Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Using Fuzzy Cognitive Map to Identify the Factors Influencing the Cost of Prefabricated Buildings
In recent years, prefabricated buildings are rising in China gradually. It has the characteristics of saving, high efficiency, and green compared with the traditional cast-in-place buildings. However, the application of prefabricated buildings is slow-moving due to high cost. Fuzzy cognitive map (FCM) is a combination of neural network and fuzzy logic, and it may effectively avoid the complexity of nonlinear models. Besides, its feedback mechanism may respond to the dynamic changes of the whole complex system of the prefabricated building cost. To effectively control the cost of prefabricated buildings, this paper identifies some influencing factors and constructs a causal model (i.e. FCM model) which is composed of nine concepts (nodes). Besides, predictive analysis and diagnostic analysis are carried out based on the FCM model. C1 (scale effect), C6 (PC component cost), C4 (standardization degree of PC components), and C8 (construction management level) have the greatest impact on the cost of prefabricated buildings are concluded. The possible root cause that affects the cost of prefabricated buildings is C1 (scale effect). Accordingly, suggestions are put forward to reduce the cost of prefabricated buildings. The research is helpful in promoting the development of prefabricated buildings as well as the transformation and upgrading of the construction industry.
Using Fuzzy Cognitive Map to Identify the Factors Influencing the Cost of Prefabricated Buildings
In recent years, prefabricated buildings are rising in China gradually. It has the characteristics of saving, high efficiency, and green compared with the traditional cast-in-place buildings. However, the application of prefabricated buildings is slow-moving due to high cost. Fuzzy cognitive map (FCM) is a combination of neural network and fuzzy logic, and it may effectively avoid the complexity of nonlinear models. Besides, its feedback mechanism may respond to the dynamic changes of the whole complex system of the prefabricated building cost. To effectively control the cost of prefabricated buildings, this paper identifies some influencing factors and constructs a causal model (i.e. FCM model) which is composed of nine concepts (nodes). Besides, predictive analysis and diagnostic analysis are carried out based on the FCM model. C1 (scale effect), C6 (PC component cost), C4 (standardization degree of PC components), and C8 (construction management level) have the greatest impact on the cost of prefabricated buildings are concluded. The possible root cause that affects the cost of prefabricated buildings is C1 (scale effect). Accordingly, suggestions are put forward to reduce the cost of prefabricated buildings. The research is helpful in promoting the development of prefabricated buildings as well as the transformation and upgrading of the construction industry.
Using Fuzzy Cognitive Map to Identify the Factors Influencing the Cost of Prefabricated Buildings
Lu, Xinhai (Herausgeber:in) / Zhang, Zuo (Herausgeber:in) / Lu, Weisheng (Herausgeber:in) / Peng, Yi (Herausgeber:in) / Luo, Lan (Autor:in) / Wu, Xia (Autor:in) / Cheng, Liang (Autor:in) / Tu, Zhihao (Autor:in)
International Symposium on Advancement of Construction Management and Real Estate ; 2020 ; Wuhan, China
12.10.2021
15 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Study on carbon emission evaluation and influencing factors of prefabricated buildings
| Springer Verlag | 2024
| DOAJ | 2022
NTIS | 1971