Comparative Analysis of Prediction Models for Particulate Matter (PM<sub>2.5</sub>) Prediction-Reference-Cited by-同舟云学术

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Comparative Analysis of Prediction Models for Particulate Matter (PM_2.5) Prediction

Published:2023-10-19 Issue: Volume:1 Page:1-6
ISSN:
Container-title:2023 First International Conference on Advances in Electrical, Electronics and Computational Intelligence (ICAEECI)
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Author:

Narkhede Gaurav¹,Hiwale Anil S¹,Pawar Mangesh²,Dixit Shagun³

Affiliation:

1. Dr Vishwanath Karad MIT World Peace University,School of Electronics and Communication Engieering,Pune,India

2. Vishwakarma Institute of Information Technology,Department of Artificial Intelligence & Data Science,Pune,India

3. MIT College of Engineering,Department of Electronics and Telecommunication Engieering,Pune,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10370005/10370765/10370965.pdf?arnumber=10370965

Reference16 articles.

1. Comparison between three back-propagation algorithms for power quality monitoring

2. Artificial Neural Network for the Prediction of Particulate Matter (PM2.5)

3. Application of Artificial Neural Networks in the Prediction of PM10 Levels in the Winter Months: A Case Study in the Tricity Agglomeration, Poland

4. Application of computational intelligence techniques to forecast daily PM 10 exceedances in Brunei Darussalam

5. Prediction of air quality based on Gradient Boosting Machine Method

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Analyzing meteorological factors for forecasting PM10 and PM2.5 levels: a comparison between MLR and MLP models;Earth Science Informatics;2024-09-03

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