Research on Group Decision Making of Large-scale Engineering Based on Uncertain Decision Tree Classification Algorithms
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A decision-making model of drilling engineering risk based on decision tree classification algorithm is proposed and constructed according to the characteristics of drilling expert decision-making process and the shortcomings of traditional CBR technology to realize intelligent decision-making of drilling engineering risk. Decision tree method is an important classification method in data mining. Decision tree is a tree structure that similar to flow chart. Among them, each internal node of tree represents the test of an attribute, its branches represent the test results, and each leaf node of tree represents a category. The decision tree model is used to classify a record, which is to find a path from root to leaf according to the attribute test results in the model. The attribute value of the last leaf node is the classification result of this record, and thus constructed a risk case retrieval model. The field test results show that the model effectively improves the accuracy and recall of case retrieval. A prototype system of drilling engineering risk decision-making is developed based on the above, which provides efficient decision support for drilling experts and technicians.
Engineering risk; Decision-making; Classification tree; Case-based reasoning; Pruning