Aviation equipment cost prediction under small sample size

To improve prediction accuracy of aviation equipment cost under small sample size, a prediction model named information diffusion support vector machine is proposed after combining the information diffusion method and support vector machine. The topology and modeling process of the model are also described. The model parameters include both continuous parameters and discrete parameters, so that a different update strategy is adopted to each component of the particle position when solving the problem of model parameter selection using the particle swarm optimization. Finally, the information diffusion support vector machine is applied to the production cost prediction of military aircraft avionics equipment. The average absolute relative error of the result is 3.3%, which can satisfy actual requirement.