基于遗传神经网络算法的方案质量评估  

Scheme Quality Assessment Based on Genetic Neural Network Algorithms

作　　者：傅勉 王丹丹[1] FU Mian;WANG Dan-dan(Business School,Anhui Xinhua University,Hefei 230088,Anhui,China;Research Center for Quality Education,Anhui Xinhua University,Hefei 230088,Anhui,China)

机构地区：[1]安徽新华学院商学院,安徽合肥230088 [2]安徽新华学院大学生素质教育研究中心,安徽合肥230088

出　　处：《山西师范大学学报（自然科学版）》2020年第4期117-121,共5页Journal of Shanxi Normal University(Natural Science Edition)

基　　金：安徽省质量工程项目(2016sxzx017);安徽新华学院基金(2017kyqd09).

摘　　要：为了提高方案质量评估的精确度和客观性,考虑到遗传算法具有强大的全局搜索能力,神经网络算法具有优良的自适应能力,提出将两种算法相结合,构建混合遗传神经网络算法对方案质量进行合理评估.通过对几组案例的仿真演示,本算法取得了比较满意的结果,验证了本文方法的有效性.In order to improve the objectivity and accuracy of scheme quality evaluation,considering the global optimization ability of genetic algorithm and the excellent adaptive ability of neural network,a hybrid genetic neural network algorithm is proposed to reasonably evaluate the scheme quality by combining genetic algorithm with neural network algorithm.The simulation results of several groups of cases show that the algorithm achieves satisfactory results,which verifies the effectiveness of the proposed method.

关 键 词：遗传算法 神经网络算法 方案 质量评估 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]