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Application of machine learning in decision support system

Jevgēnijs Nikolajevs

ABSTRACT

The aim of the work is to improve the accuracy of predicting wait times in an existing queue management system using machine learning. Client-provided data was analyzed, and models were trained using various machine learning algorithms. Performance measures of the models were collected, and the best one was selected. Additionally, software and a database were developed to manage the training process and evaluate the quality of the models. The quality of the software was assessed using industry-standard methodologies and tested.
Author: Jevgēnijs Nikolajevs
Degree: Bachelor
Year: 2024
Work Language: Latvian
Supervisor: Dr. sc. ing., Jeļena Kijonoka
Faculty: Engineering Faculty
Study programme: Computer Science

KEYWORDS

MACHINE LEARNING, QUEUE MANAGEMENT SYSTEM, PREDICTIVE ANALYTICS, PYTHON, APPLICATION DEVELOPMENT