摘要
突发事件发生后,需要对应急物资需求进行预测,以减少损失。突发事件本身具有的特性使得突发事件的相关数据难以获得。引入案例推理的预测方法,通过模糊粗糙集理论,对突发事件的特征属性进行约简、权重,并进行分配。摒除属性间的相互影响,减少存储空间,提高检索效率,使得权重分配更加客观、合理。最后,通过地震实例验证该方法的可行性和合理性,能够在信息不完备的情况下,很好地解决应急物资的需求预测问题。
In order to minimize the loss of emergent incident ,it is necessary to forecast the demand of emergency materials .Because of the properties of suddenness itself ,it is difficult to obtain the related data of unexpected events .To solve this problem ,the method of forecast based on CBR is considered ,and it is proposed that fuzzy rough set theory can be used to reduce the feature attributes and assign the weights .In this way ,the interaction between attributes can be excluded ,the storage space can be reduced ,and the retrieval efficiency can be improved .The weight distribution is more objective and reasonable through the method .Finally , the feasibility and reasonableness of the method have been verified though seismic examples .It provides a good solution to forecast of demand of emergency supplies in the case of incomplete information .
出处
《交通科技与经济》
2015年第5期1-4,共4页
Technology & Economy in Areas of Communications
基金
国家自然科学基金资助项目(61364028)
关键词
应急物资需求
案例推理
模糊粗糙集
属性约简
权重分配
emergency material demand
CBR
fuzzy rough sets
attribute reduction
weight distribution
