Architecture / Mimarlık

Permanent URI for this collectionhttps://hdl.handle.net/11147/24

Browse

Filters

1999 - 199912000 - 20082

Settings

Author: search.filters.author.Arditi, DavidEnd date: 2009

Search Results

Now showing 1 - 3 of 3
  • Article
    Citation - WoS: 66
    Citation - Scopus: 76
    Using Decision Trees for Determining Attribute Weights in a Case-Based Model of Early Cost Prediction
    (American Society of Civil Engineers (ASCE), 2008) Doğan, Sevgi Zeynep; Arditi, David; Günaydın, Hüsnü Murat
    This paper compares the performance of three different decision-tree-based methods of assigning attribute weights to be used in a case-based reasoning (CBR) prediction model. The generation of the attribute weights is performed by considering the presence, absence, and the positions of the attributes in the decision tree. This process and the development of the CBR simulation model are described in the paper. The model was tested by using data pertaining to the early design parameters and unit cost of the structural system of residential building projects. The CBR results indicate that the attribute weights generated by taking into account the information gain of all the attributes performed better than the attribute weights generated by considering only the appearance of attributes in the tree. The study is of benefit primarily to researchers, as it compares the impact of attribute weights generated by three different methods and, hence, highlights the fact that the prediction rate of models such as CBR largely depends on the data associated with the parameters used in the model.
  • Article
    Citation - WoS: 87
    Citation - Scopus: 100
    Determining Attribute Weights in a Cbr Model for Early Cost Prediction of Structural Systems
    (American Society of Civil Engineers (ASCE), 2006) Doğan, Sevgi Zeynep; Arditi, David; Günaydın, Hüsnü Murat
    This paper compares the performance of three optimization techniques, namely feature counting, gradient descent, and genetic algorithms (GA) in generating attribute weights that were used in a spreadsheet-based case based reasoning (CBR) prediction model. The generation of the attribute weights by using the three optimization techniques and the development of the procedure used in the CBR model are described in this paper in detail. The model was tested by using data pertaining to the early design parameters and unit cost of the structural system of 29 residential building projects. The results indicated that GA-augmented CBR performed better than CBR used in association with the other two optimization techniques. The study is of benefit primarily to researchers as it compares the impact attribute weights generated by three different optimization techniques on the performance of a CBR prediction tool.
  • Article
    Citation - WoS: 36
    Citation - Scopus: 47
    Perceptions of Process Quality in Building Projects
    (American Society of Civil Engineers (ASCE), 1999) Arditi, David; Günaydın, Hüsnü Murat
    A Delphi process and a questionnaire survey are conducted to investigate the differences in the perceptions of entry-level professionals and long-time practitioners with regard to process quality in building projects. The factors that affect process quality in the three phases (design, construction, and operation) of a building project's life cycle are identified and ranked by the respondents' perceived degree of importance. The findings indicate that the perceptions of entry-level professionals and long-time practitioners are in agreement for most (74%) of the factors. Given the differences in the respondents' background, expectations, and experience, differences in perceptions are to be expected in the remaining 26% of the factors. Analyzing these differences helps in revising and improving existing training courses and academic programs. It is recommended that college programs include courses that treat the administrative aspects involved in the building project in great detail and that continuing education programs cover quality training and life cycle cost analysis.