NIRS-XRF fusion spectroscopy for coal calorific value prediction using data deficient learning-Reference-Cited by-同舟云学术

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NIRS-XRF fusion spectroscopy for coal calorific value prediction using data deficient learning

Published:2024 Issue:8 Volume:39 Page:1990-2001
ISSN:0267-9477
Container-title:Journal of Analytical Atomic Spectrometry
language:en
Short-container-title:J. Anal. At. Spectrom.

Author:

Jie Xianjing¹,Yang Aiyong²,Cui Qingru³,Xu Baobei⁴^ORCID,Guo Yilu⁴,Pu Shiliang⁴

Affiliation:

1. CHN ENERGY Investment Group Co. Ltd, China

2. National Environmental Protection Research Institute for Electric Power, China

3. China Energy Science and Technology Research Institute Co. Ltd, China

4. Hikvision Research Institute, Hangzhou, Zhejiang 310051, China

Abstract

The overall pipeline of the proposed PLS-assisted neural fine-tuning framework.

Funder

Jiangsu Provincial Key Research and Development Program

Publisher

Royal Society of Chemistry (RSC)

Link

http://pubs.rsc.org/en/content/articlepdf/2024/JA/D4JA00091A

Reference49 articles.

1. Intertemporal optimization of the coal production capacity in China in terms of uncertain demand, economy, environment, and energy security

2. A review of laser-induced breakdown spectroscopy for coal analysis

3. Accuracy improvement of quantitative LIBS analysis of coal properties using a hybrid model based on a wavelet threshold de-noising and feature selection method

4. A method for in-situ measurement of calorific value of coal: a numerical study

5. Determining the elemental composition of fuels by bomb calorimetry and the inverse correlation of HHV with elemental composition

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