应急物资筹集网络适应性评价的CFNN模型及仿真

优化和提高应急物资筹集能力是应急物资筹集网络适应性评价的主要目的,针对此目的,在构建应急物资筹集网络适应性评价指标体系基础上,把一种基于改进的补偿模糊神经网络(CFNN)智能评价系统引入到应急物资筹集网络的适应性评价中,以解决应急物资筹集网络评价中时间、成本和稳定性指标的模糊性和非线性问题. 仿真实验表明: 改进的CFNN收敛速度快,容错率高,自适应能力强,是应急物资筹集网络适应性评价的有效手段．

CFNN model and simulation of adaptation evaluation of emergency material collection network

Optimizing and improving the ability of emergency material collection is a main purpose for evaluating the adaptation of emergency material collection network. Based on evaluation indexes of emergency material collection network(EMCN), the intelligent evaluation system of improved compensatory fuzzy neural network (CFNN) is introduced to evaluate the adaptation of emergency material collection network, and to solve problems of the fuzzy and non-linear from emergency cost, emergency time and stability of emergency material collection network. Simulation experiments show that the improved CFNN is an effective mean to evaluate the suitability of emergency material collection network with a fast convergence, a high fault tolerance and an adaptive ability.