Fast characterization of biomass and waste by infrared spectra and machine learning models-Reference-Cited by-同舟云学术

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Fast characterization of biomass and waste by infrared spectra and machine learning models

Published:2020-04 Issue: Volume:387 Page:121723
ISSN:0304-3894
Container-title:Journal of Hazardous Materials
language:en
Short-container-title:Journal of Hazardous Materials

Author:

Tao Junyu,Liang Rui,Li Jian,Yan Beibei,Chen Guanyi,Cheng Zhanjun,Li Wanqing,Lin Fawei,Hou Lian

Funder

Ministry of Science and Technology of the People's Republic of China

National Natural Science Foundation of China

Tianjin Science and Technology Committee

Publisher

Elsevier BV

Subject

Health, Toxicology and Mutagenesis,Pollution,Waste Management and Disposal,Environmental Chemistry,Environmental Engineering

Reference50 articles.

1. QSPR models for octane number prediction;Al-Fahemi;J. Theor. Chem.,2014

2. Introduction to Machine Learning;Alpaydin,2014

3. Infrared Absorption Spectroscopy, Environmental Instrumentation and Analysis Handbook; Down, R.; Lehr, JH Eds;Barber,2005

4. A hierarchical classification approach for recognition of low-density (LDPE) and high-density polyethylene (HDPE) in mixed plastic waste based on short-wave infrared (SWIR) hyperspectral imaging;Bonifazi;Spectrochim. Acta Part A,2018

5. Torrefaction and carbonization of refuse derived fuel: char characterization and evaluation of gaseous and liquid emissions;Catarina;Bioresour. Technol.,2019

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