Hae LUTPubista
Aineistot 1-9 / 9
Time series clustering by extracted features
(2019)
Clustering electricity consumers can give insight into how a particular consumption profile is related to other attributes of the customer, for example the residence size or whether a sauna is in use or not. Furthermore, ...
Analysing electricity consumption data by fast search and find of density peaks
(2017)
The aim of this thesis is to compare a clustering method called Clustering by fast search and find of density peaks (CFSFDP) (Rodriguez et al. 2014) to two traditional clustering methods in analysis electricity consumption. ...
Clustering electricity consumption data to identify optimal electricity contracts
(2020)
This thesis is aimed to study development of electricity consumption trends, cluster historical consumption time series and aim to determine optimal price contract for both individual clusters and customers.
First main ...
Image clustering for unsupervised analysis of plankton data
(2020)
Advancements in automated imaging has made it possible to enhance the data both in terms of quantity and quality. This has prompted the development of plankton imaging systems for acquiring the species level information ...
Unsupervised profiling of electricity consumers for load forecasting applications
(2020)
Electric power suppliers are typically interested in profiling their customers. Different
consumer categories or load profiles can give insight into behavior which affects the power grid and facilitate load forecasting ...
Plankton image clustering using similarity metric learning
(2022)
Technological advancement has evolved the imaging equipment used in plankton imaging. Nowadays it is possible to take images more efficiently. Due to the increased amount of images the processing time is longer. The ...
Clustering and prediction with a Gaussian process mixture model
(2021)
Gaussian processes provide a powerful Bayesian approach to many machine learning tasks. Unfortunately, their application has been limited by the cubic computational complexity of inference. Mixtures of Gaussian processes ...
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 ...
Moodle forums : exploration into logged data and applying machine learning to get further insight
(2023)
This work investigates the data logged into Moodle logs in relation to the usage of forums, which while not containing the text itself contains information about who did what and where. The data was from a programming ...