Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
493919 | Swarm and Evolutionary Computation | 2016 | 6 Pages |
Abstract
In this paper, we explore the possibilities of using the Random Forest algorithm in its regression version to predict the power output of a power plant based on hourly measured data. This is a task commonly leading to a optimization problem that is, in general, best solved using a bio-inspired technique. We extend the results already published on this topic and show that Regression Random Forest can be a better alternative to solve the problem. A comparison of the method with previously published results is included. In order to implement the algorithm in a way that is as efficient as possible, a massively parallel implementation using a Graphics Processing Unit was used and is also described.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Jan Janoušek, Petr Gajdoš, Pavel Dohnálek, Michal Radecký,