February 24, 2024

Air Predictive Modeling for Air Quality: A Comparative Study of Machine Learning and Deep Learning Techniques

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Authors

SDShubhangi Dhongade STShweta Tiwaskar AKAbhijeet Koturwar

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Overview

Comparative analysis demonstrates enhanced predictive precision across diverse algorithms in hourly atmospheric pollutant records, highlighting viable tools for environmental protection.

Key Points

Hourly pollutant estimates across 33,360 entries improve through machine learning models, yielding refined tracking for particulate matter and atmospheric chemical compounds.
Comparative evaluation benchmarks artificial neural network architectures against deep learning frameworks, assessing predictive performance across diverse gaseous indicators.
Highlights the utility of support vector machine architectures in public health planning, though broader geographical validation is required to confirm global model generalization.

Cite This Study

Dhongade et al. (2024) studied this question.

synapsesocial.com/papers/68e77c8eb6db6435876f0c32 https://doi.org/10.1109/sceecs61402.2024.10482082

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February 24, 2024

Air Predictive Modeling for Air Quality: A Comparative Study of Machine Learning and Deep Learning Techniques

View Full Paper

Ask AI

Bookmark

Authors

SDShubhangi Dhongade STShweta Tiwaskar AKAbhijeet Koturwar

Discussion

Member takes

Overview

Comparative analysis demonstrates enhanced predictive precision across diverse algorithms in hourly atmospheric pollutant records, highlighting viable tools for environmental protection.

Key Points

Hourly pollutant estimates across 33,360 entries improve through machine learning models, yielding refined tracking for particulate matter and atmospheric chemical compounds.
Comparative evaluation benchmarks artificial neural network architectures against deep learning frameworks, assessing predictive performance across diverse gaseous indicators.
Highlights the utility of support vector machine architectures in public health planning, though broader geographical validation is required to confirm global model generalization.

Cite This Study

Dhongade et al. (2024) studied this question.

synapsesocial.com/papers/68e77c8eb6db6435876f0c32 https://doi.org/10.1109/sceecs61402.2024.10482082

View Full Paper

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Bookmark