Based　on　the　artificial　neural　network　method,　the　nonlinear　mapping　between　the　28d　compressive　strength　of　seawater　sea　sand　concrete　and　concrete　water-cement　ratio,　cement　content,　and　the　sand　ratio　was　established　in　Python.　The　results　showed　that　with　reasonable　network　settings,　the　fitting　of　the　model　training　was　good,　and　the　prediction　results　were　satisfactory.　The　mean　relative　error　of　prediction　results　was　3.16%,　and　the　correlation　coefficient　was　0.974.　Therefore,　it　is　possible　to　use　an　artificial　neural　network　to　set　up　a　compressive　strength　prediction　model　for　seawater　sea　sand　concrete.　Compared　with　the　traditional　mix　design　method,　the　artificial　neural　network　design　method　can　decrease　the　number　of　mixing　proportion　adjustments　and　reduce　the　waste　of　labor,　time,　and　materials.　©　2022　The　Author(s).　Published　by　IOP　Publishing　Ltd.