For　a　station　on　Changchun　Metro　Line　1,　it　is　necessary　to　monitor　the　deformation　of　a　cross　passage　during　construction　by　the　CRD　method.　Considering　that　the　erection　of　air　ducts　may　impede　settlement　monitoring,　prediction　of　the　vault　settlement　for　a　typical　section　becomes　even　more　important.　Therefore,　an　ARMA　model　based　on　time　series　was　set　up　based　on　data　preprocessing　for　the　ingate　vault　settlement　and　the　truncated　characteristics　of　its　autocorrelation　function　and　partial　autocorrelation　function.　Values　of　relevant　parameters　were　primarily　determined　based　on　the　recursion　formula　of　the　autocovariance　function　and　the　spectral　density　function　of　the　MA　model,　and　further　optimization　was　carried　out　for　these　parameters　utilizing　a　Newton　iterative　algorithm.　A　model　was　established　based　on　the　settlements　of　the　first　100　days　after　cross　passage　excavation　and　was　used　for　predicting　the　settlements　of　the　next　10　days.　Finally,　a　comparison　was　carried　out　between　the　results　from　a　regression　prediction　and　the　ones　from　field　monitoring　in　order　to　verify　the　feasibility　of　this　model.　The　results　show　that　the　errors　of　the　first　five　days＇　prediction　results　are　smaller　than　that　of　the　regression　prediction,　and　they　tend　to　be　consistent　with　each　other　with　the　passing　of　time,　proving　the　advantages　of　time　series　for　shortterm　prediction.　©　2016,　Editorial　Office　of　＂Modern　Tunnelling　Technology＂.　All　right　reserved.