版权说明 操作指南
首页 > 成果 > 详情

Study on intelligent hybrid algorithm

认领
导出
Link by DOI
反馈
分享
QQ微信 微博
成果类型:
期刊论文、会议论文
作者:
Jian Guo;Fei Tan
通讯作者:
Guo, J.
作者机构:
[Jian Guo] School of Civil Engineering and Architecture, Wuhan Polytechnic University, Wuhan, China
[Fei Tan] Department of Controlled Science and Engineering, Huazhong University of Science and Technology, Wuhan, China
通讯机构:
School of Civil Engineering and Architecture, Wuhan Polytechnic University, China
语种:
英文
关键词:
hybrid algorithm;dynamic identification;radial basis function;particle swarm optimization
年:
2010
页码:
2101-2104
会议名称:
2010 International Conference on Electrical and Control Engineering
会议论文集名称:
2010 International Conference on Electrical and Control Engineering
会议时间:
June 2010
会议地点:
Wuhan, China
出版者:
IEEE
ISBN:
978-1-4244-6880-5
机构署名:
本校为第一且通讯机构
院系归属:
土木工程与建筑学院
摘要:
The radial basis function (RBF), which is well known dynamic neural network, has been improved to easily apply in dynamic systems identification. However, the RBF weights and thresholds, which are trained by the gradient descent method, will be fixed after the training completing. The adaptive ability is bad. To improve RBF performance of dynamic identification, a self-adaptive particle swarm optimization (SAPSO), which is a stochastic search algorithm, is employed to train and adjust RBF structure parameter online. The simulation experiments s...

反馈

验证码:
看不清楚,换一个
确定
取消

成果认领

标题:
用户 作者 通讯作者
请选择
请选择
确定
取消

提示

该栏目需要登录且有访问权限才可以访问

如果您有访问权限,请直接 登录访问

如果您没有访问权限,请联系管理员申请开通

管理员联系邮箱:yun@hnwdkj.com