Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Predicting sustainability assessment at early facilities design phase
Integrating the aspects of sustainability into facilities design has become a designers’ challenge, and the early design phase is seen as the most important in implementing sustainability into facilities design. Therefore, this paper aims to analyze the factors that influence sustainability assessment of preliminary design of facilities and predicts sustainability assessment depending on those factors.
Data were collected by survey questionnaire distributed to project managers using a six-point Likert scale. Obtained data were modeled with general regression neural network (GRNN) using DTREG software. In total, 27 factors were chosen for determining the most accurate predictive model, and their importance was computed.
The six most important factors for sustainability assessment of facilities design are: work experience, work on several outline design proposals, resolving issues between stakeholders, prioritization of participants in the design phase, procurement management and defining projects’ program and goals. The predictive model that was used for prediction of the sustainability assessment was shown to be highly accurate, with MAPE (mean absolute percentage error) amounting to 2.58 per cent.
Using the same approach, assessment of every other factor for the preliminary design can be predicted and the factors that are most influential to its sustainability can be obtained.
The paper supports the sustainability improvement of the preliminary design of future facilities’ projects, as well as support during the decision-making process.
Predicting sustainability assessment at early facilities design phase
Integrating the aspects of sustainability into facilities design has become a designers’ challenge, and the early design phase is seen as the most important in implementing sustainability into facilities design. Therefore, this paper aims to analyze the factors that influence sustainability assessment of preliminary design of facilities and predicts sustainability assessment depending on those factors.
Data were collected by survey questionnaire distributed to project managers using a six-point Likert scale. Obtained data were modeled with general regression neural network (GRNN) using DTREG software. In total, 27 factors were chosen for determining the most accurate predictive model, and their importance was computed.
The six most important factors for sustainability assessment of facilities design are: work experience, work on several outline design proposals, resolving issues between stakeholders, prioritization of participants in the design phase, procurement management and defining projects’ program and goals. The predictive model that was used for prediction of the sustainability assessment was shown to be highly accurate, with MAPE (mean absolute percentage error) amounting to 2.58 per cent.
Using the same approach, assessment of every other factor for the preliminary design can be predicted and the factors that are most influential to its sustainability can be obtained.
The paper supports the sustainability improvement of the preliminary design of future facilities’ projects, as well as support during the decision-making process.
Predicting sustainability assessment at early facilities design phase
Zileska Pancovska, Valentina (Autor:in) / Petrusheva, Silvana (Autor:in) / Petrovski, Aleksandar (Autor:in)
Facilities ; 35 ; 388-404
03.05.2017
17 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Predicting sustainability assessment at early facilities design phase
| Online Contents | 2017
Sustainability for Advanced Technology Facilities
| British Library Conference Proceedings | 2009
Sustainability for Advanced Technology Facilities
| ASCE | 2009
| DOAJ | 2018