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Study on the prediction of coal ash based on image recognition and BP neural network

机译:基于图像识别和BP神经网络的粉煤灰预测研究

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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.
机译:基于煤颗粒的图像识别,以红色平均值,绿色平均值,蓝色平均值,亮度平均值,饱和度平均值,色度平均值,灰度平均值,对比度和相关性为输入向量,并使用BP神经网络,本文对粉煤灰的预测进行了研究。建立网络并训练其中的实验数据后,即可刺激网络。结果表明,该网络具有较好的预测精度。

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