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To solve the problem of extreme learning machine (ELM) on-line training with sequential training samples, a new algorithm called selective forgetting extreme learning machine (SF-ELM) is proposed and applied to chaotic time series prediction. The SF-ELM adopts the latest training sample and weights the old training samples iteratively to insure that the influence of the old training samples is weakened. The output weight of the SF-ELM is determined recursively during on-line training procedure according to its generalization performance. Numerical experiments on chaotic time series on-line prediction indicate that the SF-ELM is an effective on-line training version of ELM. In comparison with on-line sequential extreme learning machine, the SF-ELM has better performance in the sense of computational cost and prediction accuracy.
[1] Song Q S, Feng Z R 2010 Expert Syst. Appl. 37 1776
[2] Fu Y Y, Wu C J, Jeng J T, Ko C N 2010 Expert Syst. Appl. 37 4441
[3] Jeng J T, Chuang C C, Tao C W 2010 Neurocomputing 73 1686
[4] Muhammad A F, Zolfaghari S 2010 Neurocomputing 73 2540
[5] Song Q S, Feng Z R 2010 Neurocomputing 73 2177
[6] Han M, Wang Y 2009 Expert Syst. Appl. 36 1280
[7] Mirzaee H 2009 Chaos Solitons Fract. 41 2681
[8] Lau K W, Wu Q H 2008 Pattern Recogn. 41 1539
[9] Lin C J, Chen C H, Lin C T 2008 IEEE Trans. Syst. Man Cybernet. 39 55
[10] Zhang C T, Ma Q L, Peng H 2010 Acta Phys. Sin. 59 7623 (in Chinese)[张春涛、 马千里、 彭 宏 2010 物理学报 59 7623]
[11] Liu J H, Zhang H G, Feng J 2010 Acta Phys. Sin. 59 4472 (in Chinese)[刘金海、 张化光、 冯 健 2010 物理学报 59 4472]
[12] Song Q S, Feng Z R, Li R H 2009 Acta Phys. Sin. 58 5057 (in Chinese)[宋青松 、 冯祖仁 、 李人厚 2009 物理学报 58 5057]
[13] Mao J Q,Yao J, Ding H S 2009 Acta Phys. Sin. 58 2220 (in Chinese)[毛剑琴、 姚 健、 丁海山 2009 物理学报 58 2220]
[14] Huang G B, Zhu Q Y, Siew C K 2007 Neurocomputing 70 489
[15] Liang N Y, Huang G B, Saratchandran P, Sundararajan N 2006 IEEE Trans. Neur. Net. 17 1411
[16] Feng G, Huang G B, Lin Q P, Gay R 2009 IEEE Trans. Neur. Net. 20 1352
[17] Miche Y, Soriamaa A, Bas P, Simula O, Jutten C, Lendasse A 2010 IEEE Trans. Neur. Net. 21 158
[18] Lan Y, Soh C Y, Huang G B 2010 Neurocomputing 73 3191
[19] Malathi V, Marimuthu N S, Baskar S 2010 Neurocomputing 73 2160
[20] Zhang X D 2005 Matrix Analysis and Applications (Beijing: Tsinghua University Press) p64 (in Chinese) [张贤达 2005 矩阵分析与应用 (北京: 清华大学出版社) 第64页]
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[1] Song Q S, Feng Z R 2010 Expert Syst. Appl. 37 1776
[2] Fu Y Y, Wu C J, Jeng J T, Ko C N 2010 Expert Syst. Appl. 37 4441
[3] Jeng J T, Chuang C C, Tao C W 2010 Neurocomputing 73 1686
[4] Muhammad A F, Zolfaghari S 2010 Neurocomputing 73 2540
[5] Song Q S, Feng Z R 2010 Neurocomputing 73 2177
[6] Han M, Wang Y 2009 Expert Syst. Appl. 36 1280
[7] Mirzaee H 2009 Chaos Solitons Fract. 41 2681
[8] Lau K W, Wu Q H 2008 Pattern Recogn. 41 1539
[9] Lin C J, Chen C H, Lin C T 2008 IEEE Trans. Syst. Man Cybernet. 39 55
[10] Zhang C T, Ma Q L, Peng H 2010 Acta Phys. Sin. 59 7623 (in Chinese)[张春涛、 马千里、 彭 宏 2010 物理学报 59 7623]
[11] Liu J H, Zhang H G, Feng J 2010 Acta Phys. Sin. 59 4472 (in Chinese)[刘金海、 张化光、 冯 健 2010 物理学报 59 4472]
[12] Song Q S, Feng Z R, Li R H 2009 Acta Phys. Sin. 58 5057 (in Chinese)[宋青松 、 冯祖仁 、 李人厚 2009 物理学报 58 5057]
[13] Mao J Q,Yao J, Ding H S 2009 Acta Phys. Sin. 58 2220 (in Chinese)[毛剑琴、 姚 健、 丁海山 2009 物理学报 58 2220]
[14] Huang G B, Zhu Q Y, Siew C K 2007 Neurocomputing 70 489
[15] Liang N Y, Huang G B, Saratchandran P, Sundararajan N 2006 IEEE Trans. Neur. Net. 17 1411
[16] Feng G, Huang G B, Lin Q P, Gay R 2009 IEEE Trans. Neur. Net. 20 1352
[17] Miche Y, Soriamaa A, Bas P, Simula O, Jutten C, Lendasse A 2010 IEEE Trans. Neur. Net. 21 158
[18] Lan Y, Soh C Y, Huang G B 2010 Neurocomputing 73 3191
[19] Malathi V, Marimuthu N S, Baskar S 2010 Neurocomputing 73 2160
[20] Zhang X D 2005 Matrix Analysis and Applications (Beijing: Tsinghua University Press) p64 (in Chinese) [张贤达 2005 矩阵分析与应用 (北京: 清华大学出版社) 第64页]
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