Dynamic modelling and time-series prediction by incremental growth of lateral delay neural networks

被引：0

作者：

Chan, LT ^{[1
]}

Li, Y ^{[1
]}

机构：

[1] Univ Glasgow, Ctr Syst & Control, Glasgow G12 8LT, Lanark, Scotland

来源：

2000 IEEE SYMPOSIUM ON COMBINATIONS OF EVOLUTIONARY COMPUTATION AND NEURAL NETWORKS | 2000年

关键词：

D O I：

10.1109/ECNN.2000.886237

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The difficult problems of predicting chaotic time series and modelling chaotic systems is approached using an innovative neural network design. By combining evolutionary techniques with others, good results can be obtained swiftly via incremental network growing. The network architecture and training algorithm make the creation of dynamic models efficient and hassle-free. The networks results accurately reflect the outputs of the chaotic systems being modelled and preserve complex attractor structures of these systems.

引用

页码：216 / 223

页数：8

共 50 条

[1] Lateral-delay neural networks: Better time-series prediction with smaller. networks
Chan, LT
Yun, L
[J]. PROCEEDINGS OF THE 5TH ASIA-PACIFIC CONFERENCE ON CONTROL & MEASUREMENT, 2002, : 191 - 196
[2] Time series prediction by growing lateral delay neural networks
Chan, L
Li, Y
[J]. REAL-WORLD APPLICATIONS OF EVOLUTIONARY COMPUTING, PROCEEDINGS, 2000, 1803 : 127 - 138
[3] Time-Series Prediction for Amount of Airworthiness Based on Time-Delay Neural Networks
Tatli, Ali
Kahvecioglu, Sinem
Karakoc, Hikmet
[J]. ELEKTRONIKA IR ELEKTROTECHNIKA, 2020, 26 (05) : 28 - 32
[4] Neural networks and seasonal time-series prediction
Prochazka, A
[J]. FIFTH INTERNATIONAL CONFERENCE ON ARTIFICIAL NEURAL NETWORKS, 1997, (440): : 36 - 41
[5] Recurrent Neural Networks for Financial Time-Series Modelling
Tsang, Gavin
Deng, Jingjing
Xie, Xianghua
[J]. 2018 24TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR), 2018, : 892 - 897
[6] RECURRENT NEURAL NETWORKS AND ROBUST TIME-SERIES PREDICTION
CONNOR, JT
MARTIN, RD
ATLAS, LE
[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS, 1994, 5 (02): : 240 - 254
[7] Time delay dynamic fuzzy networks for time series prediction
Oysal, Y
[J]. COMPUTATIONAL SCIENCE - ICCS 2005, PT 1, PROCEEDINGS, 2005, 3514 : 775 - 782
[8] Multivariate Time-Series Prediction Using LSTM Neural Networks
Ghanbari, Reza
Borna, Keivan
[J]. 2021 26TH INTERNATIONAL COMPUTER CONFERENCE, COMPUTER SOCIETY OF IRAN (CSICC), 2021,
[9] HIERARCHICAL TRAINING OF NEURAL NETWORKS AND PREDICTION OF CHAOTIC TIME-SERIES
DEPPISCH, J
BAUER, HU
GEISEL, T
[J]. PHYSICS LETTERS A, 1991, 158 (1-2) : 57 - 62
[10] Modeling and prediction with a class of time delay dynamic neural networks
Becerikli, Yasar
Oysal, Yusuf
[J]. APPLIED SOFT COMPUTING, 2007, 7 (04) : 1164 - 1169

← 1 2 3 4 5 →