AS-FOA优化GRNN网络的财务预警研究  

Employing AS-FOA for Optimization of GRNN Network with Application to Financial Warning Research

作　　者：王英博[1] 柴佳佳 

机构地区：[1]辽宁工程技术大学软件学院,葫芦岛125105

出　　处：《计算机科学》2016年第7期275-280,共6页Computer Science

基　　金：国家科技支撑计划(2013BAH12F00)资助

摘　　要：针对果蝇算法在复杂情况下寻优时易陷入局部最优等缺陷,提出一种自适应变步长果蝇算法(AS-FOA)。采用改进果蝇算法寻找GRNN网络最优参数,并利用财务数据进行危机预警以验证算法的可行性。AS-FOA算法通过赋予果蝇两次随机方向,同时引入稳定阈和适应度步长因子的概念,界定了果蝇的活跃与稳定状态,有效解决了寻优过程中因陷入局部最优而导致的收敛缓慢和低精度问题。实验表明:AS-FOA能够快速找到GRNN网络中的最佳参数,且应用于财务数据后达到的预警准确率较高。The process of fruit fly optimization algorithm（FOA） optimizing complex problems easily falls into local optimum. In order to solve the problem, adaptive step fruit fly optimization algorithm （AS-FOA） was put forward. The improved FOA was used to find GRNN network optimal parameters, and financial data were used for the crisis warning to verify the feasibility of the algorithm. The algorithm gives fruit fly two random directions, meanwhile introduces two concepts, which are stability threshold and fitness step length factor, in order to define the flies＇ active and steady state, thus effectively preventing local optimum-induced slow convergence and low accuracy in the process of searching the optimal parameters of GRNN by FOA. The experimental results show that AS-FOA can quickly find the best parameters of GRNN network and achieve higher warning accuracy after being applied to financial data.

关 键 词：FOA GRNN网络优化 稳定阈 适应度步长因子 财务预警 

分 类 号：TP3-05[自动化与计算机技术—计算机科学与技术]