As　a　hot　research　orientation　of　data　stream　mining,　multiple　data　stream　clustering　tracks　the　evolution　of　multiple　streams　and　partitions　them　according　to　their　similarities.　In　this　paper,　a　multiple　data　stream　clustering　approach　is　proposed,　which　is　based　on　the　combination　of　grey　relational　analysis　and　affinity　propagation　clustering.　A　grey　relational　degree　is　developed　so　that　the　raw　data　can　be　compressed　into　an　incrementally　updatable　grey　relational　synopsis.　The　similarity　between　two　data　streams　is　measured　by　the　grey　relational　degree　calculated　from　the　synopsis.　Finally,　the　affinity　propagation　algorithm　is　used　to　cluster　the　streams.　The　experiments　on　the　real　data　sets　prove　the　effectiveness　of　the　new　method.