Samal, K. Krishna Rani (2024) Auto imputation enabled deep Temporal Convolutional Network (TCN) model for pm2.5 forecasting. EAI Endorsed Transactions on Scalable Information Systems.
![[thumbnail of 72033.pdf]](http://eprints.eai.eu/style/images/fileicons/application_pdf.png "72033.pdf")
PDF
72033.pdf
Download (2MB)
Abstract
Data imputation of missing values is one of the critical issues for data engineering, such as air quality modeling. It is challenging to handle missing pollutant values because they are collected at irregular and different times. Accurate estimation of those missing values is critical for the air po
| Item Type: | Article |
|---|---|
| Date Deposited: | 04 Mar 2026 18:29 |
| Last Modified: | 10 Apr 2026 23:07 |
| URI: | http://eprints.eai.eu/id/eprint/52712 |
Actions (login required)
- View Item