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Flame image recognition of alumina rotary kiln by artificial neural network and support vector machine methods 被引量:18
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作者 张红亮 邹忠 +1 位作者 李劼 陈湘涛 《Journal of Central South University of Technology》 EI 2008年第1期39-43,共5页
Based on the Fourier transform, a new shape descriptor was proposed to represent the flame image. By employing the shape descriptor as the input, the flame image recognition was studied by the methods of the artificia... Based on the Fourier transform, a new shape descriptor was proposed to represent the flame image. By employing the shape descriptor as the input, the flame image recognition was studied by the methods of the artificial neural network(ANN) and the support vector machine(SVM) respectively. And the recognition experiments were carried out by using flame image data sampled from an alumina rotary kiln to evaluate their effectiveness. The results show that the two recognition methods can achieve good results, which verify the effectiveness of the shape descriptor. The highest recognition rate is 88.83% for SVM and 87.38% for ANN, which means that the performance of the SVM is better than that of the ANN. 展开更多
关键词 rotary kiln flame image image recognition shape descriptor artificial neural network support vector machine
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