Application of CLGA in Impulsion Pressure Predictio
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摘要: 针对传统预测冲击矿压方法存在网络训练时间较长、容易陷入局部极小值、容易早熟等问题,提出了采用克隆选择遗传算法预测冲击矿压的方法,详细介绍了克隆选择遗传算法优化BP神经网络权值和阈值的基本步骤,并利用Matlab7.1在PC机上建立网络模型进行仿真实验,仿真结果表明,该方法有效提高了冲击矿压预测的准确性。Abstract: To solve problems of long time of network training,easy to fall into local minimum and easy to early maturity existed in traditional method of impulsion pressure prediction,the paper proposed a method using CLGA to predict impulsion pressure.It introduced basic steps using CLGA to optimize weight and threshold of BP neural network in details and made simulation experiment using Matlab7.1 to build network model on PC.The simulation result showed that the method can improve accuracy of impulsion pressure prediction effectively.
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Key words:
- impulsion pressure /
- prediction /
- BP neural network /
- GA /
- CLGA /
- prediction precisio
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