A feature selection and multi-model fusion-based approach of predicting air quality-Reference-Cited by-同舟云学术

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A feature selection and multi-model fusion-based approach of predicting air quality

Published:2020-05 Issue: Volume:100 Page:210-220
ISSN:0019-0578
Container-title:ISA Transactions
language:en
Short-container-title:ISA Transactions

Author:

Zhang Ying,Zhang Rongrong,Ma Qunfei,Wang Yanhao,Wang Qingqing,Huang Zihao,Huang Linyan

Funder

Fundamental Research Funds for the Central Universities, China

National Natural Science Foundation of China

Overseas Expertise Introduction Project for Disciplines Innovation in Universities, China

Publisher

Elsevier BV

Subject

Applied Mathematics,Control and Systems Engineering,Electrical and Electronic Engineering,Computer Science Applications,Instrumentation

Reference23 articles.

1. LightGBM: A highly efficient gradient boosting decision tree;Ke,2017

2. XGBoost: a scalable tree boosting system;Chen,2016

3. Greedy function approximation: A gradient boosting machine;Friedman;Ann Statist,2001

4. Review of the governing equations, computational algorithms, and other components of the models-3 community multiscale air quality (CMAQ) modeling system;Byun;Appl Mech Rev,2006

5. Application of chemical transport model CMAQ to policy decisions regarding PM2.5 in the UK;Chemel;Atmos Environ,2014

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