Multiple Time Series Analysis with LSTM
Küçük Resim Yok
Tarih
2024
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer Science and Business Media Deutschland GmbH
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Inflation is caused by the growing gap between the amount of money actively involved and the sum of products and services available for purchase. It is an economic and monetary process that manifests itself as a constant rise in prices, a fall in the current value of money. Inflation is a subject that keeps itself constantly updated in our country and around the world. The main purpose of the central banks, which are dependent on countries in the world and continue their activities, on the economy is to ensure price stability permanently. In recent years, artificial intelligence techniques have been used more and more in order to consistently predict the value of inflation in the future and to make future studies with the forecasts obtained. The aim of this study is to estimate inflation in the Turkish economy with time series analysis by using LSTM (Long Short Term Memory) model, which is one of the artificial neural networks types, on a python computer program. With this study, the estimation made by the LSTM model showed result when compared in terms of MAPE and MSE statistical analyses. It has been observed that the irregular increase in the inflation value within the country in the recent periods directly affects the success level of the models. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Açıklama
12th International Symposium on Intelligent Manufacturing and Service Systems, IMSS 2023 -- 2023-05-26 through 2023-05-28 -- Istanbul -- 302369
Anahtar Kelimeler
Artificial Intelligence, Deep Learning, Inflation, LSTM
Kaynak
Lecture Notes in Mechanical Engineering
WoS Q Değeri
Scopus Q Değeri
Q4
