地理空间信息2025，Vol.23Issue(3)：13-17,5.DOI:10.3969/j.issn.1672-4623.2025.03.004
基于CEEMDAN-IPSO-KELM模型的BDS卫星钟差预报
BDS Satellite Clock Bias Prediction Based on CEEMDAN-IPSO-KELM Model
摘要
Abstract
Aiming at the nonlinear characteristics of BDS satellite clock bias data and the difficulty of accurate prediction,combining the complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN)algorithm and kernel extreme learning machine(KELM)algorithm,we constructed a new combined clock bias prediction model.Firstly,we used the signal decomposition ability of CEEMDAN algorithm to adaptively decompose the nonstationary clock bias sequence,and reconstructed the decomposition results to obtain new clock bias sequences.Then,we used the improved particle swarm optimization(IPSO)algorithm to optimize the kernel parameters and regularization parameters of KELM.Finally,we reconstructed the prediction results of different clock bias sequences to obtain the final clock bias prediction results.We used BDS clock bias data provided by the iGMAS to carry out short-term prediction experiments.The experimental results show that the prediction accuracy of model proposed in this paper is significantly better than that of the contrast models,whether it is single-day or multi-day clock bias prediction,which can enrich the existing BDS satellite clock bias prediction model.关键词
BDS/钟差预报/CEEMDAN/IPSO算法/KELMKey words
BDS/clock bias prediction/CEEMDAN/IPSO algorithm/KELM分类
天文与地球科学引用本文复制引用
边奇海,张莎薇,雷荣智,刘子巍,刘敏..基于CEEMDAN-IPSO-KELM模型的BDS卫星钟差预报[J].地理空间信息,2025,23(3):13-17,5.基金项目
浙江省测绘科学技术研究院科研基金资助项目(DFP2021D0605). （DFP2021D0605）
