PM2.5 Prediction Using Genetic Algorithm-Based Feature Selection and Encoder-Decoder Model-Reference-Cited by-同舟云学术

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PM2.5 Prediction Using Genetic Algorithm-Based Feature Selection and Encoder-Decoder Model

Published:2021 Issue: Volume:9 Page:57338-57350
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Nguyen Minh Hieu^ORCID,Le Nguyen Phi,Nguyen Kien^ORCID,Le Van An,Nguyen Thanh-Hung,Ji Yusheng^ORCID

Funder

Vingroup Joint Stock Company (Vingroup JSC), Vingroup

Vingroup Innovation Foundation

Vingroup Joint Stock Company

Domestic Master/Ph.D. Scholarship Program of Vingroup Innovation Foundation (VINIF), Vingroup Big Data Institute

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/9312710/09399408.pdf?arnumber=9399408

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1. E-YQP: A self-adaptive end-to-end framework for quality prediction in yarn spinning manufacturing;Advanced Engineering Informatics;2024-10

2. A new attention-based CNN_GRU model for spatial–temporal PM2.5 prediction;Environmental Science and Pollution Research;2024-08-23

3. Application of complete ensemble empirical mode decomposition based multi-stream informer (CEEMD-MsI) in PM2.5 concentration long-term prediction;Expert Systems with Applications;2024-07

4. A New Attention-Based a convolutional neural network-gated recurrent unit Model for Spatial-Temporal PM2.5 Prediction;2024-06-19

5. Hourly PM2.5 Concentration Prediction Based on Empirical Mode Decomposition and Geographically Weighted Neural Network;ISPRS International Journal of Geo-Information;2024-03-02

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