Analysis and Prediction of Energy Consumption Data, Using Data Mining Software
Year: 2025
Type: article
Abstract: This paper explores the ability of prediction in electricity consumption using data mining techniques and emphasizes the integration of weather conditions and previous consumption trends. The data were obtained from the Public Electricity Company of Kavala Greece, and the study employs data prepossessing techniques to extract pertinent features. For this task, RapidMiner's algorithms were utilized to model intricate relationships between electricity usage, environmental fluctuations, and general consumption behavior. The innovative part of this effort lies in selection and configuration of data with which the algorithm will be feeded. For this purpose, different types of data where used for example temperature, humidity, day and time, rain, season, etc, and moreover, procedures such as Normalization and Factor Analysis, were implemented. All the above are always shaped according to the way that each time, the specific problem has to be defined, so that, the use of results aims to support correct and complete decision making.
Authors: KAZOLIS Dimitrios, FANTIDIS Jacob, FOTAKIS Christos Dionyshs, TRAMANTZAS Kostantinos, TSIANTOS Vassilios
Institution: Democritus University of Thrace
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7036201739
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