Currently, in equipment system cost estimation, parametric models are applied widely. In this paper, on the base of the concrete analysis on the adopted cost estimation model, the discussion was given on the universal analytical procedure in equipment system cost estimation, and the establishment of objective functions and the determination of model parameters were analyzed in parametric models and a sort of modeling method was brought forward considering the fitting accuracy and generalization capability, finally a practical modeling problem was transformed into a nonlinear system optimization problem and particle swarm optimization (PSO) was adopted to obtain the model parameters aim at the complicated optimization objective function. All of those were analyzed through a case. Theoretical researches and computational analyses show that the proposed method has essentially solved the problems of model establishment and parameter optimization in parametric methods, has the good universality and strong generalization capability, and can be used as the appraisal standard of parameter cost estimation models and the basic of self-adapting modeling of parametric cost estimation.
[1]
Yang Guangyou,et al.
A Modified Particle Swarm Optimizer Algorithm
,
2007,
2007 8th International Conference on Electronic Measurement and Instruments.
[2]
Harry G. Campbell,et al.
AN INTRODUCTION TO EQUIPMENT COST ESTIMATING
,
1969
.
[3]
David Birkes,et al.
Alternative Methods of Regression: Birkes/Alternative
,
1993
.
[4]
Zhu Jia.
The Application of ANFIS Network in the Study of the Cost Estimation of Avionics Equipment
,
2002
.
[5]
Riccardo Poli,et al.
Particle swarm optimization
,
1995,
Swarm Intelligence.