Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10322738 | Expert Systems with Applications | 2011 | 7 Pages |
Abstract
Studies performed on the prediction of building energy consumption are increasingly important for selecting the best control strategies against the excessive energy consumptions. This paper presents Adaptive Network Based Inference System (ANFIS) model to forecast building energy consumption in a cold region. The objective of this paper is to examine the feasibility and applicability of ANFIS in building energy load forecasting area. Different combinations of building samples formed by using three different form factors (FF 1/2, FF 1/1 and FF 2/1), nine azimuth angles varied 0o-80o, three transparency ratios of 15%, 20%, 25% and five insulation thicknesses of 0, 2.5, 5, 10 and 15Â cm. Finally, it is observed that ANFIS can be a strong tool with the 96.5 and 83.8% for heating and cooling energy prediction in pre-design stage of energy efficient buildings for choosing the best combinations.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Betul Bektas Ekici, U. Teoman Aksoy,