The　method　from　DS　evidence　theory　based　multi-modal　information　decision　fusion　uses　the　classification　structure　information　which　the　correct　and　error　classification　information　provided　by　the　classifiers.　These　two　types　of　information　affect　the　fusion　results　of　DS　evidence　theory.　This　paper　proposes　a　new　method(DShW)　for　correct　and　error　classification　information　in　the　balanced　classification　structure　information　based　on　DS　evidence　theory.　That　is,　a　method　based　on　inertia　weight　normalization　is　introduced　in　the　confusion　matrix.　To　adjust　the　specific　gravity　of　correct　and　error　classification　in　classification　structure　information　by　changing　the　size　of　the　value　h,　so　as　to　achieve　the　purpose　of　balancing　correct　and　error　classification　information.　By　comparing　with　other　classifiers,　we　find　that　the　DShW　method　effectively　improves　the　accuracy　of　decision　fusion.　©　2020　IEEE.