Abstract
The characteristic distribution performance of big data, the exchange characteristic of lithium ion screen in cloud computing environment, quantitatively reflects the running state of lithium ion screen exchanger, in order to realize the effective monitoring of lithium ion screen exchange process. A fast extraction algorithm of Li-ion screen exchange feature big data based on big data is proposed. Big data acquisition of lithium ion screen exchange characteristics is realized in lithium ion screen exchange array, and the statistical analysis model of big data mining is constructed. In big data distribution subspace, the spectral feature extraction method is used to extract the spectral stripe feature of Li-ion screen exchange feature big data, and the extracted spectral stripe feature is fuzzy clustering and mining by adaptive neural network learning algorithm. Big data rapid extraction of exchange characteristics of lithium ion screen was realized. The simulation results show that the method has high accuracy in fast extraction of exchange features of lithium ion screen, strong resolution of exchange characteristics of lithium ion screen, and has good application value in high precision measurement of exchange characteristics of lithium ion screen.
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Zhou, S.B., Xu, W.X.: A novel clustering algorithm based on relative density and decision graph. Control Dec. 33(11), 1921–1930 (2018)
He, H., Tan, Y.: Automatic pattern recognition of ECG signals using entropy-based adaptive dimensionality reduction and clustering. Appl. Soft Comput. 55, 238–252 (2017)
Zhou, S.B., Xu, W.X.: A novel clustering algorithm based on relative density and decision graph. Control Dec. 33(11), 1921–1930 (2018)
Zhu, Y.L., Zhu, X.X., Wang, J.M.: Time series motif discovery algorithm based on subsequence full join and maximum clique. J. Comput. Appl. 39(2), 414–420 (2019)
He, W., Guo, C.J., Tian, Z.: Optimization method for multi-constellation precise point positioning performance evaluation. Comput. Eng. 45(5), 88–92 (2019)
Wei, X.S., Luo, J.H., Wu, J.: Selective convolutional descriptor aggregation for fine-grained image retrieval. IEEE Trans. Image Process. 26(6), 2868–2881 (2017)
Huang, X.J., You, R.Y., Zhou, C.J.: Study on optical properties of equivalent film constructed of metal nanoparticle arrays. J. Optoelectr. Laser 24(7), 1434–1438 (2013)
Ma, Z.K., Chen, W.H.: Friction torque calculation method of ball bearings based on rolling creepage theory. J. Mech. Eng. 53(22), 219–224 (2017)
Tu, G.S., Yang, X.Y., Zhou, T.P.: Efficient identity-based multi-identity fully homomorphic encryption scheme. J. Comput. Appl. 39(3), 750–755 (2019)
Wang, Z.H., Huang, M.Y.: Integrated algorithm based on density peaks and density-based clustering. J. Comput. Appl. 39(2), 398–402 (2019)
Feng, W., Wang, Y., Lin, D., et al.: When mm wave communications meet network densification: a scalable interference coordination perspective. IEEE J. Sel. Areas Commun. 35(7), 1459–1471 (2017)
Matilainen, M., Nordhausen, K., Oja, H.: New independent component analysis tools for time series. Stat. Probabil. Lett. 32(5), 80–87 (2017)
Hao, S.G., Zhang, L., Muhammad, G.: A union authentication protocol of cross-domain based on bilinear pairing. J. Software 8(5), 1094–1100 (2013)
Liu, S, Fu, W., Deng, H., et al.: Distributional fractal creating algorithm in parallel environment. Int. J. Distrib. Sen. Networks (2013). https://doi.org/10.1155/2013/281707
Acknowledgement
School-level Project of Changsha Normal University: XXZD20171103.
Hunan Natural Science Foundation: 2018JJ3555.
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© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Xiao, X., Wei, Z., Pei, P. (2020). Big Data Fast Extraction Method of Lithium Ion Screen Exchange Feature in Cloud Computing. In: Zhang, YD., Wang, SH., Liu, S. (eds) Multimedia Technology and Enhanced Learning. ICMTEL 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 327. Springer, Cham. https://doi.org/10.1007/978-3-030-51103-6_3
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DOI: https://doi.org/10.1007/978-3-030-51103-6_3
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