Open AccessLife Cycle Cost Estimation of Large Freight Cars Based on BP Neural Network Integration
Author(s) -
Huiqing Wen,
Yin Dongyang,
Xiaochuan Chen
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/563/5/052065
Subject(s) - artificial neural network , driving cycle , estimation , automotive engineering , life cycle cost analysis , torque , engineering , computer science , transport engineering , reliability engineering , systems engineering , artificial intelligence , electric vehicle , power (physics) , physics , quantum mechanics , thermodynamics
With the continuous growth of China’s economy, the demand for large freight cars is increasing day by day. Therefore, it is necessary to estimate the total life cycle cost of large freight cars. Design for cost (DFC) is a method to reduce the LCC-Life Cycle Cost from the perspective of Design. From the perspective of DFC, the design features of large freight cars are mainly obtained through analysis, such as wheelbase, rated load, torque and other parameters, and LCC is estimated based on BP neural network integration.