Artificial Intelligence in Standard Localization of Green Buildings in Iran
Subject Areas : محاسبات نرم در علوم مهندسی
Mohamad Rajabi
1
(
Department of Civil Engineering, Faculty of Civil and Earth Resources Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran
)
Javad Majrouhi Sardroud
2
(
Department of Civil Engineering, Faculty of Civil and Earth Resources Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran
)
Ali Kheyroddin
3
(
Department of Civil Engineering, Semnan University, Semnan, Iran
)
Keywords: Renewable Energy, energy consumption, Environmental pollution, Green buildings, Natural soils,
Abstract :
Residential buildings consume a major part of energy, soil and natural materials and play a large role in environmental pollution. Energy consumption in Iran is increasing by 270% in the last 20 years. One of the basic solutions to reduce use of fossil fuels, soil and natural materials is the implementation of green buildings. Green buildings reduce the use of natural sand and soil and are generally replaced by micro-produced waste from various industries and mines. Unfortunately, unlike many countries in world, Iran does not have a native green standard and most investors do not have information about benefits of this type of building. In this research, using opinions of experts in the first stage to identify the advantages and obstacles of the implementation of green buildings and in the second stage, using 6 green standards of the world, a total of 68 items in 5 seasons of site, water, energy, materials and the quality of the indoor environment. It has been identified for the native green standard in Iran. The results of 103 questionnaires indicate that the lack of knowledge about green buildings is the biggest obstacle and the high potential of renewable energy production is introduced as the biggest necessity for the implementation of green buildings. Also, among the total number of green standard items, the optimal performance of energy consumption and the use of renewable energies have been identified as the most influential parameters. Finally, based on artificial intelligence, the total green standard score has been calculated.
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