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Predicting lead times of purchase orders using gradient boosting machine
(2020)
A company can make more accurate predictions of its internal processes and sales lead
times when it has accurate predictions of the lead times of purchase orders. It results in more
efficient processes as well as improved ...
Improving the performance of Bayesian deep model training for artery-vein segmentation
(2020)
Retinal images are an important tool for diagnosis of ocular diseases. Automating the process of screening the retinal images would allow wider screening and make diagnosing of patients’ swifter. The possibility of performing ...
Detecting factors affecting contract terminations in the electricity distribution system
(2022)
Distribution system contract terminations are a factor of economic interest in the electricity market, as they affect the willingness of the distribution system operators (DSOs) to invest in the improvement of the distribution ...
Predicting imbalance power price
(2021)
The electricity market is a complex multi-layer system that is designed to balance power consumption and production at every single moment. This thesis focuses on the lowest level of the Finnish electricity market called ...
Comparison of machine learning algorithms in forest tree species classification from aerial images
(2022)
Remotely sensed data, such as satellite and aerial imagery, allow data to be obtained without visiting the area or physical contact with the area to be studied. Collecting remotely sensed data is faster and cheaper than ...
Machine learning techniques applied to energy behavior profiling
(2022)
The European Union has set a goal to reduce greenhouse gas emissions from the year 1990 by at least 55% by 2030. To achieve the goal, sustainable use of energy resources needs to be utilized. This study consists of conducting ...
Classifying customer companies in an enterprise resource planning system using machine learning methods
(2022)
Information systems such as smart phone applications collect large amounts of data about their users. The data is used mostly for the system’s primary task, but machine learning methods can be used to get additional value ...
Material classification in the industry
(2023)
In the industry material classification and quality control are key challenges that require speed and accuracy. Automation of material classification using machine learning classifiers would provide a unified method that ...
Predicting late payment of sales invoices with statistical learning methods
(2023)
Predicting the time at which a company is bound to receive money from their outstanding sales invoices is a part of cash flow forecasting, which helps companies make better financial decisions. This study explores the ...
Statistical quality control via machine learning
(2023)
Faults in the rolling element bearings are a common problem in rotating equipment. Therefore predicting and identifying the faults from vibration signals has gained increased attention. The goal of this thesis is to explore ...