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Meteorological and traffic effects on air pollutants using Bayesian networks and deep learning
Yuan Chien Lin
, Yu Ting Lin, Cai Rou Chen, Chun Yeh Lai
土木工程學系
研究成果
:
雜誌貢獻
›
期刊論文
›
同行評審
4
引文 斯高帕斯(Scopus)
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深入研究「Meteorological and traffic effects on air pollutants using Bayesian networks and deep learning」主題。共同形成了獨特的指紋。
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Keyphrases
Air Pollutants
100%
Traffic Impact
100%
Meteorological Effects
100%
Bayesian Deep Learning
100%
Bayesian Network Learning
100%
Traffic Factor
75%
Rainfall Pattern
50%
Air Quality
50%
Meteorological Factors
50%
Urban Areas
25%
Taipei
25%
Traffic Emissions
25%
Nonlinear Relationship
25%
Rainfall Events
25%
Vehicle Speed
25%
PM10
25%
Big Data Analysis
25%
Bayesian Network
25%
Analysis Procedure
25%
Long Short-term Memory Model
25%
Particulate Matter 2.5 (PM2.5)
25%
Rainfall Amount
25%
Quality Prediction Model
25%
Pollutant Concentration
25%
Probability Model
25%
Meteorological Variables
25%
Generalized Additive Model
25%
Air Pollution Sources
25%
Causality Relationship
25%
Air Pollutant Concentration
25%
Air Quality Prediction
25%
Data Analysis Framework
25%
Airborne Pollutants
25%
Air Pollution Data
25%
Latent Factor Analysis
25%
Traffic Flow Speed
25%
Vehicle Flow
25%
Pattern Factor
25%
Causality Condition
25%
Earth and Planetary Sciences
Air Pollutant
100%
Air Quality
50%
Pollutant Concentration
33%
Meteorological Factors
33%
Air Pollution
16%
Nitrogen Dioxide
16%
Traffic Emission
16%
Big Data
16%
Particular Matter 2.5
16%
Pollutant Source
16%