TY - GEN
T1 - Regularized dynamic self organized neural network inspired by the immune algorithm for financial time series prediction
AU - Al-Askar, Haya
AU - Hussain, Abir Jaafar
AU - Al-Jumeily, Dhiya
AU - Radi, Naeem
PY - 2014
Y1 - 2014
N2 - A novel type of recurrent neural network, the regularized Dynamic Self Organised Neural Network Inspired by the Immune Algorithm, is presented. The Regularization technique is used with the Dynamic self-organized multilayer perceptrons network that is inspired by the immune algorithm. The regularization has been addressed to improve the generalization and to solve the over-fitting problem. The results of an average 30 simulations generated from ten stationary signals are demonstrates. The results of the proposed network were compared with the regularized multilayer neural networks and the regularized self organized neural network inspired by the immune algorithm. The simulation results indicated that the proposed network showed better values in terms of the annualized return in comparison to the benchmarked networks.
AB - A novel type of recurrent neural network, the regularized Dynamic Self Organised Neural Network Inspired by the Immune Algorithm, is presented. The Regularization technique is used with the Dynamic self-organized multilayer perceptrons network that is inspired by the immune algorithm. The regularization has been addressed to improve the generalization and to solve the over-fitting problem. The results of an average 30 simulations generated from ten stationary signals are demonstrates. The results of the proposed network were compared with the regularized multilayer neural networks and the regularized self organized neural network inspired by the immune algorithm. The simulation results indicated that the proposed network showed better values in terms of the annualized return in comparison to the benchmarked networks.
KW - And financial time series prediction
KW - Dynamic neural network
KW - Exchange rate time series
UR - https://www.scopus.com/pages/publications/84958535711
U2 - 10.1007/978-3-319-09330-7_8
DO - 10.1007/978-3-319-09330-7_8
M3 - Conference contribution
AN - SCOPUS:84958535711
SN - 9783319093291
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 56
EP - 62
BT - Intelligent Computing in Bioinformatics - 10th International Conference, ICIC 2014, Proceedings
PB - Springer Verlag
T2 - 10th International Conference on Intelligent Computing, ICIC 2014
Y2 - 3 August 2014 through 6 August 2014
ER -