A comparative study on prediction of throughput in coal ports among three models
作者： Shuang Liu , Lixia Tian , Yuansheng Huang
DOI: 10.1007/S13042-013-0201-5
关键词:
摘要: Three forecasting models, i.e., the least squares support vector machine (LSSVM), neural network with back-propagation algorithm (BP), and a hybrid approach called APSO-LSSVM, are presented in this paper to predict throughput of coal ports. A comparative study on prediction accuracy among three models is conducted. The purpose provide some useful guidelines for selecting more accurate model throughput. results experimentally show that, comparison LSSVM BP, APSO-LSSVM has better generalization performance regarding indexes average error, mean absolute error squared error.
springer.com
sci-hub.se 参考文章(25)
XI-ZHAO WANG, SHU-XIA LU, JUN-HAI ZHAI, FAST FUZZY MULTICATEGORY SVM BASED ON SUPPORT VECTOR DOMAIN DESCRIPTION International Journal of Pattern Recognition and Artificial Intelligence. ,vol. 22, pp. 109- 120 ,(2008) , 10.1142/S0218001408006144
Philip Hans Franses, Dick van Dijk, The forecasting performance of various models for seasonality and nonlinearity for quarterly industrial production International Journal of Forecasting. ,vol. 21, pp. 87- 102 ,(2005) , 10.1016/J.IJFORECAST.2004.05.005
Peter M. Schulze, Alexander Prinz, Forecasting container transshipment in Germany Applied Economics. ,vol. 41, pp. 2809- 2815 ,(2009) , 10.1080/00036840802260932
Hubert Setzler, Cem Saydam, Sungjune Park, EMS call volume predictions: A comparative study Computers & Operations Research. ,vol. 36, pp. 1843- 1851 ,(2009) , 10.1016/J.COR.2008.05.010
Constantinos S. Hilas, Sotirios K. Goudos, John N. Sahalos, Seasonal decomposition and forecasting of telecommunication data: A comparative case study Technological Forecasting and Social Change. ,vol. 73, pp. 495- 509 ,(2006) , 10.1016/J.TECHFORE.2005.07.002
Xi-Zhao Wang, Yu-Lin He, Ling-Cai Dong, Huan-Yu Zhao, Particle swarm optimization for determining fuzzy measures from data Information Sciences. ,vol. 181, pp. 4230- 4252 ,(2011) , 10.1016/J.INS.2011.06.002
Phillip M. Yelland, Stable seasonal pattern models for forecast revision: A comparative study International Journal of Forecasting. ,vol. 22, pp. 799- 818 ,(2006) , 10.1016/J.IJFORECAST.2006.04.005
Wen-Yi Peng, Ching-Wu Chu, A comparison of univariate methods for forecasting container throughput volumes Mathematical and Computer Modelling. ,vol. 50, pp. 1045- 1057 ,(2009) , 10.1016/J.MCM.2009.05.027
Qiang He, Congxin Wu, Separating theorem of samples in Banach space for support vector machine learning International Journal of Machine Learning and Cybernetics. ,vol. 2, pp. 49- 54 ,(2011) , 10.1007/S13042-011-0013-4
Chih-Min Lin, Ming-Chia Li, Ang-Bung Ting, Ming-Hung Lin, None, A robust self-learning PID control system design for nonlinear systems using a particle swarm optimization algorithm International Journal of Machine Learning and Cybernetics. ,vol. 2, pp. 225- 234 ,(2011) , 10.1007/S13042-011-0021-4