Space　division　multiplexing　(SDM),　as　a　potential　means　of　enhancing　the　capacity　of　optical　transmission　systems,　has　attracted　widespread　attention.　However,　the　adoption　of　SDM　technology　has　also　additionally　increased　resource　dimensions,　introduced　complex　crosstalk,　and　made　it　difficult　to　integrate　multi-dimensional　fragments.　These　factors　force　the　transmission　constraints　to　be　more　complicated.　Especially,　some　factors　have　a　mutual　restraint　relationship,　and　excessive　consideration　of　certain　factors　will　cause　the　deterioration　of　other　ones.　Therefore,　how　to　comprehensively　consider　the　associated　factors　to　achieve　trade-offs　and　improve　network　performance　is　a　problem　worthy　of　study.　This　paper　exploits　the　advantages　of　self-organizing　feature　mapping　(SOFM)　model　to　process　multi-dimensional　data　with　relevant　features.　Firstly,　multiple　constraints　will　be　input　into　SOFM　as　mode　vectors　from　the　core　level.　Then,　by　judging　the　similarity　between　the　competition　layer　neuron　and　the　pattern　vector,　the　position　of　the　winning　neuron　is　located,　which　determines　the　transmission　level　of　each　core.　Finally,　a　routing,　core,　and　spectrum　allocation　scheme　is　proposed　by　preferentially　locating　the　core　with　higher　transmission　quality.　Along　the　selected　core,　the　available　slots　will　be　classified　twice　respectively　by　the　number　of　adjacent　cores　and　crosstalk　direction　to　quickly　find　the　spectrum　blocks　with　relatively　small　crosstalk.　Results　indicate　the　scheme　can　reduce　blocking　probability　and　the　resource　fragmentation.　Further,　it　can　increase　the　resource　utilization　within　tested　network　load.