Neural computation in paleoclimatology: General methodology and a case study

被引:10
|
作者
Carro-Calvo, L. [1 ]
Salcedo-Sanz, S. [1 ]
Luterbacher, J. [2 ]
机构
[1] Univ Alcala, Dept Signal Proc & Commun, Alcala De Henares, Spain
[2] Univ Giessen, Dept Geog, Giessen, Germany
关键词
Paleoclimatology; Neural networks; Climate reconstruction; CLIMATE RECONSTRUCTION; WINTER PRECIPITATION; LAST-MILLENNIUM; NETWORKS; EUROPE; PROXY;
D O I
10.1016/j.neucom.2012.12.045
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper we present the general methodology and main issues related to the application of neural networks to paleoclimatic reconstruction problems. We establish the basic methodological framework, data selection, organization and their relation to neural networks features. We also describe a skill score to compare regressors' performance and finally the paleoclimatic variable's reconstruction. We show a case study focused on winter precipitation reconstruction in the Mediterranean back to 1700, using multi-layer perceptrons, and the comparison of the obtained results to that of the existing alternative methodologies. (C) 2013 Elsevier B.V. All rights reserved.
引用
收藏
页码:262 / 268
页数:7
相关论文
共 50 条
  • [1] A general probability estimation approach for neural computation
    Khaikine, M
    Holthausen, K
    NEURAL COMPUTATION, 2000, 12 (02) : 433 - 450
  • [2] A General Methodology for Utility Microgrid Planning A Cairns Case Study
    Beere, Nicholas
    McPhail, Donald
    Sharma, Rahul
    2015 IEEE PES ASIA-PACIFIC POWER AND ENERGY ENGINEERING CONFERENCE (APPEEC), 2015,
  • [3] General metaheuristic-based methodology for computation and decomposition of LMPs
    Saraiva, Felipe Oliveira Silva
    Paucar, Vicente Leonardo
    ELECTRICAL ENGINEERING, 2021, 103 (02) : 793 - 811
  • [4] General metaheuristic-based methodology for computation and decomposition of LMPs
    Felipe Oliveira Silva Saraiva
    Vicente Leonardo Paucar
    Electrical Engineering, 2021, 103 : 793 - 811
  • [5] MIXED-SIGNAL APPROXIMATE COMPUTATION: A NEURAL PREDICTOR CASE STUDY
    Amant, Renee St.
    Jimenez, Daniel A.
    Burger, Doug
    IEEE MICRO, 2009, 29 (01) : 104 - 115
  • [6] A framework for the general design and computation of hybrid neural networks
    Rong Zhao
    Zheyu Yang
    Hao Zheng
    Yujie Wu
    Faqiang Liu
    Zhenzhi Wu
    Lukai Li
    Feng Chen
    Seng Song
    Jun Zhu
    Wenli Zhang
    Haoyu Huang
    Mingkun Xu
    Kaifeng Sheng
    Qianbo Yin
    Jing Pei
    Guoqi Li
    Youhui Zhang
    Mingguo Zhao
    Luping Shi
    Nature Communications, 13
  • [7] A framework for the general design and computation of hybrid neural networks
    Zhao, Rong
    Yang, Zheyu
    Zheng, Hao
    Wu, Yujie
    Liu, Faqiang
    Wu, Zhenzhi
    Li, Lukai
    Chen, Feng
    Song, Seng
    Zhu, Jun
    Zhang, Wenli
    Huang, Haoyu
    Xu, Mingkun
    Sheng, Kaifeng
    Yin, Qianbo
    Pei, Jing
    Li, Guoqi
    Zhang, Youhui
    Zhao, Mingguo
    Shi, Luping
    NATURE COMMUNICATIONS, 2022, 13 (01)
  • [8] A STUDY OF ARAB COMPUTER USERS - A SPECIAL CASE OF A GENERAL HCL METHODOLOGY
    KALLALA, M
    BELLIN, W
    LECTURE NOTES IN COMPUTER SCIENCE, 1988, 313 : 338 - 350
  • [9] A general partial discretization methodology for interlaminar stress computation in composite laminates
    Kant, Tarun
    Pendhari, Sandeep S.
    Desai, Yogesh M.
    CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES, 2007, 17 (02): : 135 - 161
  • [10] A general partial discretization methodology for interlaminar stress computation in composite laminates
    Department of Civil Engineering, Indian Institute of Technology Bombay, Powai, Mumbai-400 076, India
    CMES Comput. Model. Eng. Sci., 2007, 2 (135-161):