Research on Intelligent Evaluation and Monitoring Method for Cost of Transmission and Transformation Project

With the advancement of fine-grained management of transmission and transformation projects, the construction of an intelligent learning model for the assessment of cost levels is a prerequisite for the implementation of asset management of transmission and transformation projects. To this end, an intelligent assessment and monitoring method for the cost level of transmission and transformation projects is studied. In view of the high-dimensional small sample characteristics of transmission and transformation project cost data, this method constructs cost level evaluation indicators and monitoring error indicators, and proposes a random bit random forest-based transmission and transformation project cost data feature selection method. Based on this, an umbrella-type evaluation monitor was used to build a transmission and transformation project cost level evaluation and online monitoring model. The validity of the algorithm is verified with the actual substation project cost data of a province. The results show that the method proposed in this paper has good feature stability and evaluation accuracy, and can realize online dynamic monitoring of the transmission and substation project cost level.