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Application of machine learning in decision support system

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

Supervisor: Jeļena Kijonoka

Degree: Bachelor

Year: 2024

Work Language: Latvian

Study programme: Computer Science

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PREDICTIVE ANALYTICS FOR ONLINE CASINO REVENUE IN THE AUSTRALIAN MARKET.

This thesis investigates the influence of economic indicators and weather conditions on online slot machine gambling habits and revenues in Australia. By reviewing the interplay of GDP, CPI, and unemployment rates, the study uncovers their impact on gambling behaviors, revealing that a healthier economy boosts gambling expenditures while financial strain reduces participation. Weather's impact was minimal, likely due to the indoor nature of gambling. Predictive models, including Multiple Linear Regression, ARIMAX, and SARIMAX, were developed and evaluated. ARIMAX and SARIMAX models proved more accurate for predicting gross gaming revenue and winning bets, capturing seasonal and external influences effectively. This research provides insights for policymakers and industry stakeholders, emphasizing the need for localized studies to better understand these dynamics and improve strategic planning in the gambling sector. Future work should focus on expanding datasets and incorporating diverse economic and weather patterns to enhance predictive accuracy and industry applicability.

Author: Jānis Želannovs

Supervisor: Nadežda Spiridovska

Degree: Master

Year: 2024

Work Language: English

Study programme: Computer Sciences

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