Next Article in Journal
On the Construction of Differential Inclusion with Prescribed Integral Funnel
Previous Article in Journal
An Algorithm for Segment Stability
Article Menu

Article Versions

Export Article

Mathematical and Computational Applications is published by MDPI from Volume 21 Issue 1 (2016). Articles in this Issue were published by another publisher in Open Access under a CC-BY (or CC-BY-NC-ND) licence. Articles are hosted by MDPI on as a courtesy and upon agreement with the previous journal publisher.
Open AccessArticle
Math. Comput. Appl. 2008, 13(2), 71-80;

Long Term Energy Consumption Forecasting Using Genetic Programming

Department of Computer Engineering, Yasar University, 35500 Izmir, Turkey
Department of Electrical and Electronics Engineering, Kahramanmaras Sutcu Imam University, Kahramanmaras, Turkey
Authors to whom correspondence should be addressed.
Published: 1 August 2008
PDF [163 KB, uploaded 31 March 2016]


Managing electrical energy supply is a complex task. The most important part of electric utility resource planning is forecasting of the future load demand in the regional or national service area. This is usually achieved by constructing models on relative information, such as climate and previous load demand data. In this paper, a genetic programming approach is proposed to forecast long term electrical power consumption in the area covered by a utility situated in the southeast of Turkey. The empirical results demonstrate successful load forecast with a low error rate.
Keywords: genetic programming; load forecasting; symbolic regression genetic programming; load forecasting; symbolic regression
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

Share & Cite This Article

MDPI and ACS Style

Karabulut, K.; Alkan, A.; Yilmaz, A.S. Long Term Energy Consumption Forecasting Using Genetic Programming. Math. Comput. Appl. 2008, 13, 71-80.

Show more citation formats Show less citations formats

Article Metrics

Article Access Statistics



[Return to top]
Math. Comput. Appl. EISSN 2297-8747 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top