The　BP　neural　network　(BPNN)　is　used　to　research　on　the　speed　prediction.　For　the　problem　that　the　different　initial　weights　and　thresholds　of　the　BPNN　can　influence　the　speed　prediction　accuracy,　a　speed　prediction　method　based　on　the　BPNN　with　GA-　PSO　optimization　algorithm　is　proposed.　A　route　from　Beigongdaximen　to　Baigeqiao　is　selected　as　the　research　path;　then　the　speed　prediction　model　based　on　the　BPNN　is　established.　Based　on　the　optimization　process　between　the　genetic　algorithm　(GA)　and　particle　swarm　optimization　(PSO),　the　speed　prediction　method　based　on　the　BPNN　with　GA-PSO　optimization　algorithm　is　designed　through　the　method　that　the　optimal　weights　and　thresholds　of　the　BPNN　are　determined　by　using　the　iteratively　optimal　method.　Finally,　based　on　the　selected　route,　the　GA-BPNNbased,　the　PSO-BPNN-based　and　the　proposed　speed　prediction　methods　are　used　to　achieve　speed　prediction,　respectively.　The　result　indicates　that,　compared　with　the　other　two　optimal　methods　on　the　BPNN,　the　average　speed　errors　of　the　proposed　method　are　reduced　by　37.1%　and　24.1%,　respectively.　The　proposed　method　can　effectively　improve　the　accuracy　of　the　speed　prediction.　Copyright　©　2017　by　Science　Press.