Enhancing multi-type coal quality prediction accuracy with fusion spectra and classification models using NIRS and XRF techniques-Reference-Cited by-同舟云学术

Enhancing multi-type coal quality prediction accuracy with fusion spectra and classification models using NIRS and XRF techniques

Author:

Zhang Zhedong¹²,Li Jiaxuan¹²,Gao Rui¹²,Zhao Yang³,Zhang Yan⁴,Zhang Lei¹²^ORCID,Ye Zefu⁵,Zhu Zhujun⁵,Zhang Peihua¹,Yin Wangbao¹²,Jia Suotang¹²

Affiliation:

1. State Key Laboratory of Quantum Optics and Quantum Optics Devices, Institute of Laser Spectroscopy, Shanxi University, Taiyuan, China

2. Collaborative Innovation Center of Extreme Optics, Shanxi University, Taiyuan, China

3. School of Semiconductor and Physics, North University of China, Taiyuan 030051, China

4. School of Optoelectronic Engineering, Xi'an Technological University, Xi'an, China

5. Shanxi Gemeng US-China Clean Energy R&D Center Co., Ltd., Taiyuan, China

Abstract

The various analytical indices of coal are important criteria for evaluating the quality of commercial coal.

Funder

Ministry of Education of the People's Republic of China

National Natural Science Foundation of China

Higher Education Discipline Innovation Project

China Petrochemical Corporation

Publisher

Royal Society of Chemistry (RSC)

Link

Reference25 articles.

3. P.Chen , Chinese coal properties, classification and use , Chemical Industry Press Pub , 2nd edn, 2007