Title :
State recognition of rotary kiln sintering based on genetic algorithm and neural network
Author :
Jiang, Hui-Yan ; Huo, Yan ; Zhou, Xiao-Jie ; Chai, Tian-You
Author_Institution :
Sch. of Software, Northeastern Univ., Shenyang
Abstract :
A valid recognition technology of sintering state based on advanced genetic algorithm (GA) and artificial neural network (ANN) is presented Then important features are extracted and are selected from sintering images by some image processing methods, and GA is used to optimize the parameters of modified ANN. Lastly recognize the sintering state with ANN method. The results show that the strategy can improve effectiveness for state recognition of sintering image.
Keywords :
feature extraction; genetic algorithms; image recognition; kilns; neural nets; production engineering computing; sintering; artificial neural network; feature extraction; genetic algorithm; image processing methods; image sintering; rotary kiln sintering; state recognition; Genetic algorithms; Kilns; Neural networks; GA; Sintering state; feature extraction; neural network; recognition technology;
Conference_Titel :
Control and Decision Conference, 2008. CCDC 2008. Chinese
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-1733-9
Electronic_ISBN :
978-1-4244-1734-6
DOI :
10.1109/CCDC.2008.4597549
