Artificial Neural Network Based Model for Forecasting of Inflation in India

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• 作者：Gour Sundar Mitra Thakur^a ; ^{cse.gsmt@gmail.com" class="auth_mail" title="E-mail the corresponding author} ; Rupak Bhattacharyya^b ; ^{mathsrup@gmail.com" class="auth_mail" title="E-mail the corresponding author} ; Seema Sarkar Mondal^c ; ^{seemasarkarmondal@yahoo.co.in" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Inflation forecasting ; Artificial neural network ; Back propagation algorithm
• 刊名：Fuzzy Information and Engineering
• 出版年：2016
• 出版时间：March 2016
• 年：2016
• 卷：8
• 期：1
• 页码：87-100
• 全文大小：6937 K

文摘

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.