Prediction of FX Data Using ANFIS and Ann with Combined Approach of Wavelet and Feature Extraction Technique - Handa, Richa; Shrivas, A.K; Hota, H.S (International Journal of Computer Sciences and Engineering, 2025)
This paper analyses the hybridization of intelligent techniques for time series data prediction of FX rate INR/USD to alleviate the limitation of statistical methods for non-linear data. This paper uses the feature extraction to extract the new features, five new features are extracted from the one original feature of INR/USD i.e Next week FX. Wavelet technique has been used for pre-processing the chaotic data series and prepares the de-noised data to get accurate prediction result. ANFIS is uses the non-linear functions and identify the non-linear components to predict the time series data with its fluctuating behaviour. Result came from ANFIS is compare with ANN technique, Error Back Propagation Network (EBPN). The empirical result of Hybridization of Wavelet and Feature selection with ANFIS and ANN shows that ANFIS produces the best prediction result with MAPE 1.568, MAE0.0136 and RMSE 0.0174