XIE Li, YANG Huaining, YIN Xiangping, SUN Yuhua. Combination Forecasting Method of Ship Equipment Maintenance Cost withPrincipal Component Analysis[J]. Chinese Journal of Ship Research, 2012, 7(4): 108-112. doi: 10.3969/j.issn.1673-3185.2012.04.019
Citation: XIE Li, YANG Huaining, YIN Xiangping, SUN Yuhua. Combination Forecasting Method of Ship Equipment Maintenance Cost withPrincipal Component Analysis[J]. Chinese Journal of Ship Research, 2012, 7(4): 108-112. doi: 10.3969/j.issn.1673-3185.2012.04.019

Combination Forecasting Method of Ship Equipment Maintenance Cost withPrincipal Component Analysis

doi: 10.3969/j.issn.1673-3185.2012.04.019
More Information
  • Corresponding author: XIE Li
  • Received Date: 2011-12-31
  • Accepted Date: 2012-08-20
  • Rev Recd Date: 2012-03-23
  • Publish Date: 2012-08-25
    © 2012 The Authors. Published by Editorial Office of Chinese Journal of Ship Research. Creative Commons License
    This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
  • Using regression-based combination forecasting method to forecast ship equipment maintenance cost has fundamental drawback that the number of methods available is bigger than the cost samples',making it insufficient to estimate the regression coefficient. This paper proposed to apply the Principal Component Analysis(PCA)on the results which obtained by the individual forecast method prior to building regression-based combination model of a ship equipment maintenance cost forecast,and then the regression model of a realistic ship equipment maintenance cost on selected principal components was established,further,the forecast combination model based on PAC was presented. Meanwhile,in the process of PCA,there was some subjectivity in deciding the number of principal components according as cumulate contribution rate of principal components,so we took the Akaike's Information Criterion(AIC)as a substitution. Finally an exampal was used to analyze and validate the performance of the above mentioned method. The results show that the presented method not only can solve the problem that the number of forecasting models is in excess of the sample's in the regression-based combination forecasting of ship equipment maintenance cost,but also can solve the collinear between individual forecast method. And the performance of the presented method obviously superior to the usual combined forecasting models.
  • loading
  • XIE L,WEI R X,JIANG T J,et al. Generalized PLS regression forecast modeling of warship equipment maintenance cost[C]/16th International Conference on Management Science and Engineering. Washington:IEEE Press,2009:607-612.
    谢力,魏汝祥,于伟宗. 舰船装备维修费预测方法评 价准则体系研究[J]. 中国舰船研究,2011,6(2): 98-102. XIE L,WEI R X,YU W Z. Evaluation criteria system of forecasting methods for maintenance cost of ship equipment[J]. Chinese Journal of Ship Research, 2011,6(2):98-102.
    谢力,魏汝祥,訾书宇,等. 基于包容性检验的舰船装 备维修费组合预测[J]. 系统工程与电子技术,2010, 32(12):2599-2602. XIE L,WEI R X,ZI S Y,et al. Combined forecasting of ship equipment maintenance cost based on encompassing tests[J]. Systems Engineering and Electronics,2010,32(12):2599-2602.
    WEI R X,XIE L,YIN X P,et al. Combined forecasting of ship equipment maintenance cost with AHP and odds-matrix method[C]/The Proceedings of 2010 Conference on System Sciences, Management Sciences and System Dynamics. China, Beijing:Publishing House of Electronics Industry,2010(4):115-122.
    GRANGER C W J, RAMANATHAN R. Improved methods of combining forecasts[J]. Journal of Forecasting,1984,3(2):197-204.
    WEI X Q. Regression-based forecast combination methods[J]. Romanian Journal of Economic Forecasting, 2009,10(4):5-18.
    TIMMERMAN A. Forecast combinations[M]/ELLIOTT G,GRANGER C W J,TIMMERMAN A. Handbook of Economic Forecasting. North-Holland:Elsevier,2006:135-196.
    GRANGER C W J,JEON Y. Thick modeling[J]. Economic Modeling,2004,21(2):323-343.
    AIOLFI M,FAVERO C A. Model uncertainty,thick modeling and the predictability of stock returns[J]. Journal of Forecasting,2005,24(4):233-254.
    AIOLFI M,TIMMERMANN A. Persistence in forecasting performance and conditional combination strategies[J]. Journal of Econometrics,2006,135(1/ 2):31-53.
    CAMACHO J,PIC J,FERRER A. Data understanding with PCA:structural and variance information plots[J]. Chemometrics and Intelligent Laboratory Systems,2010,100(1):48-56.
    PEARSON K. On lines and planes of closest fit to systems of points in space[J]. Philosophical Magazine, 1901,2(11):559-572.
    HOTELLING H. Analysis of a complex of statistical variables into principal components[J]. Journal of Educational Psychology,1933,24(6):417-441.
    马丽艳,李宏伟. 一种基于非线性PCA的卷积混合 盲源分离算法[J]. 电子学报,2008,36(5):1009- 1012. MA L Y,LI H W. An algorithm based on nonlinear PCA for blind separation of convolutive mixtures[J]. Acta Electronica Sinica,2008,36(5):1009-1012.
    宋怀波,路长厚,邱化冬. 基于概率PCA 模型的压 印字符集本征维数确定方法[J]. 光电子激光, 2010,21(5):754-757. SONG H B,LU C H,QIU H D. Determine the intrinsic dimension of protuberant characters based on probabilistic PCA modeling method[J]. Journal of Optoelectronics. Laser,2010,21(5):754-757.
    王洪斌,肖金壮,王洪瑞. 数控系统连接相关故障的 核PCA 监测方法[J]. 制造技术与机床,2009,59 (7):94-97. WANG H B,XIAO J Z,WANG H R. Monitoring method on connection dependent faults in numerical control system using kernel PCA[J]. Manufacturing Technology and Machine Tool,2009,59(7):94-97.
    KOLASSA S. Combining exponential smoothing forecasts using Akaike weights[J]. International Journal of Forecasting,2011,27(2):238-251.
    訾书宇,魏汝祥,周萍. 基于RBF 神经网络的舰船 维修费预测[J]. 中国水运(学术版),2007,2(5): 164-165. ZI S Y,WEI R X,ZHOU P. Ship maintenance cost forecasting based on RBF neural network[J]. China Water Transport,2007,2(5):164-165.
    ANDRAWIS R R,ATIYA A F,EI-SHISHINY H. Forecast combinations of computational intelligence and linear models for the NN5 time series forecasting competition[J]. International Journal of Forecasting, 2011,27(3):672-688.
    ANDRAWIS R R,ATIYA A F,EI-SHISHINY H. Combination of long term and short term forecasts, with application to tourism demand forecasting[J]. International Journal of Forecasting,2011,27(3):870- 886.
    DIKS C G H,VRUGT J A. Comparison of point forecast accuracy of model averaging methods in hydrologic applications[J]. Stochastic Environmental Research and Risk Assessment,2010,24(6):809-820.
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article Views(135) PDF Downloads(4) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return