Abstract
This paper presents two two-stage intelligent hybrid FOREX Rate prediction models comprising chaos, Neural Network (NN) and PSO. In these models, Stage-1 obtains initial predictions and Stage-2 fine tunes them. The exchange rates data of US Dollar versus Japanese Yen (JPY), British Pound (GBP), and Euro (EUR) are used to test the effectiveness of hybrid models. We conclude that the proposed intelligent hybrid models yield better predictions compared to the baseline neural networks and PSO in terms of MSE and MAPE.
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Pradeepkumar, D., Ravi, V. (2014). FOREX Rate Prediction Using Chaos, Neural Network and Particle Swarm Optimization. In: Tan, Y., Shi, Y., Coello, C.A.C. (eds) Advances in Swarm Intelligence. ICSI 2014. Lecture Notes in Computer Science, vol 8795. Springer, Cham. https://doi.org/10.1007/978-3-319-11897-0_42
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DOI: https://doi.org/10.1007/978-3-319-11897-0_42
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