Advertisement

Multi-source Heterogeneous Data Acquisition Algorithm Design Different Time Periods

  • Jun LiEmail author
  • Jun Xing
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 301)

Abstract

The traditional algorithm was affected by dynamic error and data loss, resulting in low efficiency of collection. In order to solve this problem, a time division collection algorithm based on data format transformation was proposed. According to the data format conversion process multi-source heterogeneous configuration files, and access to the content of the whole configuration file and the GDAL, according to the results of the configuration process design algorithm, under the constraints of the input data for approximate operation, minimize the objective function, through the fixed matrix other factors influence on partial derivatives root, period of time the multi-source heterogeneous data acquisition algorithm design. The experimental results showed that the maximum collection efficiency of the algorithm can reach 90%, which provided an effective solution for scientific researchers to solve the problems caused by differences in data format.

Keywords

Multiple source Heterogeneous data Period of time Acquisition Dynamic error Packet loss 

Notes

Acknowlegements

National Key R&D Program of China (2017YFF0211100).

Shenzhen Science and Technology Project (KJYY20160229141621130).

References

  1. 1.
    Liu, S., Li, N., Fu, J.: A peak-valley time division model based on high-dimensional norming and SGHSA algorithm. China Electr. Power 51(1), 179–184 (2018)Google Scholar
  2. 2.
    Li, B., Huang, J., Wu, Y., et al.: Short-term load forecasting of typhoon based on meteorological information particle reduction. J. Electr. Technol. 33(9), 2068–2076 (2018)Google Scholar
  3. 3.
    Wang, S., Shi, C., Qian, G., et al.: Chaotic time series prediction based on fractional order maximum correlation entropy algorithm. J. Phys. 20(1), 248–255 (2018)Google Scholar
  4. 4.
    Liu, C., Hu, N., Guo, Z., et al.: Numerical simulation of wave field in viscous fluid biphasic VTI medium based on fractional time derivative constant Q viscoelastic constitutive relation. Geophysics 19(6), 24–25 (2018)Google Scholar
  5. 5.
    Shi, J., Zhang, J.: Vehicle routing problem model and algorithm for batch distribution with stochastic travel time. Comput. Appl. 38(2), 573–581 (2018)Google Scholar
  6. 6.
    Wang, Z., Yi, Lin, Lin, Y.: Similarity measurement of time series based on coefficient matrix arc differential. Comput. Eng. 20(2), 9–16 (2018)Google Scholar
  7. 7.
    Wang, Y., Lian, C.H., Jin, Q.: Single quantum bit storage time refreshes the world record - single ion qubit. Physics with more than 10 minutes of coherent time, 47(5), 320–322 (2018)Google Scholar

Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2019

Authors and Affiliations

  1. 1.Shenzhen Academy of Inspection and QuarantineShenzhenChina

Personalised recommendations