Forecasting the Exchange Rate Using the Improved SAPSO Neural Network

Abstract:

The paper researches on the behavior of particles in the PSO, and improves the situation of easily falling into local optimum by the right combination of simulated annealing and PSO. In the paper, the author compared the original PSO and the improved SAPSO algorithms in neural network training. The empirical research shows that the improved algorithm performed better than the PSO algorithm in global search ability, and the prediction accuracy is greatly increased.

• Periodical: Advanced Materials Research (Volumes 468-471)
• Pages: 1714-1720
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.468-471.1714
• Online since: February 2012
• Authors: Li Meng, Li Jun Dong
• Keywords: Exchange Rate Forecasts, Particle Swarm Optimization (PSO), Simulated Annealing (SA), Simulated Annealing-Particle Swarm Optimization

References

[1] Li M, Lin S. Several Problems of Exchange Rate Forecasting Using Neural Network.International Symposium on Intelligent Information Systems and Applications, OCT 28-30, 2009 Qingdao, PEOPLES R CHINA.

[2] Wolfgang Polasek and Lei Ren. A multivariate GARCH - M model for exchange rates in the US, Germany and Japan [M]. Institute of Statistics and Econometrics University of Basel, 1999.

[3] Jerry Coakley and Ana - Maria Fuertes.Nonparametric cointegration analysis of real exchange rate [J].Applied Financial Economics, 2001, (11): 1 - 8.

DOI: 10.1080/09603100150210200

[4] Guoqiang Zhang, Eddy Patuwo, Michael Hu. Forecasting with artificial neural networks: The state of the art [J].International Journal of Forecasting, 1998, 14: 35 - 62.

DOI: 10.1016/s0169-2070(97)00044-7

[5] Y Shi, RC Eberhart. A modified swarm optimizer [A].IEEE International Conference of Evolutionary Computation [C]. Anchorage, Alaska: IEEE Press, May, 1998.

DOI: 10.1109/icec.1998.699146

[6] Hongbo Liu, XiukunWang, Jun Meng.The algorithm study of Neural network based on particle swarm optimization[J].Minitype Computer Systems, 2005.

[7] Suihua Wang, naiqin Fen, Aiguo Li.The BP network learning algorithm based on particle swarm optimization [J]. Computer Applications and Software, 2003.

[8] Xuewen Li, Siyi Jin, Shaohui Tao.The application of simulated annealing particle swarm algorithm in integrated chemical process[J]. Journal of Qindao University of Science and Technology (Natural Science Edition), 2011.2.

[9] Sadati N, Amraee T, Ranjbar A M. A global particle swarm based-simulated annealing optimization technique for under-voltage load shedding problem. [J]. Applied Soft Computing, 2009,9 (2) :652-657.

DOI: 10.1016/j.asoc.2008.09.005

[10] Li Meng, Shaoxiong Chen.The assessment of scientific and technological achievements of colleges and universities based on simulated annealing neural network [J]. Technology Management Research, 2011, (15) :67-72.