Dempster-Shafer　theory　(DST)　or　evidence　theory　has　significant　advantages　in　the　fields　of　information　aggregation　and　decision　analysis.　In　this　paper,　in　order　to　overcome　the　counter-intuitive　behavior　or　specificity　changes　caused　by　evidence　theory,　the　evidential　reasoning　(ER)　rule　which　handles　the　weight　and　reliability　of　evidence　in　an　appropriate　way,　is　generalized　to　deal　with　the　combination　of　conflicting　interval-valued　belief　structures　(IBSs).　Specifically,　an　optimization　model　of　pignistic　probability　distance　is　established　from　the　global　perspective　to　provide　the　relative　weights　for　interval　evidence　so　that　the　modified　interval　evidence　can　be　reasonably　combined,　and　then　a　modified　interval　evidence　combination　approach　is　proposed　which　is　based　on　ER　rule.　The　method　can　lead　to　a　rational　combination　of　conflicting　interval　evidence,　which　is　also　a　development　of　Yang＇s　ER　rule.　Numerical　examples　are　provided　to　indicate　that　the　proposed　method　is　not　only　suitable　for　combining　conflict-free　interval　evidence,　but　can　also　suitably　combine　conflicting　interval　evidence.　At　last,　a　case　study　is　conducted　on　the　actual　pattern　recognition　problem　to　illustrate　the　applicability　of　the　proposed　method　and　the　potential　in　dealing　with　the　combination　of　conflicting　interval　evidence.