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    Perceptions of Process Quality in Building Projects 

    Source: Journal of Management in Engineering:;1999:;Volume ( 015 ):;issue: 002
    Author(s): David Arditi; H. Murat Gunaydin
    Publisher: American Society of Civil Engineers
    Abstract: 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 ...
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    Factors That Affect Process Quality in the Life Cycle of Building Projects 

    Source: Journal of Construction Engineering and Management:;1998:;Volume ( 124 ):;issue: 003
    Author(s): David Arditi; H. Murat Gunaydin
    Publisher: American Society of Civil Engineers
    Abstract: The factors that affect process quality in the three phases (design, construction, and operation) of the life cycle of a building project are identified and ranked by degree of importance. The perceptions of long-time ...
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    Determining Attribute Weights in a CBR Model for Early Cost Prediction of Structural Systems 

    Source: Journal of Construction Engineering and Management:;2006:;Volume ( 132 ):;issue: 010
    Author(s): Sevgi Zeynep Doğan; David Arditi; H. Murat Günaydın
    Publisher: American Society of Civil Engineers
    Abstract: 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 ...
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    Using Decision Trees for Determining Attribute Weights in a Case-Based Model of Early Cost Prediction 

    Source: Journal of Construction Engineering and Management:;2008:;Volume ( 134 ):;issue: 002
    Author(s): Sevgi Zeynep Doğan; David Arditi; H. Murat Günaydin
    Publisher: American Society of Civil Engineers
    Abstract: 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 ...
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