A CBR-based power engineering cost estimation method

Li Zhou; Qixin Wang; Li Ma; Fangchao Ke

doi:10.1117/12.2626830

20 December 2021 A CBR-based power engineering cost estimation method

Li Zhou, Qixin Wang, Li Ma, Fangchao Ke

Proceedings Volume 12155, International Conference on Computer Vision, Application, and Design (CVAD 2021); 121550S (2021) https://doi.org/10.1117/12.2626830
Event: International Conference on Computer Vision, Application, and Design (CVAD 2021), 2021, Sanya, China

Abstract

Case-based Reasoning (CBR) is an important reasoning methodology in the field of artificial intelligence. The main idea of CBR is to solve new problems by using historical cases. Since the construction of CBR models need to be based on the data of similar historical cases, the reusability of CBR models is usually low. Constructing CBR models for specific problems is one of the research hot-spots in the field of CBR methodology. The CBR model for power engineering cost estimation is studied in this paper. A novel CBR model considering the characteristics of power engineering industry is proposed. The multidimensional scale change (MDS) method and K-means method are introduced into the proposed CBR model to reduce the data dimensional and solve the problem of low calculation accuracy. An artificial neural network (ANN) model is constructed in the proposed CBR model and the deep learning technology is used to estimate the cost of engineering projects. Simulation results show that the proposed CBR model can estimate the cost of power engineering projects accurately and the estimation error is less than 8%.

Citation Download Citation

Li Zhou, Qixin Wang, Li Ma, and Fangchao Ke "A CBR-based power engineering cost estimation method", Proc. SPIE 12155, International Conference on Computer Vision, Application, and Design (CVAD 2021), 121550S (20 December 2021); https://doi.org/10.1117/12.2626830

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