Fast and Nondestructive Proximate Analysis of Coal from Hyperspectral Images with Machine Learning and Combined Spectra-Texture Features

Fast and Nondestructive Proximate Analysis of Coal from Hyperspectral Images with Machine Learning and Combined Spectra-Texture Features

Proximate analysis, including ash, volatile matter, moisture, fixed carbon, and calorific value, is a fundamental aspect of fuel testing and serves as the primary method for evaluating coal quality, which is critical for the processing and utilization of coal. The traditional analytical methods invo...

詳細記述

書誌詳細
主要な著者: Jihua Mao, Hengqian Zhao, Yu Xie, Mengmeng Wang, Pan Wang, Yaning Shi, Yusen Zhao
フォーマット: 論文
言語:English
出版事項: MDPI AG 2024-09-01
シリーズ:Applied Sciences
主題:
hyperspectral detection
coal proximate analysis
feature extraction
texture information
prediction modeling
オンライン･アクセス:https://www.mdpi.com/2076-3417/14/17/7920

インターネット

https://www.mdpi.com/2076-3417/14/17/7920

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