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Research on Intelligent Task Management and Control Mode of Space Information Networks Based on Big-Data Driven

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Space Information Networks (SINC 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1169))

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Abstract

The space information networks provide a rich space, time, frequency spectrum resources, meet all kinds of scene mission requirements, especially the rapid development of information technology and the interaction of human life fusion, and the global data presents the characteristics of explosive growth and massive convergence, artificial intelligence has advantages such as flexibility, adaptability and low robustness in the direction of information fusion. On the basis of studying the framework of space-based information network, an integrate task management and control mode based on big-data driven space-based information networks and Internet of things is proposed. Artificial intelligence technology is used to solve the problem of the front-end requirements of task management and control, and the ratio of resource utilization to actual profit of joint information network load points is improved, at the same time, it lays a foundation for realizing autonomous task planning.

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References

  1. Na, L.Y., et al.: Analysis of spatial big data distributed storage strategy based on MySQL database. Digit. Technol. Appl. (2), 71–75 (2018)

    Google Scholar 

  2. Long, L.H., Liang, Y.H., Zhu, F.J., et al.: Considerations on accelerating the construction of reconnaissance and intelligence capability based on network information system. J. China Acad. Electron. Sci. 14(4), 23–25 (2019)

    Google Scholar 

  3. Xu, K., et al.: Application of probability theory and mathematical statistics in information theory. Sci. Technol. Inf. (10) (2008)

    Google Scholar 

  4. Dong, Y., Jinyu, L., et al.: Recent progresses: deep learning based acoustic models. IEEE J. Autom. Sin. 3, 18–22 (2017)

    Google Scholar 

  5. Chao, W.Y., et al.: Study on evaluation method of D-S evidence synthesis rules. Inf. Technol. (4) (2011)

    Google Scholar 

  6. Yan, D.C., et al.: Research on the application of feedforward neural network based on back propagation chaos particle swarm optimization training. Beijing University of Chemical Technology, Beijing (2013)

    Google Scholar 

  7. Zhao, S., Dong, X., et al.: Speech recognition based on improved LSTM deep neural network. J. Zhengzhou Univ. 5, 31–34 (2018)

    Google Scholar 

  8. Peng, Q., Jiao, L.H., Zhou, L., Bin, Z., et al.: Thinking on the construction of the comprehensive management and control system of space-based information network. J. China Acad. Electron. Sci. 12(5), 13–18 (2017)

    Google Scholar 

  9. Wu, M., Wu, W., Zhou, B., Lu, Z., Zhang, P., et al.: General framework of integrated information network of Space & Earth. In : Proceedings of the 12th Annual Meeting of Satellite Communication. Annual Meeting of Satellite Communication, Beijing (2016)

    Google Scholar 

  10. Li, G., Liu, X., Hua, G.G., et al.: Video behavior recognition algorithm based on convolutional dense network. Chin. Sci. Technol. Pap. 13(14), 57–61 (2018)

    Google Scholar 

  11. Hong, W.G., Feng, C.J., et al.: Spacecraft fault diagnosis method based on BP neural network and DS evidence theory. Comput. Eng. 30(6) (2009)

    Google Scholar 

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Correspondence to Qi Wang .

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Yu, X., Wang, Q. (2020). Research on Intelligent Task Management and Control Mode of Space Information Networks Based on Big-Data Driven. In: Yu, Q. (eds) Space Information Networks. SINC 2019. Communications in Computer and Information Science, vol 1169. Springer, Singapore. https://doi.org/10.1007/978-981-15-3442-3_10

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  • DOI: https://doi.org/10.1007/978-981-15-3442-3_10

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-3441-6

  • Online ISBN: 978-981-15-3442-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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