This　article　proposes　a　risk　assessment　method　based　on　interval　intuitionistic　integrated　cloud　Petri　net　(IIICPN).　The　cloud　model　is　widely　used　in　data　mining　and　knowledge　discovery,　especially　in　risk　assessment　problems　with　linguistic　variables.　However,　the　cloud　models　proposed　in　the　literature　do　not　express　interval-valued　intuitionistic　linguistic　satisfactorily,　and　the　reasoning　methods　based　on　the　cloud　models　cannot　perform　risk　assessment　well.　The　work　in　this　article　includes　the　definition　of　IIIC　and　IIICPN,　the　method　of　converting　the　interval-valued　intuitionistic　uncertain　linguistic　numbers　into　IIIC,　and　the　reasoning　method　of　IIICPN.　As　proofs,　a　subway　fire　accident　model　is　adopted　to　confirm　the　feasibility　of　the　proposed　method,　and　comparison　experiments　between　the　IIICPN　with　general　fuzzy　Petri　net　and　the　trapezium　cloud　model　are　conducted　to　verify　the　superiority　of　the　proposed　model.　Note　to　Practitioners-This　work　deals　with　the　subway　fire　risk　assessment　problem.　It　proposes　a　cloud　model　based　on　interval-valued　intuitionistic　uncertain　linguistic　and　builds　a　cloud-based　Petri　net　model.　The　methods　of　fire　risk　assessment　use　the　existing　fault　trees　or　aggregation　operators　to　combine　all　the　factors　into　consideration,　but　they　do　not　take　the　interaction　of　factors.　The　goal　of　this　work　is　to　assess　the　risk　of　subway　fire　accident　of　subway,　using　fuzzy　linguistic　decision　variables.　The　simulation　results　indicate　that　the　proposed　method　is　highly　effective.　The　obtained　results　can　help　assessors　better　determine　which　factors　may　cause　the　disaster.