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International Conference on Geo-Spatial Knowledge and Intelligence

GSKI 2017: Geo-Spatial Knowledge and Intelligence pp 40–47Cite as

MIC for Analyzing Attributes Associated with Thai Agricultural Products

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 848))

Abstract

A prediction system of Thai agricultural products will purpose as our future work. The large amount of data is necessary and precise to predict the trend. Due to the high-efficiency prediction, only the associated attributes are preferred and well prepared in the next process. MIC is one statistical method to measure a correlation coefficient of pairwise variables on an immense dataset. After that their correlation coefficient shows the ranking of variables relationship. Thus, the pre-processing of data is done before executing. In this paper will present the theoretical of MIC and related works. The general concepts of MIC and the special ideas will be described.

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Acknowledgments

This work was supported by National Key Research and Development Plan of China (2016YFB0502604, 2016YFC0803000), National Natural Science Fund of China (61472039), and Frontier and Interdisciplinary Innovation Program of Beijing Institute of Technology (2016CX11006), International Scientific and Technological Cooperation and Academic Exchange Program of Beijing Institute of Technology (GZ2016085103).

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Authors and Affiliations

  1. School of Software, Beijing Institute of Technology, No. 5, 100081 Haidian, Beijing, China

    Tisinee Surapunt, Chuanlu Liu & Shuliang Wang

Authors
  1. Tisinee Surapunt
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  2. Chuanlu Liu
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  3. Shuliang Wang
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Corresponding author

Correspondence to Tisinee Surapunt .

Editor information

Editors and Affiliations

  1. Beijing Institute of Technology, Beijing, China

    Hanning Yuan

  2. Beijing Institute of Technology, Beijing, China

    Jing Geng

  3. Beijing Institute of Technology, Beijing, China

    Chuanlu Liu

  4. Wuhan University, Wuhan, China

    Fuling Bian

  5. Beijing Institute of Technology, Beijing, China

    Tisinee Surapunt

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Surapunt, T., Liu, C., Wang, S. (2018). MIC for Analyzing Attributes Associated with Thai Agricultural Products. In: Yuan, H., Geng, J., Liu, C., Bian, F., Surapunt, T. (eds) Geo-Spatial Knowledge and Intelligence. GSKI 2017. Communications in Computer and Information Science, vol 848. Springer, Singapore. https://doi.org/10.1007/978-981-13-0893-2_5

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  • DOI: https://doi.org/10.1007/978-981-13-0893-2_5

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-0892-5

  • Online ISBN: 978-981-13-0893-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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