학술논문
Estimation Of The Lower Heating Value Of Solid Recovered Fuel Based On Swir Hyper-Spectral Images And Machine Learning
Document Type
Conference
Author
Source
2022 12th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS) Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2022 12th Workshop on. :1-5 Sep, 2022
Subject
Language
ISSN
2158-6276
Abstract
In this work, we apply Machine Learning techniques to Hyper-Spectral Images acquired by a Short Wave Infra-Red (SWIR) Camera, to classify the materials composing the Solid Recovered Fuel (SRF). This classification, enabled by data pre-processing techniques, is used to estimate the Lower Heat Value (LHV) of SRF samples, building on models of the literature. The accurate and timely estimates of SRF LHVs yield significant benefits to SRF consumers.