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Features Extraction of Flotation Froth Images and BP Neural Network Soft-Sensor Model of Concentrate Grade Optimized by Shuffled Cuckoo Searching Algorithm
Joint Authors
Shen, Na-na
Han, Shuang
Li, Shu-xia
Wang, Jie-sheng
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-17, 17 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-07-16
Country of Publication
Egypt
No. of Pages
17
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
For meeting the forecasting target of key technology indicators in the flotation process, a BP neural network soft-sensor model based on features extraction of flotation froth images and optimized by shuffled cuckoo search algorithm is proposed.
Based on the digital image processing technique, the color features in HSI color space, the visual features based on the gray level cooccurrence matrix, and the shape characteristics based on the geometric theory of flotation froth images are extracted, respectively, as the input variables of the proposed soft-sensor model.
Then the isometric mapping method is used to reduce the input dimension, the network size, and learning time of BP neural network.
Finally, a shuffled cuckoo search algorithm is adopted to optimize the BP neural network soft-sensor model.
Simulation results show that the model has better generalization results and prediction accuracy.
American Psychological Association (APA)
Wang, Jie-sheng& Han, Shuang& Shen, Na-na& Li, Shu-xia. 2014. Features Extraction of Flotation Froth Images and BP Neural Network Soft-Sensor Model of Concentrate Grade Optimized by Shuffled Cuckoo Searching Algorithm. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-17.
https://search.emarefa.net/detail/BIM-1048733
Modern Language Association (MLA)
Wang, Jie-sheng…[et al.]. Features Extraction of Flotation Froth Images and BP Neural Network Soft-Sensor Model of Concentrate Grade Optimized by Shuffled Cuckoo Searching Algorithm. The Scientific World Journal No. 2014 (2014), pp.1-17.
https://search.emarefa.net/detail/BIM-1048733
American Medical Association (AMA)
Wang, Jie-sheng& Han, Shuang& Shen, Na-na& Li, Shu-xia. Features Extraction of Flotation Froth Images and BP Neural Network Soft-Sensor Model of Concentrate Grade Optimized by Shuffled Cuckoo Searching Algorithm. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-17.
https://search.emarefa.net/detail/BIM-1048733
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1048733