Various　uncertainties　often　influence　the　serviceability　of　cable　net　structures,　which　can　impact　their　structural　safety　performance.　The　accurate　identification　of　sensitive　factors　during　the　structure＇s　service　life　and　the　determination　of　its　serviceability　state　is　crucial　for　achieving　intelligent　serviceability　safety.　In　this　paper,　based　on　the　digital　twin　model,　a　multi-factor-based　assessment　method　for　the　serviceability　safety　of　cable　net　structures　was　proposed.　Firstly,　the　assessment　method　for　serviceability　safety　under　multi-factor　influence　was　described　in　detail,　outlining　the　specific　workflow.　Secondly,　key　indicators　that　affect　the　structural　safety　state　are　selected,　and　their　range　of　variation　is　determined.　Subsequently,　a　comprehensive　dataset　of　sample　data,　considering　long-term　multi-factor　influence,　was　constructed,　through　combined　simulation　using　MATLAB　2021　and　ANSYS　15.0.　Finally,　a　support-vector-regression-based　structural　safety　assessment　model　was　established　and　validated.