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A decision support system for the selection of green roof for residential buildings

Mahdiyar, Amir (2017) A decision support system for the selection of green roof for residential buildings. PhD thesis, Universiti Teknologi Malaysia, Faculty of Civil Engineering.

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Abstract

Green roofs have been installed as a sustainable approach for many years all around the world. There are myriad benefits for green roof installation in terms of private and public sectors such as energy saving, stormwater management, and carbon reduction. Furthermore, there are three types of green roofs with different levels of benefits and costs; however, there is lack of model, framework, or decision support system (DSS) to facilitate the process of decision making for selecting the optimum type of green roof. The aim of the research is to develop a DSS to determine the optimum type of green roof. The research was conducted on residential buildings due to the highest percentage of green roof installation among other building categories in Malaysia. Enhanced Fuzzy Delphi Method (EFDM) has been developed for this study as the approach for data collection, while Multi-Criteria Decision Making (MCDM) is adopted in order to develop the DSS. Moreover, Cybernetic Fuzzy Analytic Hierarchy Process (CFAHP) was also developed as the method used in MCDM. EFDM and CFAHP were developed due to the shortcomings of previous methods for the novelty in this research. A database was created for the DSS using EFDM, while CFAHP method was used for developing the DSS. Additionally, in terms of DSS evaluation, hypothetical examples were defined and after obtaining the results, multiple criteria approach was conducted to understand its level of effectiveness and efficiency. DSS evaluation has been conducted involving experts in the field of green roof. Finally, it was concluded that the DSS works well and can be utilized in construction industry in the design phase. The experts’ feedbacks showed that the developed DSS is effective and efficient, and were satisfied with the performance of the DSS.

Item Type:Thesis (PhD)
Additional Information:Thesis (Ph.D (Kejuruteraan Awam)) - Universiti Teknologi Malaysia, 2017; Supervisor : Assoc. Prof. Dr. Arham Abdullah, Prof. Ir. Dr. Rosli Mohamad Zin, Dr. Mohammadereza Vafaei
Subjects:T Technology > TA Engineering (General). Civil engineering (General)
Divisions:Civil Engineering
ID Code:79239
Deposited By: Widya Wahid
Deposited On:14 Oct 2018 08:39
Last Modified:14 Oct 2018 08:39

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