武器系统费用估算的参数法研究

提出了武器系统费用估算中参数法的形式化研究方法,对参数模型的建立、目标函数的建立以及优化参数的求取进行分析.考虑到模型对样本数据的适应能力,采用径向基神经网络建立参数模型;针对模型的拟合精度和推广能力之间的矛盾以及两者的要求,提出建立一种折中的目标函数;针对目标函数的参数较多、形式较为复杂的特点,采用粒子群优化算法计算得到模型的优化参数,最后通过实例加以分析验证.理论研究和计算分析表明,该方法从本质上解决了参数法的模型建立、参数优化等问题,既可以对新参数模型的建立在理论上提供指导,也可以在实践中推广应用,通用性较好.

Formalization study on parametric methods for weapon system cost estimation

Regarding weapon system cost estimation the paper aims at three key problems: the establishment of parametric models,the establishment of objective function and the determination of optimum parameters.The related analysis is extended respectively.Considering the adaptability of models to samples,radial basis function neural network is adopted to establish the parametric model;considering the inconsistency between fitting precision and generalization of models,an eclectic method is adopted to establish the objective function;and considering the multiple parameters and the complex format of objective function,particle swarm optimization algorithm is adopted to optimize model parameters.A verification example is provided.Theoretical research and numerical analysis show that the method can thoroughly solve the problem of model establishment and parameter optimization,supply a theoretical guidance to the new parametric model and has a good performance of currency and popularization.