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Predictive maintenance for Valmet's breast roll shaker
(2019)
Digitalization and the Industrial Internet of Things (IIoT) enables the collection and analysis of vast amounts of data. Big data is often not utilized optimally, especially when regarding the condition and maintenance of ...
Data analytics for predictive maintenance in a pulp mill : case electric motors
(2018)
Industry is going through the fourth industrial revolution, as sensors and devices in industrial
sites are being connected to the Internet. The collected data can be refined with
machine learning and data analytics to ...
Predicting the customer churn with machine learning methods : case: private insurance customer data
(2019)
Customer churn prediction is a field that uses machine learning to predict whether a customer is going to leave the company or not. The goal of this thesis is to study the churn prediction field and apply the knowledge in ...
Predicting short-term traffic speed : a model assessment using spatiotemporal variables
The focus of the thesis is to examine different machine learning models’ ability to predict short-term traffic speed. An autoregressive model, ARIMA model, Linear Regression, K-Nearest Neighbor and Extreme Gradient Boosted ...
Deep reinforcement learning in portfolio management : policy gradient method for S&P-500 stock selection
(2019)
Tämän maisterintutkielman tavoitteena on tutkia syvän vahvistusoppimisen (deep reinforcement learning, DRL) soveltuvuutta salkunhoitoon S&P500-indeksin osakkeista koostuvan osakeportfolion riskikorjatun tuoton parantamiseksi. ...
Insurance claim risk scoring with machine learning algorithms: A case study on developing a predictive system for assessing corporate customers' claim risk
(2018)
Predictive learning algorithms offer tools to automate and improve insurance risk management. The aim of this thesis is to study classification algorithms in risk scoring applications and to evaluate them in the creation ...
Tekoälyn ja koneoppimisen liiketoimintamahdollisuudet teollisuusyrityksessä
(2018)
Tässä kandidaatintyössä selvitetään, miten tekoälyn malleilla luodaan arvoa yritykseen. Työn lopussa esitetään ehdotus tekoälyn potentiaalisista sovelluskohteista kohdeyrityksen prosesseissa. Työssä hyödynnetään aiheeseen ...
Detection and data-driven root cause analysis of paper machine drive anomalies
(2019)
The Industrial Internet has increased interest in the collection and utilization of data. The latter has become easier due to increased computing power and the development of analytical methods. The goal of this thesis is ...
Ohjelmistoon integroitavien tekoälymoduulien nykytila-analyysi
(2020)
Tekoäly on viimeisimpien vuosien aikana kehittynyt yhdeksi tietotekniikan trendikkäimmistä osa-alueista. Samalla myös erilaisten tekoälyratkaisujen määrä on kasvanut merkittävästi. Tämän työn tavoitteena on selvittää näiden ...
Analysis of production testing data and detecting abnormal behavior
(2020)
This thesis presents methods to improve production testing methods by applying unsupervised machine learning to find anomalies from the data collected during testing. These methods are applied to a real-world case with the ...