The　construction　process　of　cable　net　structure　is　complicated,　which　leads　to　the　strong　randomness　of　construction　errors.　The　safety　state　of　the　cable　net　structure　is　very　sensitive　to　construction　errors.　Obtaining　the　coupling　relationship　between　construction　errors　and　cable　force　response　efficiently　and　accurately　is　critical　to　developing　the　construction　technique　of　cable　structures.　This　paper　proposed　an　analysis　method　based　on　a　genetic　algorithm　optimized　back　propagation　neural　network　(GA-BPNN)　to　judge　the　influence　of　construction　error　on　the　cable　force　of　single-layer　orthogonal　cable　network　structures.　Taking　the　speed　skating　stadium　of　the　2022　Winter　Olympic　Games　as　the　research　object,　this　paper　analyzed　the　structure　form　of　the　venue.　According　to　the　characteristics　of　cable　network　structure　and　GA-BPNN　calculation,　the　principle　of　construction　error　analysis　was　put　forward.　The　influence　of　construction　errors　of　load-bearing　cables　and　stable　cables　on　cable　force　response　was　analyzed.　The　influence　degree　of　different　component　errors　on　structural　cable　forces　was　obtained,　and　the　most　unfavorable　key　components　were　obtained.　For　the　key　components,　the　influence　trend　of　different　construction　errors　on　cable　force　was　analyzed,　and　the　fitting　formula　was　given.　Driven　by　GA-BPNN,　it　can　realize　the　analysis　of　structural　and　mechanical　responses　under　the　action　of　multi-type,　multi-component,　and　multi-combination　construction　errors.　The　results　show　that　the　research　method　efficiently　and　accurately　obtains　the　performance　law　of　structural　cable　force　under　the　influence　of　construction　error,　effectively　predicts　the　influencing　factors　of　the　structural　safety　risk,　and　effectively　avoids　structural　safety　accidents　caused　by　construction　error.　The　construction　errors　analysis　method　based　on　GA-BPNN　proposed　in　this　paper　can　provide　a　reference　for　similar　structural　analysis　and　application.