Combined model of GM (0, N) and neural network algorithm for civil aircraft cost estimation

Author

Xie Nai-ming ; Liu Feng-hua ; Song Ding

Author_Institution

Coll. of Econ. & Manage., Nanjing Univ. of Aeronaut. & Astronaut., Nanjing, China

fYear

2014

fDate

5-8 Oct. 2014

Firstpage

3526

Lastpage

3530

Abstract

Cost estimation is the key problem in production management of civil aircraft. Consider the cost information of similar products can not be easily gathered, a combination model of GM (0, N) model and BP neural network algorithm is proposed. The superiorities of simulation of BP neural network algorithm and poor information generating of GM (0, N) can be effectively combined. So the new algorithm of combination model is given out. The case of cost estimation of civil aircraft is used to test the validity of the proposed model. To compare with the traditional multiple linear regression model and simple GM (0, N) model, the results indicated that the proposed model can do the work better.

Keywords

aerospace computing; aircraft; backpropagation; neural nets; queueing theory; regression analysis; BP neural network algorithm; GM (0,N) model; civil aircraft cost estimation; combination model; multiple linear regression model; Aircraft; Atmospheric modeling; Biological neural networks; Data models; Estimation; Mathematical model; Predictive models; BP neural network algorithm; Cost estimation; GM (0, N) model; Multiple linear regression;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man and Cybernetics (SMC), 2014 IEEE International Conference on

Conference_Location

San Diego, CA

Type

conf

DOI

10.1109/SMC.2014.6974476

Filename

6974476