[1] TAL D, ZILBER G, BIRAN G. System architecture[J]. Axerra Networks, 2003.
[2] 葛冰峰,任长晟,赵青松,等. 可执行体系结构建模与分析[J]. 系统工程理论与实践, 2011,31(11):2191-2201.
[3] 周曼,周荣坤,沈涛. 面向服务架构(SOA)标准发展现状及趋势[J]. 科协论坛(下半月), 2010(4):133-135.
[4] ERL T. SOA Design Patterns[M]. Prentice Hall, 2009.
[5] REISIG W. Petri Nets: An Introduction[M]. Springer Verlag, 1985.
[6] NI F,WANG M Z, ZHOU F, et al. Approach to executable architecture modeling from DoDAF to HCPN[J]. Systems Engineering and Electronic Technology, 2010,321(5):959-965.
[7] STAINES T S. Intuitive mapping of UML 2 activity diagrams into fundamental modeling concept Petri net diagrams and colored Petri nets[C]// Proceedings of the 15th Annual IEEE International Conference & Workshop on the Engineering of Computer Based Systems. 2008:191-200.
[8] BUYYA R, RANJAN R, CALHEIROS R N. Modeling and simulation of scalable cloud computing environments and the CloudSim toolkit: Challenges and opportunities[C]// 2009 International Conference on High Performance Computing & Simulation. 2009:1-11.
[9] KUMAR R, SAHOO G. Cloud computing simulation using CloudSim[J]. International Journal of Engineering Trends & Technology, 2014,8(2):82-86.
[10] RANI E, KAUR H. Study on fundamental usage of CloudSim simulator and algorithms of resource allocation in cloud computing[C]// 2017 8th International Conference on Computing. 2017:1-7.
[11]BECKER S, KOZIOLEK H, REUSSNER R. The Palladio component model for model-driven performance prediction[J]. Journal of Systems & Software, 2009,82(1):3-22.
[12]BECKER S. The Palladio component model[C]// Proceedings of the 1st Joint WOSP/SIPEW International Conference on Performance Engineering. 2010:257-258.
[13]KROGMANN K, REUSSNER R, MIRANDOLA R, et al. Palladio Prediction of Performance Property[M]. Springer, Berlin, Heidelberg, 1970.
[14]SUN Y, TAN W A, XIE N, et al. Online learning approach for performance prediction in large-scale service computing[J]. Journal of Frontiers of Computer Science and Technology, 2017,11(12):1922-1930.
[15]NAIR V, MENZIES T, SIEGMUND N, et al. Using bad learners to find good configurations[C]// Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering. 2017:257-267.
[16]RANGARAJAN A. SOA principles of service design[J]. Prentice Hall, 2008,10(4):53-54.
[17] HAGER S, CUMMINGS M. Management Information Systems in the Information Age[M]. Machinery Industry Press, 2011.
[18] 豆丁. Data Life Cycle Models and Concepts[EB/OL]. [2020-09-27]. https://www.docin.com/p-649059389.html.
[19]RUMELHART D, MCCLELLAND E. Parallel Distributed Processing: Explorations in the Microstructure of Cognition[M]. Cambridge: MIT Press, 1986.
[20]JIN L, LI S, HU B. RNN models for dynamic matrix inversion: a control-theoretical perspective[J]. IEEE Transactions on Industrial Informatics, 2018,14(1):189-199.
[21] JIN L, LI S, WANG H Q, et al. Non-convex projection activated zeroing neurodynamic models for time-varying matrix pseudoinversion with accelerated finite-time convergence[J]. Applied Soft Computing, 2018,62(1):840-850.
[22]冉均均,方方,杨耀宗. 改进Chebyshev前向神经网络在曲线拟合中的应用[J]. 信息通信, 2013(6):19-20.
[23]肖秀春,彭银桥,梅其祥,等. 基于梯度下降法的Chebyshev前向神经网络[J]. 安徽工业大学学报(自然科学版), 2018,35(2):153-159.
[24]XU Y. Orthogonal polynomials of several variables[J]. Journal of Approximation Theory, 2014,112(3):318-319.
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