基于卷积神经网络预测煤炭浮选精矿中的灰分含量
IF 2
4区 工程技术
Q4 ENERGY & FUELS
International Journal of Coal Preparation and Utilization
Pub Date : 2024-01-24
DOI:10.1080/19392699.2024.2308549
引用次数: 0
摘要
卷积神经网络（CNN）是目前最流行的图像分类技术之一。其出色的图像分类能力可预测灰度含量、灰度值和灰度......本文章由计算机程序翻译，如有差异，请以英文原文为准。
Predicting the ash content in coal flotation concentrate based on convolutional neural network
Convolutional neural networks (CNNs) are currently one of the most popular image classification technologies. Their excellent image classification ability enables the prediction of the ash content ...
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来源期刊
CiteScore
4.10
自引率
23.80%
发文量
106
审稿时长
6 months
期刊介绍：
International Journal of Coal Preparation and Utilization publishes original research papers, short communications, review articles, book reviews, and symposium announcements covering all aspects of coal preparation. The journal is significant reading for all individuals involved with coal preparation, including those in operations, engineering, management, education, and scientific research.
Topics include:
coal properties and coal petrography;
coal quality and characterization;
surface chemistry of coal and minerals;
crushing, grinding and liberation;
coal screening and classification;
dense medium and density separations;
froth flotation and oil agglomeration;
process control and optimization;
flocculation and thickening;
dewatering and thermal drying;
briquetting and pelletizing;
coal handling and storage;
coal utilization and blending;
waste disposal and pollution;
utility waste product utilization;
and carbon based material.
Additional subjects covered by the journal include properties of coal/water and coal/oil slurries as well as the processing of oil shales and tarsands by physical and physiochemical methods.
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