IEEE International Conference on Functional-Structural Plant Growth Modeling, Simulation, Visualization and Applications. 2017:133-139.
[8] Zhan Che-sheng, Song Xiao-meng, Xia Jun, et al. An efficient integrated approach for global sensitivity analysis of hydrological model parameters[J]. Environmental Modelling & Software, 2013,41(41):39-52.
[9] 孔凡哲,宋晓猛,占车生,等. 水文模型参数敏感性快速定量评估的RSMSobol方法[J]. 地理学报, 2011,66(9):1270-1280.
[10]Luo Jiannan, Lu Wenxi. Sobol sensitivity analysis of NAPL-contaminated aquifer remediation process based on multiple surrogates[J]. Computers & Geosciences, 2014,67:110-116.
[11]Huang Guang-bin, Zhu Qin-yu, Siew C K. Extreme learning machine: A new learning scheme of feedforward neural networks[C]// Proceedings of IEEE International Joint Conference on Neural Networks. 2004:985-990.
[12]高尚,娄寿春. 武器系统效能评定方法综述[J]. 系统工程理论与实践, 1998,18(7):109-114.
[13]吴晓锋,钱东. 用于系统效能分析的WSEIAC模型及其扩展[J]. 系统工程理论与实践, 2000,20(8):1-6.
[14]Ding Shifei, Zhao Han, Zhang Yanan, et al. Extreme learning machine: Algorithm, theory and applications[J]. Artificial Intelligence Review, 2015,44(1):103-115.
[15]魏昕. 基于元模型的全局优化算法研究[D]. 武汉:华中科技大学, 2012.
[16]Mckay M D, Beckman R J, Conover W J. A comparison of three methods for selecting values of input variables in the analysis of output from a computer code[J]. Technometrics, 2000,42(1):55-61.
[17]Buslenko N P, Golenko D I, Sobol I M, et al.The Monte Carlo method[J]. Journal of the American Statistical Association, 1949,44(247):335-341.
[18]Sobol I M. On the distribution of points in a cube and the approximate evaluation of integrals[J]. USSR Computational Mathematics & Mathematical Physics, 1976,7(4):86-112.
[19]周心莲. 几个常用随机数及其性质的比较[J]. 郧阳师范高等专科学校学报, 2010,30(6):13-17.
[20]Wang Chen, Duan Qingyun, Gong Wei, et al. An evaluation of adaptive surrogate modeling based optimization with two benchmark problems[J]. Environmental Modelling & Software, 2014,60(76):167-179.
[21]Sobol I M. Sensitivity estimates for nonlinear mathematical models[J]. Matem Mod, 1993,2(1):112-118.
[22]Paruggia M. Sensitivity analysis in practice: A guide to assessing scientific models[J]. Journal of the Royal Statistical Society, 2005,168(2):466. |