GDL

Journal from gdlhub / 2017-08-21 15:06:13
Oleh : Gour Sundar Mitra Thakur, Rupak Bhattacharyya, Seema Sarkar Mondal, Fuzzy Information and Engineering
Dibuat : 2016-03-21, dengan 1 file

Keyword : Inflation forecastingArtificial neural networkBack propagation algorithm
Url : http://www.sciencedirect.com/science/article/pii/S1616865816300061
Sumber pengambilan dokumen : web

Inflation can be attributed to both microeconomic and macroeconomic factors which influence the stability of the economy of any nation. With the raising of recession at the end of the year 2008, world communities started paying much contemplation on inflation and put enormous hard work to predict it accurately. Prediction of inflation is not a simple task. Moreover, the behavior of inflation is so complex and uncertain that both economists and statisticians have been striving to model and forecast inflation in an accurate way. As a result, many researchers have proposed inflation forecasting models based on different methods; however the accuracy is always being a major constraint. In this paper, we have analyzed the historical monthly economic data of India between January 2000 and December 2012 and constructed an inflation forecasting model based on feed forward back propagation neural network. Initially some critical factors that can considerably influence the inflation of India have been identified, then an efficient artificial neural network (ANN) model has been proposed to forecast the inflation. Accuracy of the model is proved to be satisfactory when compared with the forecasting of some well-known agencies.

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