High　peak-to-average　power　ratio　(PAPR)　is　one　of　the　major　drawbacks　of　orthogonal　frequency　division　multiplexing　(OFDM)　communication　system,　which　causes　signal　distortion　and　affects　communication　performance.　Partial　transmission　sequence　(PTS)　is　an　effective　method　to　reduce　the　PAPR,　but　it　cannot　adaptively　select　processing　parameters　for　the　signal　and　has　high　computational　complexity.　Aiming　at　the　defects　of　PTS　method,　this　paper　propose　an　adaptive　PTS　method　based　on　fuzzy　neural　network　(FNN-APTS).　The　method　considers　the　signal　and　system　characteristics,　combining　the　learning　ability　of　the　neural　network　with　the　reasoning　ability　of　the　fuzzy　control　method,　to　select　the　processing　parameters　for　the　signal　adaptively.　The　simulation　results　show　that　the　proposed　FNN-APTS　method　can　adapt　to　different　OFDM　models,　reducing　the　computational　complexity　and　improving　the　system　performance　while　ensuring　the　reasonable　PAPR.　(C)&　nbsp;2022　Published　by　Elsevier　Inc.