Rule-Based Mamdani-Type Fuzzy Modelling of Buildings Annual Heating Energy Need in Design of Industrial Buildings in Konya-Turkey
ABSTRACT In this study, it is aimed to present a model in which measures can be taken to improve the energy performance of buildings while designing industrial areas. Within the context of the study, it was investigated in the workplace buildings in the Eski Industry and Karatay Industry in Konya. As a result of the research conducted in the workplaces in the area, 128 different building alternatives emerged in terms of design parameters such as building size, orientation, and exterior wall material properties. Annual heating energy needs of these alternatives are calculated by the calculation method in TSE 825. A fuzzy logic (FL) model, an artificial intelligence method, was created by using some of the calculated values. The rest of the calculated heating energy need values and the values obtained from the FL model were compared with the multiple coefficients of determination (R-squared). As a result of the comparison, it was revealed that the FL model created predicted the annual heating energy need of the buildings by 98.1%. This shows that the FL model created can be used to estimate the annual heating energy need at an accuracy rate of 98.1% of the single volume industrial buildings to be designed.