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基 于 SVM 算 法 的 TATB 基 PBX 单 轴 准 静 态 应 力 应 变 关 系
stitutive behavior of RDX‑based PBX with loading‑history and 589-598.
loading‑rate effects[J]. Chinese Journal of Energetic Materials [17] Ramin G,Mohammad R G,Mohammad N. Comparative stud‑
(Hanneng Cailiao),2016,24(9):832-837. ies of metamodeling and AI‑Based techniques in damagedetec‑
[4] 唐维,颜熹琳,温茂萍,等 . 典型 PBX 基于 Boltzmann 函数的准 tion of structures[J]. Advances in Engineering Software,2018,
115:65-77.
静 态 单 轴 拉 压 非 线 性 本 构 模 型[J]. 含 能 材 料 ,2017,25(8):
689-693. [18] Qasim A A,Zamri C,Mohammed F A,et al. Support vector
TANG Wei,YAN Xi‑lin,WEN Mao‑ping. A uniaxial nonlinear regression‑based model for prediction of behaviorstone col‑
tension‑compression constitutive model based on boltzmann‑ umn parameters in soft clay under highway embankment[J].
function for typical PBXs under quasi‑static loading[J]. Chi⁃ Neural Computing and Applications,2017,30(8):2459-
2469.
nese Journal of Energetic Materials(Hanneng Cailiao),2017,
25(8):689-693. [19] 魏小红,常双君,申孝立 . 基于 HLLE‑SVM 预测混合炸药爆轰性
[5] Bennett J G,Haberman K S,et al. A constitutive model for the 能[J]. 含能材料,2014,22(2):221-225.
non‑shock ignition and mechanical response of high explosives WEI Xiao‑hong,CHANG Shuang‑jun,SHEN Xiao‑li. Predic‑
[J]. Journal of the Mechanics and Physics of Solids,1998,46 tion of the Composite Explosion Parameters by HLLE‑SVM[J].
(12):2303-2322. Chinese journal of energetic materials(Hanneng Cailiao),
[6] Peeters R L, Hackett R M. Constitutive modeling of plas‑ 2014,22(2):221-225.
tic‑bonded explosives [J]. Experimental Mechanics, 1981: [20] 周红萍,庞海燕,温茂萍,等 . 3 种粘结剂材料的力学性能对比
111-116. 研究[J]. 材料导报,2009,23(12):34-36,52.
[7] R Browning,M Gurtin,W Williams. A one‑dimensional visco‑ ZHOU Hong‑ping,PANG Hai‑yan,WEN Map‑ping,et al.
plastic constitutive theory for filled polymers[J]. International⁃ Comparative studies on the mechanical properties of three
Journal of Solids and Structures,1984,20:921-934. kinds of binders[J]. Materials Review,2009,23(12):34-
[8] Ramberg W,Osgood W R. Description of stress‑strain curves 36,52.
by three parameters[J]. Technical Note,1943,902. [21] Ian G,Yoshua B,and AaronC. Deep Learning[M]. Massachu‑
[9] Browning R,Gurtin M,Williams W. A model for viscoplastic setts: Massachusetts Institute of Technology Press, 2016:
materials with temperature dependence [J]. International 88-90.
Journalof Solids and Structures,1989,25:441-457. [22] 周志华 . 机器学习[M]. 北京:清华大学出版社,2016:121-139.
ZHOU Zhi‑hua. Machine learning[M]. Beijing:Tsinghua Uni‑
[10] 李尚昆,黄西城,王鹏飞 . 高聚物粘结炸药的力学性能研究进展
[J]. 火炸药学报,2016,39(8):1-11. versity Press,2016:121-139.
LI Shang‑kun,HUANG Xi‑cheng,WANG Peng‑fei. Recent ad‑ [23] Goldfarb D,Idnani A. A numerically stable dual method for
vances in the investigation on mechanical properties of PBX solving strictly convex quadratic programs[J]. Mathematical
[J]. Chinese Journal of Explosives & Propellants,2016,39 Programming,1983,27(1):1-33.
(8):1-11. [24] Burachik R S,Rizvi M M. On weak and strong Kuhn‑Tucker
[11] Timm K,Halim K,Alexandr K,et al. The lattice boltzman‑ conditions for smooth multi‑objective optimization[J]. Journal
nmethod[M]. Berlin:Springer‑Verlag,2017. of Optimization Theory and Applications, 2012, 155:
[12] Shunk Devin. PBX 9502 literature review:An engineering per‑ 477-491.
spective [R]. Los Alamos National Laboratory report [25] 叶永伟,陆俊杰,钱志勤,等 . 基于 LS‑SVM 的机械式温度仪表误
LA‑UR‑13‑21673,2013. 差预测研究[J]. 仪器仪表学报,2016,37(1):57-66.
[13] Jiang N,Zhao Z,Ren L. Design of structural modular neural YE Yong‑wei,LU Jun‑jie,QIAN Zhi‑qin,et al. Study on the
networks with genetic algorithm[J]. Advances in Engineer Soft⁃ temperature error prediction of mechanical temperature instru‑
ware,2003,34(1):17-24. ment based on LS‑SVM[J]. Chinese Journal of Scientific Instru⁃
[14] Asfaram A,Ghaedi M,AhmadiAzqhandi M H,et al. Statisti‑ ment,2016,37(1):57-66.
cal experimental design,least squaressupport vector machine [26] 叶永伟,陆俊杰,钱志勤,等 . 基于 LS‑SVM 的机械式温度仪表误
(LS‑SVM) and artificialneural network (ANN) methods for 差预测研究[J]. 仪器仪表学报,2016,37(1):57-66.
modeling thefacilitated adsorption of methylene blue dye[J]. YE Yong‑wei,LU Jun‑jie,QIAN Zhi‑qin,et al. Study on the
RSC Advances,2016,6:40502-40516. temperature error prediction of mechanical temperature instru‑
[15] VAPNIK V N. The nature of statistical learning theory[M]. ment based on LS‑SVM[J]. Chinese Journal of Scientific Instru⁃
New York:Springer,1995. ment,2016,37(1):57-66.
[16] Farzad N,Faezeh J,Ehsan M,et al. Experimental observa‑ [27] Reuter U,Sultana A,Reischl D S. A comparative study of ma‑
tions and SVM‑based prediction of properties of polypropylene chine learning approaches for modeling concrete failure Sur‑
fibres reinforced self‑compacting composites incorporating na‑ faces[J]. Advances in Engineering Software, 2018, 116:
67-79.
no‑CuO[J]. Construction and Building Materials,2017,143:
CHINESE JOURNAL OF ENERGETIC MATERIALS 含能材料 2019 年 第 27 卷 第 5 期 (410-416)