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首页> 外文会议>International symposium on multispectral image processing and pattern recognition >The Method For Froth Floatation Condition Recognition Based On Adaptive Feature Weighted
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The Method For Froth Floatation Condition Recognition Based On Adaptive Feature Weighted

机译：基于自适应特征加权的泡沫浮选条件识别方法

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摘要

The fusion of foam characteristics can play a complementary role in expressing the content of foam image. The weight of foam characteristics is the key to make full use of the relationship between the different features. In this paper, an Adaptive Feature Weighted Method For Froth Floatation Condition Recognition is proposed. Foam features without and with weights are both classified by using support vector machine (SVM).The classification accuracy and optimal equaling algorithm under the each ore grade are regarded as the result of the adaptive feature weighting algorithm. At the same time the effectiveness of adaptive weighted method is demonstrated.
机译：泡沫特征的融合可以在表达泡沫图像的内容中起到补充作用。泡沫特性的权重是充分利用不同特征之间关系的关键。提出了一种泡沫浮选条件识别的自适应特征加权方法。使用支持向量机（SVM）对不带权重的泡沫特征和带权重的泡沫特征进行分类。将每个矿石品位下的分类精度和最优均衡算法视为自适应特征加权算法的结果。同时证明了自适应加权方法的有效性。

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