|
|||||
|
|
| 基于麻雀搜索算法优化的BP神经网络卫星钟差预报 | |
| 引用本文： | 孟彩霞,吴迪,雷雨. 基于麻雀搜索算法优化的BP神经网络卫星钟差预报[J]. 大地测量与地球动力学, 2022, 42(2): 125-131. DOI: 10.14075/j.jgg.2022.02.004 |
| 作者姓名： | 孟彩霞 吴迪 雷雨 |
| 作者单位： | 西安邮电大学计算机学院,西安市西长安街618号,710121 |
| 基金项目： | 陕西省自然科学基础研究计划(2020JQ893);陕西省自然科学基金(2014JM8303)。 |
| 摘 要： | 使用麻雀搜索算法(sparrow search algorithm,SSA)对BP神经网络的初始权值和阈值进行优化和调整,以提高神经网络模型短期预报的精度和稳定性.采用IGS产品中的卫星钟差数据,对SSA-BP神经网络模型、PSO-BP神经网络模型、传统BP神经网络模型及传统二次多项式模型(QP模型)进行实验对比,结果... |
| 关 键 词： | 卫星钟差 BP神经网络模型 麻雀搜索算法 钟差预报 SSA-BP神经网络模型 |
BP Neural Network for Satellite Clock Bias Prediction Based on Sparrow Search Algorithm |
|
| MENG Caixia,WU Di,LEI Yu. BP Neural Network for Satellite Clock Bias Prediction Based on Sparrow Search Algorithm[J]. Journal of Geodesy and Geodynamics, 2022, 42(2): 125-131. DOI: 10.14075/j.jgg.2022.02.004 | |
| Authors: | MENG Caixia WU Di LEI Yu |
| Affiliation: | (School of Computer Science and Technology,Xi’an University of Posts and Telecommunications,618 West-Chang’an Street,Xi’an 710121,China) |
| Abstract: | We use sparrow search algorithm (SSA) to optimize and adjust the initial weights and thresholds of the BP neural network and thus improve the accuracy and stability of the neural network model’s short-term forecast. We use the satellite clock bias data in the IGS product to compare the SSA-BP neural network model, PSO-BP neural network model, traditional BP neural network model and traditional quadratic polynomial model (QP model). The results show that the SSA-BP neural network model has the highest prediction accuracy and stability, and its superiority becomes more obvious as forecasting time increases. |
| Keywords: | satellite clock bias BP neural network model sparrow search algorithm clock bias prediction SSA-BP neural network mode |
| 本文献已被 维普 万方数据 等数据库收录！ | |
| 点击此处可从《大地测量与地球动力学》浏览原始摘要信息 | |
| 点击此处可从《大地测量与地球动力学》下载全文 | |