GDL

Journal from gdlhub / 2017-08-15 15:20:30
Oleh : Pradyot Ranjan Jena , Ritanjali Majhi , Babita Majhi, King Saud University
Dibuat : 2015-10-15, dengan 1 file

Keyword : Artificial neural network Exchange rate forecasting Functional link artificial neural network (FLANN) Knowledge guided ANN model
Url : http://www.sciencedirect.com/science/article/pii/S1319157815000622
Sumber pengambilan dokumen : web

This paper presents a new adaptive forecasting model using a knowledge guided artificial neural network (KGANN) structure for efficient prediction of exchange rate. The new structure has two parallel systems. The first system is a least mean square (LMS) trained adaptive linear combiner, whereas the second system employs an adaptive FLANN model to supplement the knowledge base with an objective to improve its performance value. The output of a trained LMS model is added to an adaptive FLANN model to provide a more accurate exchange rate compared to that predicted by either a simple LMS or a FLANN model. This finding has been demonstrated through an exhausting computer simulation study and using real life data. Thus the proposed KGANN is an efficient forecasting model for exchange rate prediction.

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