MIC for Analyzing Attributes Associated with Thai Agricultural Products

Tisinee Surapunt; Chuanlu Liu; Shuliang Wang

doi:10.1007/978-981-13-0893-2_5

MIC for Analyzing Attributes Associated with Thai Agricultural Products

Tisinee Surapunt^*
, Chuanlu Liu
, Shuliang Wang

^*此作品的通讯作者

Beijing Institute of Technology

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

1 引用（Scopus）

摘要

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.

源语言	英语
主期刊名	Geo-Spatial Knowledge and Intelligence - 5th International Conference, GSKI 2017, Revised Selected Papers
编辑	Fuling Bian, Hanning Yuan, Jing Geng, Chuanlu Liu, Tisinee Surapunt
出版商	Springer Verlag
页	40-47
页数	8
ISBN（印刷版）	9789811308925
DOI	https://doi.org/10.1007/978-981-13-0893-2_5
出版状态	已出版 - 2018
已对外发布	是
活动	5th International Conference on Geo-Spatial Knowledge and Intelligence, GSKI 2017 - Chiang Mai, 泰国期限: 8 12月 2017 → 10 12月 2017

出版系列

姓名	Communications in Computer and Information Science
卷	848
ISSN（印刷版）	1865-0929

会议

会议	5th International Conference on Geo-Spatial Knowledge and Intelligence, GSKI 2017
国家/地区	泰国
市	Chiang Mai
时期	8/12/17 → 10/12/17

联合国可持续发展目标

此成果有助于实现下列可持续发展目标：

可持续发展目标 2 零饥饿

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10.1007/978-981-13-0893-2_5

其它文件与链接

链接到 Scopus 的出版物

引用此

Surapunt, T., Liu, C., & Wang, S. (2018). MIC for Analyzing Attributes Associated with Thai Agricultural Products. 在 F. Bian, H. Yuan, J. Geng, C. Liu, & T. Surapunt (编辑), Geo-Spatial Knowledge and Intelligence - 5th International Conference, GSKI 2017, Revised Selected Papers (页码 40-47). (Communications in Computer and Information Science; 卷 848). Springer Verlag. https://doi.org/10.1007/978-981-13-0893-2_5

Surapunt, Tisinee ; Liu, Chuanlu ; Wang, Shuliang. / MIC for Analyzing Attributes Associated with Thai Agricultural Products. Geo-Spatial Knowledge and Intelligence - 5th International Conference, GSKI 2017, Revised Selected Papers. 编辑 / Fuling Bian ; Hanning Yuan ; Jing Geng ; Chuanlu Liu ; Tisinee Surapunt. Springer Verlag, 2018. 页码 40-47 (Communications in Computer and Information Science).

@inproceedings{ee4ef819081e4a78a11f6e0d010135c4,

title = "MIC for Analyzing Attributes Associated with Thai Agricultural Products",

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.",

keywords = "Agricultural production, MIC, Prediction production",

author = "Tisinee Surapunt and Chuanlu Liu and Shuliang Wang",

note = "Publisher Copyright: {\textcopyright} 2018, Springer Nature Singapore Pte Ltd.; 5th International Conference on Geo-Spatial Knowledge and Intelligence, GSKI 2017 ; Conference date: 08-12-2017 Through 10-12-2017",

year = "2018",

doi = "10.1007/978-981-13-0893-2\_5",

language = "English",

isbn = "9789811308925",

series = "Communications in Computer and Information Science",

publisher = "Springer Verlag",

pages = "40--47",

editor = "Fuling Bian and Hanning Yuan and Jing Geng and Chuanlu Liu and Tisinee Surapunt",

booktitle = "Geo-Spatial Knowledge and Intelligence - 5th International Conference, GSKI 2017, Revised Selected Papers",

address = "Germany",

}

Surapunt, T, Liu, C & Wang, S 2018, MIC for Analyzing Attributes Associated with Thai Agricultural Products. 在 F Bian, H Yuan, J Geng, C Liu & T Surapunt (编辑), Geo-Spatial Knowledge and Intelligence - 5th International Conference, GSKI 2017, Revised Selected Papers. Communications in Computer and Information Science, 卷 848, Springer Verlag, 页码 40-47, 5th International Conference on Geo-Spatial Knowledge and Intelligence, GSKI 2017, Chiang Mai, 泰国, 8/12/17. https://doi.org/10.1007/978-981-13-0893-2_5

MIC for Analyzing Attributes Associated with Thai Agricultural Products. / Surapunt, Tisinee; Liu, Chuanlu; Wang, Shuliang.
Geo-Spatial Knowledge and Intelligence - 5th International Conference, GSKI 2017, Revised Selected Papers. 编辑 / Fuling Bian; Hanning Yuan; Jing Geng; Chuanlu Liu; Tisinee Surapunt. Springer Verlag, 2018. 页码 40-47 (Communications in Computer and Information Science; 卷 848).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

TY - GEN

T1 - MIC for Analyzing Attributes Associated with Thai Agricultural Products

AU - Surapunt, Tisinee

AU - Liu, Chuanlu

AU - Wang, Shuliang

PY - 2018

Y1 - 2018

N2 - 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.

AB - 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.

KW - Agricultural production

KW - MIC

KW - Prediction production

UR - https://www.scopus.com/pages/publications/85049023926

U2 - 10.1007/978-981-13-0893-2_5

DO - 10.1007/978-981-13-0893-2_5

M3 - Conference contribution

AN - SCOPUS:85049023926

SN - 9789811308925

T3 - Communications in Computer and Information Science

SP - 40

EP - 47

BT - Geo-Spatial Knowledge and Intelligence - 5th International Conference, GSKI 2017, Revised Selected Papers

A2 - Bian, Fuling

A2 - Yuan, Hanning

A2 - Geng, Jing

A2 - Liu, Chuanlu

A2 - Surapunt, Tisinee

PB - Springer Verlag

T2 - 5th International Conference on Geo-Spatial Knowledge and Intelligence, GSKI 2017

Y2 - 8 December 2017 through 10 December 2017

ER -

Surapunt T, Liu C, Wang S. MIC for Analyzing Attributes Associated with Thai Agricultural Products. 在 Bian F, Yuan H, Geng J, Liu C, Surapunt T, 编辑, Geo-Spatial Knowledge and Intelligence - 5th International Conference, GSKI 2017, Revised Selected Papers. Springer Verlag. 2018. 页码 40-47. (Communications in Computer and Information Science). doi: 10.1007/978-981-13-0893-2_5

MIC for Analyzing Attributes Associated with Thai Agricultural Products

摘要

出版系列

会议

联合国可持续发展目标

访问文件

其它文件与链接

指纹

引用此