Abstract
System integration has been the fastest growing industry in the international information service industry. The essence of system integration is optimum integrated design with a large-scale integrated computer network system. System integration includes the integration of computer software, hardware, operating system technology, database technology, network communication technology, as well as the integration of product selection, collocation and system integration of different manufacturers. The goal-overall performance is the best, that is, all components can work together, and the whole system is a low-cost, efficient, symmetrical, scalable and maintainable system. In order to achieve this goal, the merits and demerits of system integrators are crucial. However, the traditional models can not provide sufficient considerations on the system integration, so the actual computation has a larger error and reliability of system integration formula is greatly limited. In this paper, a new method applied to system integration is proposed combining Grey Relational Analysis (GRA) and BP Neural Network Technology (BPNN).
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Acknowledgments
This research was supported by the Key Projects of Natural Science Research in Inner Mongolia Higher Education Institutions (Grant No. NJZZ17647), and the Project of Humanities and Social Sciences Research in Inner Mongolia higher Education Institutions (Grant No. NJSY17149).
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Wu, H. (2020). Application of Intelligent Algorithms in System Integration Design. In: Xu, Z., Choo, KK., Dehghantanha, A., Parizi, R., Hammoudeh, M. (eds) Cyber Security Intelligence and Analytics. CSIA 2019. Advances in Intelligent Systems and Computing, vol 928. Springer, Cham. https://doi.org/10.1007/978-3-030-15235-2_103
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DOI: https://doi.org/10.1007/978-3-030-15235-2_103
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