Family cars' Life cycle cost (LCC) estimation model based on the neural network ensemble

Abstract

Design for cost (DFC) is a method that reduces life cycle cost (LCC) at design stage. From the angle of DFC, the design features of family cars were obtained, such as all dimensions, engine power and displacement. At conceptual design stage, cars' LCC were estimated using back propagation (BP) artificial neural networks (ANN) method based on the features. An example was given. Levenberg-Marquardt (LM) and Genetic algorithm (GA) were used to train BP ANN' s weights. The results obtained through the adoptions of neural network ensemble is better than simply use GA or LM algorithm. © 2006 International Federation for Information Processing.