Modeling and forecasting of geomagnetic variation field based on ensemble empirical mode decomposition (EEMD) and linear neural network (LNN)

被引：0
|
作者：
Chen, Dingxin [1 ,2 ]
Liu, Daizhi [1 ]
Zeng, Xiaoniu [1 ]
Li, Yihong [1 ]
Wang, Yi [2 ]
机构：
[1] Xi'an Research Inst. of Hi-Tech, Xi'an, China
[2] State Key Laboratory of Information Processing, Department of Automation, Tsinghua University, Beijing, China
来源：
Journal of Computational Information Systems | 2015年 / 11卷 / 09期
关键词：
Number:; 41374154; Acronym:; NSFC; Sponsor: National Natural Science Foundation of China;
D O I：
10.12733/jcis14266
中图分类号：
学科分类号：
摘要：
引用
收藏
页码：3317 / 3322
相关论文
共 50 条
  • [1] Rainfall Forecasting Based on Ensemble Empirical Mode Decomposition and Neural Networks
    Beltran-Castro, Juan
    Valencia-Aguirre, Juliana
    Orozco-Alzate, Mauricio
    Castellanos-Dominguez, German
    Travieso-Gonzalez, Carlos M.
    ADVANCES IN COMPUTATIONAL INTELLIGENCE, PT I, 2013, 7902 : 471 - 480
  • [2] Forecasting stochastic neural network based on financial empirical mode decomposition
    Wang, Jie
    Wang, Jun
    NEURAL NETWORKS, 2017, 90 : 8 - 20
  • [3] Forecasting tourism demand based on empirical mode decomposition and neural network
    Chen, Chun-Fu
    Lai, Ming-Cheng
    Yeh, Ching-Chiang
    KNOWLEDGE-BASED SYSTEMS, 2012, 26 : 281 - 287
  • [4] The Modeling and Forecasting of Variable Geomagnetic Field Based on Artificial Neural Network
    Li, Yihong
    Guan, Wenliang
    Niu, Chao
    Liu, Daizhi
    ADVANCES IN FUTURE COMPUTER AND CONTROL SYSTEMS, VOL 1, 2012, 159 : 83 - 88
  • [5] Forecasting wavelet neural hybrid network with financial ensemble empirical mode decomposition and MCID evaluation
    Yang, Yu
    Wang, Jun
    EXPERT SYSTEMS WITH APPLICATIONS, 2021, 166
  • [6] Forecasting wavelet neural hybrid network with financial ensemble empirical mode decomposition and MCID evaluation
    Yang, Yu
    Wang, Jun
    Expert Systems with Applications, 2021, 166
  • [7] Forecasting model of geomagnetic variation field based on modified ensemble empirical mode decomposition-sample entropy-least square support vector machine
    Niu, C. (niuchao0511@163.com), 1600, Editorial Board of Medical Journal of Wuhan University (39):
  • [8] A hybrid model for PM2.5 forecasting based on ensemble empirical mode decomposition and a general regression neural network
    Zhou, Qingping
    Jiang, Haiyan
    Wang, Jianzhou
    Zhou, Jianling
    SCIENCE OF THE TOTAL ENVIRONMENT, 2014, 496 : 264 - 274
  • [9] Grid load forecasting based on hybrid ensemble empirical mode decomposition and CNN-BiLSTM neural network approach
    Tao, Peng
    Zhao, Junpeng
    Liu, Xiaoyu
    Zhang, Chao
    Zhang, Bingyu
    Zhao, Shasha
    INTERNATIONAL JOURNAL OF LOW-CARBON TECHNOLOGIES, 2024, 19 : 330 - 338
  • [10] A Novel Wind Speed Forecasting Method Based on Ensemble Empirical Mode Decomposition and GA-BP Neural Network
    Wang, Yamin
    Wang, Shouxiang
    Zhang, Na
    2013 IEEE POWER AND ENERGY SOCIETY GENERAL MEETING (PES), 2013,
12345