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Using particle swarm optimization algorithm in an artificial neural network to forecast the strength Using particle swarm optimization algorithm in an artificial neural network to forecast the strength

Using particle swarm optimization algorithm in an artificial neural network to forecast the strength

  • 期刊名字:中國礦業(yè)大學(xué)學(xué)報(英文版)
  • 文件大?。?/li>
  • 論文作者:CHANG Qing-liang,ZHOU Hua-qian
  • 作者單位:School of Mines
  • 更新時間:2023-02-12
  • 下載次數(shù):
論文簡介

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 networks. Based on cases related to our test data of filling material, the predicted results of the model and measured values are compared 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.

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