In　order　to　obtain　the　accurate　dynamic　model　of　the　furnace　temperature　of　a　solid　waste　incineration　plant,　the　intelligent　algorithm　based　on　weighted　adaptive　particle　swarm　optimization　algorithm　is　used　for　parameter　identification.　First,　the　transfer　function　model　of　furnace　temperature　is　determined　by　burning　characteristic　analysis.　Then,　the　model　parameters　to　be　identified　are　determined.　Finally,　the　parameters　of　primary　air-furnace　temperature　channel　transfer　function　model　are　identified　by　weighted　adaptive　particle　swarm　optimization　using　preprocessed　data;　In　the　iteration　process,　the　algorithm　can　obtain　the　optimal　weight　value　for　each　iteration　adaptively　according　to　the　objective　function　value　and　maximum　and　minimum　value　of　the　weight,　which　improves　the　identification　accuracy　of　the　algorithm.　The　simulation　results　show　that　the　established　transfer　function　model　can　fully　describe　the　dynamic　characteristics　of　this　condition,　and　proves　the　effectiveness　of　the　weighted　adaptive　particle　swarm　optimization　algorithm,　which　provides　a　basis　for　subsequent　multi-channel　model　identification　of　furnace　temperature.