基于改进AHP算法的某武器质量评估研究

Research on quality evaluation based on improved AHP algorithm for certain weaponc

武器的质量评估是其研制和维护过程中的重要环节,在定期检验次数有限的情况下,质量评估的精确率一直是影响战斗力生成的瓶颈。以层次分析法(AHP)递阶层次思想为主导,基于BP神经网络,结合指数评估法,提出了质量评估的一种改进算法:基于层次分析的神经网络算法,并给出了建立模型的方法和步骤,模型有效解决了精确率在武器质量评估中的问题。通过具体算例,说明该方法有效,并可将其推广到其它类似武器系统质量评估应用中。

The quality evaluation of weapon system is a very important tache in process of developing and maintaining.In the case of limited time-test number,the accuracy rate of quality evaluation has been the bottleneck in making battle effectiveness.According to the hierarchical thinking in analytic hierarchy process（AHP）,based on back-propagation neutral network,and combining index evaluation method,we present an improved algorithm： neural network algorithm based on analytic hierarchy process,and gives the methods and procedures in establishing model.Model is an effective solution to the accuracy rate in the quality evaluation of weapon.Example shows the method is effective,and can be extended to other similar weapon systems quality evaluation.