To　solve　the　problem　of　combinatorial　explosion　in　belief　rule　base　(BRB)　caused　by　too　many　antecedent　attributes,　many　rule　reduction　methods　that　adopt　dimensionality　reduction　techniques　are　proposed.　However,　these　methods　cannot　simultaneously　achieve　the　desired　results,　namely　algorithm　implementation,　reasonability　of　filtering　attributes,　the　number　of　reduced　rule　and　the　accuracy　of　reasoning.　Hence,　a　new　rule　reduction　method　that　uses　correlation　coefficient　and　standard　deviation　integrated　method　is　proposed.　The　kernel　method　is　based　on　the　coefficient　weight　for　reducing　BRB.　An　armored　system　of　systems　also　introduced　to　analyze　the　applicability　of　the　rule　reduction　method　using　the　correlation　coefficient　and　standard　deviation　integrated　method.　The　experimental　results　show　that　the　BRB,　which　is　reduced　by　the　proposed　method,　has　lower　utility　deviation　and　higher　similarity.