基于优化神经网络的采集终端软件可靠性预测  

Reliability prediction of acquisition terminal software based on optimization neural network

作　　者：董永乐[1] 毛永梅 张理放 张帆 白露薇 林海军[2] 梁肇聪 Dong Yongle;Mao Yongmei;Zhang Lifang;Zhang Fan;Bai Luwei;Lin Haijun;Liang Zhaocong(Inner Mongolia Power Research Institute,Hohhot 010000,China;Harbin University of Science and Technology,Harbin 150080,China)

机构地区：[1]内蒙古电力科学研究院,呼和浩特010000 [2]哈尔滨理工大学,哈尔滨150080

出　　处：《电测与仪表》2023年第11期174-179,187,共7页Electrical Measurement & Instrumentation

基　　金：黑龙江省自然基金资助项目(F2016021)。

摘　　要：采集终端软件的可靠性是评价软件系统生命周期的一个重要指标。针对多种神经网络和支持向量机等方法在软件系统可靠性评价中存在的参数优化困难、软件系统预测模型的低准确率问题,提出基于SAGFA-BPNN的建模方法。该方法采用PCA对实验数据降维处理,剔除影响模型准确率的冗余和干扰样本;在优化SA和GA的基础上,给出退火遗传融合优化算法(SAGFA),并发挥其全局寻优能力,以及BPNN非线性映射能力,提出SAGFA-BPNN网络,及基于它的建模方法,以提高训练速度、全局寻优能力及准确度。文章还应用该方法对采集终端软件的可靠性进行了预测,预测结果表明,该方法可以有效地提高模型的准确度。The reliability of acquisition terminal software is an essential criterion for the life span of software system.In view of the difficulties of parameter optimization and low accuracy of software system predictive model existing in multi-neural network(NN)method and SVP method in reliability evaluation of software system,method of building model based on simulated annealing genetic fusion algorithm(SAGFA)-BPNN is proposed in this paper.Firstly,PCA is used to reduce the dimension of the experimental data,this is to eliminate the redundancy and interference sample that will affect the accuracy of model.Then,SAGFA is developed based on the optimization of SA and GA method.Furthermore,by utilizing the global optimization property of SAGFA method and the non-linear mapping property of BPNN,the SAGFA-BPNN and the method of its model building are given.This will raise the training speed,improve the ability of global optimization and increase the accuracy of prediction.This method is then applied to predict the reliability of acquisition terminal software and the prediction result shows that the proposed method can effectively raise the accuracy of model.

关 键 词：SAGFA BP神经网络 采集终端 软件可靠性 预测模型 

分 类 号：TM933[电气工程—电力电子与电力传动]