Air pollution prediction using semi-experimental regression model and Adaptive Neuro-Fuzzy Inference System

Masoomeh Zeinalnezhad; Abdoulmohammad Gholamzadeh Chofreh; Feybi Ariani Goni; Jiří Jaromír Klemeš

doi:10.1016/j.jclepro.2020.121218

Air pollution prediction using semi-experimental regression model and Adaptive Neuro-Fuzzy Inference System

Masoomeh Zeinalnezhad
, Abdoulmohammad Gholamzadeh Chofreh^*
, Feybi Ariani Goni
, Jiří Jaromír Klemeš

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

104 Citations (SciVal)

Original language	English
Article number	121218
Journal	Journal of Cleaner Production
Volume	261
DOIs	https://doi.org/10.1016/j.jclepro.2020.121218
Publication status	Published (VoR) - 10 Jul 2020

Funding

Two authors from this study have been supported by the EC co-funded project Sustainable Process Integration Laboratory – SPIL, funded as project No. CZ.02.1.01/0.0/0.0/15_003/0000456, the Operational Programme Research, Development, and Education of the Czech Ministry of Education, Youth and Sports by EU European Structural and Investment Funds, Operational Programme Research, Development and Education. Two authors from this study have been supported by the EC co-funded project Sustainable Process Integration Laboratory – SPIL, funded as project No. CZ.02.1.01/0.0/0.0/15_003/0000456 , the Operational Programme Research, Development, and Education of the Czech Ministry of Education , Youth and Sports by EU European Structural and Investment Funds, Operational Programme Research, Development and Education.

Funders	Funder number
Czech Ministry of Education, Youth and Sports Operational Programme Research, Development and Education
EC co-funded project Sustainable Process Integration Laboratory
Sustainable Process Integration Laboratory – SPIL
European Commission	CZ.02.1.01/0.0/0.0/15_003/0000456
European Commission
Ministerstvo Školství, Mládeže a Tělovýchovy

Keywords

Adaptive neuro-fuzzy inference system
Air pollution prediction
Nonlinear regression
Semi-experimental model
Sustainable development
Time-series data

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10.1016/j.jclepro.2020.121218

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title = "Air pollution prediction using semi-experimental regression model and Adaptive Neuro-Fuzzy Inference System",

keywords = "Adaptive neuro-fuzzy inference system, Air pollution prediction, Nonlinear regression, Semi-experimental model, Sustainable development, Time-series data",

author = "Masoomeh Zeinalnezhad and Chofreh, \{Abdoulmohammad Gholamzadeh\} and Goni, \{Feybi Ariani\} and Kleme{\v s}, \{Ji{\v r}{\'i} Jarom{\'i}r\}",

note = "Publisher Copyright: {\textcopyright} 2020 Elsevier Ltd",

year = "2020",

month = jul,

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doi = "10.1016/j.jclepro.2020.121218",

language = "English",

volume = "261",

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T1 - Air pollution prediction using semi-experimental regression model and Adaptive Neuro-Fuzzy Inference System

AU - Zeinalnezhad, Masoomeh

AU - Chofreh, Abdoulmohammad Gholamzadeh

AU - Goni, Feybi Ariani

AU - Klemeš, Jiří Jaromír

PY - 2020/7/10

Y1 - 2020/7/10

KW - Adaptive neuro-fuzzy inference system

KW - Air pollution prediction

KW - Nonlinear regression

KW - Semi-experimental model

KW - Sustainable development

KW - Time-series data

UR - https://www.scopus.com/pages/publications/85082700905

UR - https://www.scopus.com/pages/publications/85082700905#tab=citedBy

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DO - 10.1016/j.jclepro.2020.121218

M3 - Article

AN - SCOPUS:85082700905

SN - 0959-6526

VL - 261

JO - Journal of Cleaner Production

JF - Journal of Cleaner Production

M1 - 121218

ER -

Air pollution prediction using semi-experimental regression model and Adaptive Neuro-Fuzzy Inference System

Funding

Keywords

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