Construction knowledge discovery system using fuzzy approach

Most research works in simulating construction operations have predominantly focused on modeling and mistreated data preparation that is paramount for simulation. To prepare data for simulation process, a knowledge discovery system (KDS) is indispensable in extracting hidden knowledge from construction data sets. This knowledge is typically hard to obtain using traditional means, such as statistical analysis. The presented research develops, using fuzzy approach, a KDS to prepare, utilize, analyze, and extract the hidden patterns from construction data to predict work task durations. The KDS depends mainly on finding the relation between quantitative and qualitative variables, which affect the duration of construction operations and work tasks as well as prepare data for simulation modeling. It consists of two stages: data processing and mining. Data processing consists of cleaning, integrating, transforming, and selecting the appropriate knowledge. Data mining consists of selecting the factors that affec...

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