| BP和Elman神经网络在砂土液化预测中的研究 |
| |
| 引用本文： | 高宗军,付青,郑秋霞,王世臣,许传杰,董红志.BP和Elman神经网络在砂土液化预测中的研究[J].中国安全生产科学技术,2013,9(6):58-62. |
| |
| 作者姓名： | 高宗军 付青 郑秋霞 王世臣 许传杰 董红志 |
| |
| 作者单位： | （山东省沉积成矿作用与沉积矿产重点实验室/山东科技大学地质科学与工程学院，山东青岛266590） |
| |
| 摘 要： | 基于砂土液化的影响因素具有非线性关系，而神经网络模型能够逼近任意非线性函数和适合于动态系统辨识的特性，分别建立输入层为4，隐含层神经元为2，输出层为1的三层BP神经网络和Elman网络，并且通过matlab软件运算，实例比较得出Elman模型比BP模型收敛速度快、精度高，在砂土液化的预测中效果更好。
|
| 关 键 词： | 砂土液化 BP神经网络 Elman神经网络 Matlab软件 |
Study on forecasting of sand liquefaction by using BP neural and Elamn neural networks |
| |
| GAO Zong-jun
,
FU Qing
,
ZHENG Qiu-xia
,
WANG Shi-chen
,
XU Chuan-jie
,
DONG Hong-zhi.Study on forecasting of sand liquefaction by using BP neural and Elamn neural networks[J].Journal of Safety Science and Technology,2013,9(6):58-62. |
| |
| Authors: | GAO Zong-jun FU Qing ZHENG Qiu-xia WANG Shi-chen XU Chuan-jie DONG Hong-zhi |
| |
| Affiliation: | (Shandong Provincial Key Laboratory of Depositional Mineralization & Sedimentary Minerals, College of GeologicalSciences & Engineering, Shandong University of Science and Technology, Qingdao Shandong 266590, China) |
| |
| Abstract: | Based on the condition that the
influencing factors of sand liquefaction have a non linear relationship, while the neural network model can simulate any nonlinear function and is suitable for dynamic system recognition, in this paper, a three layer BP neural network and Elman network with 4 input layer neuron ,2 hidden layer neuron and 1output layer neuron were established respectively. What’s more, by the way of practical examples simulations, Elamn neural networks haa a faster convergence speed, a higher accuracy and a better effect than Elamn neural networks. |
| |
| Keywords: | sand liquefaction BP neural networks elamn neural networks Matlab software |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
| 点击此处可从《中国安全生产科学技术》浏览原始摘要信息 |
|
点击此处可从《中国安全生产科学技术》下载全文 |
