Forecasting Exchange Rate Change between USD and JPY by Using Dynamic Adaptive Neuron-Fuzzy Logic System
نویسنده
چکیده
Foreign exchange rate is a chaotic time series which is consistent with the MackeyGlass equation. Fuzzy logic is an intelligent computational technique and has good potential in forecasting time-series data. This study uses fuzzy logic to study data of exchange rates and build a dynamic adaptive neuron-fuzzy logic forecasting model. The performance of the model built is compared with an autoregressive model by using the same data set.
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تاریخ انتشار 2008