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Using particle swarm optimization algorithm in an artificial neural network to forecast the strength of paste filling material 被引量:24
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作者 CHANG Qing-liang ZHOU Hua-qiang HOU Chao-jiong 《Journal of China University of Mining and Technology》 EI 2008年第4期551-555,共5页
In order to forecast the strength of filling material exactly, the main factors affecting the strength of filling material are analyzed. The model of predicting the strength of filling material was established by appl... In order to forecast the strength of filling material exactly, the main factors affecting the strength of filling material are analyzed. The model of predicting the strength of filling material was established by applying the theory of artificial neural net- works. Based on cases related to our test data of filling material, the predicted results of the model and measured values are com- pared and analyzed. The results show that the model is feasible and scientifically justified to predict the strength of filling material, which provides a new method for forecasting the strength of filling material for paste filling in coal mines. 展开更多
关键词 mining engineering paste filling material neural network particle swarm optimized algorithm prediction
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