| 人工神经网络在岩体质量分级中的应用 |
| |
| 引用本文： | 王彪,陈剑平,李钟旭,晁军.人工神经网络在岩体质量分级中的应用[J].世界地质,2004,23(1):64-68. |
| |
| 作者姓名： | 王彪 陈剑平 李钟旭 晁军 |
| |
| 作者单位： | 吉林大学,建设工程学院,吉林,长春,130026 |
| |
| 基金项目： | 教育部资助优秀年轻教师基金项目(120413133) |
| |
| 摘 要： | 结合四川省金沙江某水电站工程实例，应用BP人工神经网络方法建立3层BP网络模型，选取岩石单轴抗压强度等6个影响因素为输入变量，对坝基复杂岩体进行质量分级。通过机算机Visual C 语言编程实现神经网络模型，进行网络的学习和运算。以神经网络合理结构分析方法选取合理结构，确定合理隐层单元的数量，提高网络测试的精度。对测试结果的分析发现，经过优化的BP网络模型经多次学习后，测试精度提高，结果可靠，取得较好的实际应用效果。
|
| 关 键 词： | 人工神经网络 岩体质量 网络模型 网络结构 |
| 文章编号： | 1004-5589(2004)01-0064-05 |
Application of artificial neural network in rockmass quality classification |
| |
| WANG Biao,CHEN Jian-ping,LI Zhong-xu,CHAO Jun.Application of artificial neural network in rockmass quality classification[J].World Geology,2004,23(1):64-68. |
| |
| Authors: | WANG Biao CHEN Jian-ping LI Zhong-xu CHAO Jun |
| |
| Abstract: | Applying the method of the back propagation artificial neural network of a hydraulic power station on the Jinsha River, Sichuan Province, choosing six influential factors on the rock mass quality as the input variables, such as one axis compressive strength of rock, the complicated rock mass of dam foundation is classified. With Visual C++ program language, network model is realized and can be used to learning and calculating. Through selecting rational network structure and setting the rational number of implicit layers and their units, network and training procedure are optimized, testing precision is also improved. The analysis indicats that the test result is exact and credible. The application has gained a good effect. |
| |
| Keywords: | artificial neural network rockmass quality network model network structure |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
|
