Behavior Analysis of Atmospheric Components and Meteorological Variables Applying Data Mining Association Techniques

Marcos Orellana; Jimmy Salto; Priscila Cedillo

doi:10.1007/978-3-030-73103-8_12

Behavior Analysis of Atmospheric Components and Meteorological Variables Applying Data Mining Association Techniques

Marcos Orellana
, Jimmy Salto
, Priscila Cedillo

Universidad del Azuay

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

The relationship between atmospheric components and meteorological variables is essential to assess the air quality and thus avoid citizens' health risks. However, finding an association relationship between those factors could be complicated due to the number of categorization methods that can be used (e.g., frequency, size, binning). Therefore, the objective of this study is to propose a methodology that prepares data through a discretization process and then applies association techniques of the possible combinations between the analyzed variables. The results show that the method used is effective in locating patterns, which are useful for the environmental manager to find knowledge.

Original language	English
Title of host publication	Advances in Information and Communication - Proceedings of the 2021 Future of Information and Communication Conference, FICC
Editors	Kohei Arai
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	192-204
Number of pages	13
ISBN (Print)	9783030731021
DOIs	https://doi.org/10.1007/978-3-030-73103-8_12
State	Published - 2021
Event	Future of Information and Communication Conference, FICC 2021 - Virtual, Online Duration: 29 Apr 2021 → 30 Apr 2021

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	1364 AISC
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Conference

Conference	Future of Information and Communication Conference, FICC 2021
City	Virtual, Online
Period	29/04/21 → 30/04/21

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Association rules
Atmospheric pollutants
Data mining
Discretization
Meteorological variables

Access to Document

10.1007/978-3-030-73103-8_12

Cite this

Orellana, M., Salto, J., & Cedillo, P. (2021). Behavior Analysis of Atmospheric Components and Meteorological Variables Applying Data Mining Association Techniques. In K. Arai (Ed.), Advances in Information and Communication - Proceedings of the 2021 Future of Information and Communication Conference, FICC (pp. 192-204). (Advances in Intelligent Systems and Computing; Vol. 1364 AISC). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-73103-8_12

Orellana, Marcos ; Salto, Jimmy ; Cedillo, Priscila. / Behavior Analysis of Atmospheric Components and Meteorological Variables Applying Data Mining Association Techniques. Advances in Information and Communication - Proceedings of the 2021 Future of Information and Communication Conference, FICC. editor / Kohei Arai. Springer Science and Business Media Deutschland GmbH, 2021. pp. 192-204 (Advances in Intelligent Systems and Computing).

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title = "Behavior Analysis of Atmospheric Components and Meteorological Variables Applying Data Mining Association Techniques",

abstract = "The relationship between atmospheric components and meteorological variables is essential to assess the air quality and thus avoid citizens' health risks. However, finding an association relationship between those factors could be complicated due to the number of categorization methods that can be used (e.g., frequency, size, binning). Therefore, the objective of this study is to propose a methodology that prepares data through a discretization process and then applies association techniques of the possible combinations between the analyzed variables. The results show that the method used is effective in locating patterns, which are useful for the environmental manager to find knowledge.",

keywords = "Association rules, Atmospheric pollutants, Data mining, Discretization, Meteorological variables",

author = "Marcos Orellana and Jimmy Salto and Priscila Cedillo",

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year = "2021",

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isbn = "9783030731021",

series = "Advances in Intelligent Systems and Computing",

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Orellana, M, Salto, J & Cedillo, P 2021, Behavior Analysis of Atmospheric Components and Meteorological Variables Applying Data Mining Association Techniques. in K Arai (ed.), Advances in Information and Communication - Proceedings of the 2021 Future of Information and Communication Conference, FICC. Advances in Intelligent Systems and Computing, vol. 1364 AISC, Springer Science and Business Media Deutschland GmbH, pp. 192-204, Future of Information and Communication Conference, FICC 2021, Virtual, Online, 29/04/21. https://doi.org/10.1007/978-3-030-73103-8_12

Behavior Analysis of Atmospheric Components and Meteorological Variables Applying Data Mining Association Techniques. / Orellana, Marcos; Salto, Jimmy; Cedillo, Priscila.
Advances in Information and Communication - Proceedings of the 2021 Future of Information and Communication Conference, FICC. ed. / Kohei Arai. Springer Science and Business Media Deutschland GmbH, 2021. p. 192-204 (Advances in Intelligent Systems and Computing; Vol. 1364 AISC).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Behavior Analysis of Atmospheric Components and Meteorological Variables Applying Data Mining Association Techniques

AU - Orellana, Marcos

AU - Salto, Jimmy

AU - Cedillo, Priscila

PY - 2021

Y1 - 2021

N2 - The relationship between atmospheric components and meteorological variables is essential to assess the air quality and thus avoid citizens' health risks. However, finding an association relationship between those factors could be complicated due to the number of categorization methods that can be used (e.g., frequency, size, binning). Therefore, the objective of this study is to propose a methodology that prepares data through a discretization process and then applies association techniques of the possible combinations between the analyzed variables. The results show that the method used is effective in locating patterns, which are useful for the environmental manager to find knowledge.

AB - The relationship between atmospheric components and meteorological variables is essential to assess the air quality and thus avoid citizens' health risks. However, finding an association relationship between those factors could be complicated due to the number of categorization methods that can be used (e.g., frequency, size, binning). Therefore, the objective of this study is to propose a methodology that prepares data through a discretization process and then applies association techniques of the possible combinations between the analyzed variables. The results show that the method used is effective in locating patterns, which are useful for the environmental manager to find knowledge.

KW - Association rules

KW - Atmospheric pollutants

KW - Data mining

KW - Discretization

KW - Meteorological variables

UR - https://www.scopus.com/pages/publications/85105958883

U2 - 10.1007/978-3-030-73103-8_12

DO - 10.1007/978-3-030-73103-8_12

M3 - Contribución a la conferencia

AN - SCOPUS:85105958883

SN - 9783030731021

T3 - Advances in Intelligent Systems and Computing

SP - 192

EP - 204

BT - Advances in Information and Communication - Proceedings of the 2021 Future of Information and Communication Conference, FICC

A2 - Arai, Kohei

PB - Springer Science and Business Media Deutschland GmbH

T2 - Future of Information and Communication Conference, FICC 2021

Y2 - 29 April 2021 through 30 April 2021

ER -

Orellana M, Salto J, Cedillo P. Behavior Analysis of Atmospheric Components and Meteorological Variables Applying Data Mining Association Techniques. In Arai K, editor, Advances in Information and Communication - Proceedings of the 2021 Future of Information and Communication Conference, FICC. Springer Science and Business Media Deutschland GmbH. 2021. p. 192-204. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-3-030-73103-8_12

Behavior Analysis of Atmospheric Components and Meteorological Variables Applying Data Mining Association Techniques

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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