International Data Science & Engineering Symposium

CO2 Emission and Energy Consumption for Different Climate and Building Materials

Salih HİMMETOĞLU Yılmaz DELİCE Emel KIZILKAYA AYDOĞAN

Abstract

With the development of technology from past to present, the types, properties and product range of the materials used in the buildings are quite developed. Therefore, the effects of climate, environmental conditions and energy consumption cannot be ignored for selecting these materials used in the buildings. Usage of materials with the same characteristics for buildings to be built on different climate may lead to adverse effects about energy-saving and green gasses. Furthermore, the use of the same materials may not be a proper approach even in buildings with a different purpose. In this study, forecasting of energy consumption and CO2 emission is analyzed by utilizing artificial neural network structure according to different climate criteria and material characteristics for public buildings built in recent years. The Effect levels to energy consumption and CO2 emission of the building materials and the climate criteria are determined for buildings serving the same using purpose in different climate characteristics. For the study, different pilot regions where the public buildings are located are chosen according to climatic characteristics and five different building materials used in these public buildings are taken into account. When the results compare according to CO2 emission and energy consumption, it was observed that the conditions which obtain most efficient results are different



Conference
International Data Science & Engineering Symposium
Keywords
Artificial Neural Network Energy Consumption CO2 Emission Data Mining Forecasting Public Buildings

Language
English

Subject
Engineering

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