Multiple Time Series Analysis with LSTM

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dc.contributor.authorŞen, Hasan
dc.contributor.authorEfe, Omer Faruk
dc.date.accessioned2026-02-08T15:11:04Z
dc.date.available2026-02-08T15:11:04Z
dc.date.issued2024
dc.departmentBursa Teknik Üniversitesi
dc.description12th International Symposium on Intelligent Manufacturing and Service Systems, IMSS 2023 -- 2023-05-26 through 2023-05-28 -- Istanbul -- 302369
dc.description.abstractInflation 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.
dc.identifier.doi10.1007/978-981-99-6062-0_72
dc.identifier.endpage760
dc.identifier.isbn9789819650583
dc.identifier.isbn9783031991585
dc.identifier.isbn9783031928185
dc.identifier.isbn9789819529971
dc.identifier.isbn9783031948886
dc.identifier.isbn9789819629985
dc.identifier.isbn9789819536450
dc.identifier.isbn9789819676583
dc.identifier.isbn9789819683710
dc.identifier.isbn9789819667314
dc.identifier.issn2195-4356
dc.identifier.scopus2-s2.0-85174569538
dc.identifier.scopusqualityQ4
dc.identifier.startpage753
dc.identifier.urihttps://doi.org/10.1007/978-981-99-6062-0_72
dc.identifier.urihttps://hdl.handle.net/20.500.12885/5219
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherSpringer Science and Business Media Deutschland GmbH
dc.relation.ispartofLecture Notes in Mechanical Engineering
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzScopus_KA_20260207
dc.subjectArtificial Intelligence
dc.subjectDeep Learning
dc.subjectInflation
dc.subjectLSTM
dc.titleMultiple Time Series Analysis with LSTM
dc.typeConference Object

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