系统变化的复杂性导致了系统行为数据的不确定性与异构性，面向多源信息的数据集结导致了表征系统变化规律的灰色异构时序数据的产生。对面向区间灰数与离散灰数的双重异构数据序列预测建模方法展开研究，通过对区间灰数均匀分割处理，得到与离散灰数灰元数量相等的次级区间灰数，进而实现了灰色异构数据的“同质化”转换；在此基础上构建了面向异构数据序列的灰色预测模型，并应用该模型实现了大桥沉降量的有效模拟与准确预测。研究成果对拓展灰色预测模型应用范围具有积极意义。%The complexity of system changes that lead to the uncertainty and heterogeneity of system behavior data ,multi-source information data aggregation often cause heterogeneous date sequence of grey system .This paper studies the modeling method of grey heterogeneous data based interval grey number and discrete grey number ,the internal grey number is evenly divided to get secondary interval grey number w hich is equal to the number of grey elements in discrete grey number ,grey heterogeneous data so as to realize the " homogenization" transformation ,then establishes a grey prediction model of double heterogeneous data sequence;finally ,this model is used to achieve the bridge settlement effectively and accurately predict analog . The research results have a positive significance toenlarge the range of grey prediction model applications .
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