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Customer segmentation and churn prediction via customer metrics
(IEEE, 2022)
Bu çalışmada faktoring sektöründe faaliyet gösteren müşterilerin geçmişte yapmış oldukları işlem hareketleri ve sahip oldukları risk, limit ve şirket verileri üzerinden, son işlem tarihlerinden sonra gelecek üç ay içerisinde ...
Transaction Volume Estimation in Financial Markets with LSTM
(IEEE, 2023)
In this study, it was aimed to determine the transaction volume that will be encountered in the future (hourly) in the factoring sector, and then to take financial and operational action early. For the study, the LSTM ...
Enhancing quality control in plastic injection production: deep learning-based detection and classification of defects
(IEEE, 2023)
This study investigates the applicability of diverse deep learning techniques in detecting and classifying defects within plastic injection manufacturing processes. The findings derived from the models yield several feasible ...
Segmentation for factoring customers: using unsupervised machine learning algorithms
(IEEE, 2023)
Nowadays the fact that technology facilitates data collection is an important opportunity, as well as making the management of all this data difficult and makes no sense unless it is well processed. This stored data is ...
High-performance real-time data processing: managing data using Debezium, Postgres, Kafka, and Redis
(IEEE, 2023)
This research focuses on monitoring and transferring logs of operations performed on a relational database, specifically PostgreSQL, in real-time using an event-driven approach. The logs generated from database operations ...
GRAFRAUD: Fraud detection using graph databases and neural networks
(IEEE, 2023)
The issue of fraud has become a significant concern for many companies, particularly in the finance sector, but the traditional methods of detecting fraud are no longer adequate. Innovative technologies are necessary to ...