A Neural Network Approach with Iterative Strategy for Long-term PM2.5 Forecasting
Author:
Affiliation:
1. NIT Rourkela,Department of CSE,Rourkela,India
2. IIITDM Kurnool,Department of CSE,Kurnool,India
3. NIT Rourkela,Department of ECE,Rourkela,India
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9691480/9691481/09691552.pdf?arnumber=9691552
Reference27 articles.
1. An improved pollution forecasting model with meteorological impact using multiple imputation and fine-tuning approach
2. Long term forecasting of ambient air quality using deep learning approach;samal;2020 IEEE 17th India Council International Conference (INDICON),2020
3. Predicting the least air polluted path using the neural network approach
4. Data driven multivariate air quality forecasting using dynamic fine tuning autoencoder layer;samal;2020 IEEE 17th India Council International Conference (INDICON),2020
5. Temporal convolutional denoising autoencoder network for air pollution prediction with missing values
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1. Novel MIA-LSTM Deep Learning Hybrid Model with Data Preprocessing for Forecasting of PM2.5;Algorithms;2023-01-12
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