DocumentCode :
2470803
Title :
Study on the prediction of coal ash based on image recognition and BP neural network
Author :
Ling, Xiangyang ; Wang, Yuling
Author_Institution :
Sch. of Chem. Eng. & Technol., China Univ. of Min. & Technol., Xuzhou, China
fYear :
2011
fDate :
24-26 June 2011
Firstpage :
6378
Lastpage :
6380
Abstract :
Based on image recognition of coal particles, taking red average, green average, blue average, brightness average, saturation average, chroma average, mean value of gray scale, contrast ratio, and correlation as the input vectors, and using the BP neural network, this paper study on the prediction of coal ash. After establishing the network and training the experimental data in it, the network is stimulated. The result shows that the network has better prediction accuracy.
Keywords :
brightness; coal ash; image recognition; neural nets; physics computing; BP neural network; blue average; brightness average; chroma average; coal ash; coal particles; contrast ratio; gray scale; green average; image recognition; red average; saturation average; Artificial neural networks; Ash; Coal; MATLAB; Measurement uncertainty; Neurons; Training; BP neural network; average; coal ash; image recognition; prediction; stimulation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Remote Sensing, Environment and Transportation Engineering (RSETE), 2011 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-9172-8
Type :
conf
DOI :
10.1109/RSETE.2011.5965816
Filename :
5965816
Link To Document :
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