Multi-condition flotation process condition recognition method based on deep learning and multivariate data pre-processing-Reference-Cited by-同舟云学术

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Multi-condition flotation process condition recognition method based on deep learning and multivariate data pre-processing

Published:2024-05-25 Issue: Volume: Page:1975-1980
ISSN:
Container-title:2024 36th Chinese Control and Decision Conference (CCDC)
language:
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Author:

Wang Yicheng¹,Wang Shu¹,Li Kang²

Affiliation:

1. Northeastern University,College of Information Science and Engineering,Shenyang,China

2. Beijing Key Laboratory of Process Automation in Mining & Metallurgy,State Key Laboratory of Intelligent Optimized Manufacturing in Mining & Metallurgy Process,Beijing,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10587298/10587321/10588288.pdf?arnumber=10588288

Reference17 articles.

1. Working Condition Recognition of a Mineral Flotation Process Using the DSFF-DenseNet-DT

2. A layered working condition perception integrating handcrafted with deep features for froth flotation

3. Process working condition recognition based on the fusion of morphological and pixel set features of froth for froth flotation

4. Sulfur Flotation Performance Recognition Based on Hierarchical Classification of Local Dynamic and Static Froth Features

5. Color co-occurrence matrix based froth image texture extraction for mineral flotation

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