评估危机信息传播有效性的模糊人工神经网络方法

Validating information transmitted about a crisis with a fuzzy artificial neural network

如何评估危机信息传播有效性是危机管理研究中一项重要内容,但至今尚缺乏科学的定量评估方法,为弥补此项空白,引入模糊人工神经网络方法.通过对危机信息特征、危机信息传播特征、危机信息传播方式的分析,构建了危机信息传播有效性的评估指标体系.依据评估指标模糊性的特点,应用模糊人工神经网络理论,利用人工神经网络的自学习、非线性动态处理等特征进行危机信息传播有效性的评估,建立了危机信息传播有效性的模糊评估模型,为研究危机信息传播评估中的不确定性、模糊性和动态性提供了一条新的途径,同时也避免了建立复杂的数学模型描述非线性关系所遇到的困难.该文是对危机信息传播有效性评估理论与方法的拓展,为危机信息传播有效性的定量研究提供了思路.

Validating information that has been transmitted about a crisis is an important issue in crisis management,but it still lacks scientific quantitative assessment methods.The authors sought to remedy the gap through discussion and analysis of the features of crisis information as well as typical means for transmission of crisis information.In this way a crisis evaluation index system was built.By using a fuzzy artificial neural network to deal with the fuzziness of an evaluation index,it was possible to build a fuzzy evaluation model to validate transmission of crisis information.The evaluation model in this paper depends on the characteristics of self-learning and non-linear dynamic processing.It also provides a new path for evaluating information that has been transmitted by identifying its uncertainty,fuzziness and dynamic nature.Meanwhile,it avoids the weakness of constructing complex non-linear mathematics models.This research provides a fresh perspective on quantitative research into transmission of crisis information.