Cost estimation and performance index prediction for the whole life cycle of family car based on neural network integration

The design for cost(DFC) is a designing method for lowering the whole life cycle cost(LCC) from a design point of view.From the angle of design and through analysis,the designing characteristics that mainly contain parameters of outline dimensions,power of engine and delivery capacity etc.of family car were obtained.By adopting the characteristics based neural network integration method it has been indicated by means of a living example that its life cycle cost(LCC) could then be estimated during the phase of conceptual design,and thus laid an important foundation for lowering its LCC.The LM(Levenberg-Marquardt) method and genetic algorithm(GA) have been adopted respectively while computing the weights of BP neural network.The neural network integration was carried out on the calculation results of these two kinds of algorithms,and found that the result after integration is so much the better.Finally,by adopting the similar method a prediction on partial performance indexes(oil consumption/100 kilometers and car-body mass) of family car was carried out.