| 基于径向基函数(RBF)神经网络的测流断面插值处理 |
| |
| 引用本文： | 陈希球. 基于径向基函数(RBF)神经网络的测流断面插值处理[J]. 长江工程职业技术学院学报, 2020, 0(2): 30-32 |
| |
| 作者姓名： | 陈希球 |
| |
| 作者单位： | 长江工程职业技术学院 |
| |
| 摘 要： | 水文测验中的测流断面数据处理方法较多,大多采用线性插值法,但精度不够高。在传统插值方法的基础上,运用径向基函数神经网络进行插值计算,实验表明,其插值精度符合水文行业规范要求,且可提高流量测验成果的精度。
|
| 关 键 词： | 神经网络 测流断面 插值 |
Interpolation of Flow Measurement Section based onRadial Basis Function(RBF)Neural Network |
| |
| CHEN Xi-qiu. Interpolation of Flow Measurement Section based onRadial Basis Function(RBF)Neural Network[J]. Journal of Changjiang Engineering Vocational College, 2020, 0(2): 30-32 |
| |
| Authors: | CHEN Xi-qiu |
| |
| Affiliation: | (Changjiang Institute of Technology,Wuhan 430212,China) |
| |
| Abstract: | There are many methods for data processing of flow measurement section in hydrological tests,most of which adopt linear interpolation method,but the accuracy is not high enough.Based on the traditional interpolation method,the radial basis function(RBF)neural network is used to carry out the interpolation calculation.The experiments show that the interpolation accuracy meets the requirements of hydrology industry and can improve the accuracy of flow test results. |
| |
| Keywords: | neural network flow measurement section interpolation |
| 本文献已被 CNKI 维普 等数据库收录！ |
|
