Real-time　hybrid　simulation　(RTHS)　is　a　testing　method　that　combines　numerical　simulation　and　physical　testing,　enabling　large-scale　or　even　full-scale　tests　of　large　and　complex　engineering　structures　using　the　existing　experimental　facilities.　At　present,　the　accuracy　and　stability　of　RTHS　are　limited　by　the　loading　device　and　numerical　solution　efficiency.　The　experimental　method　was　improved　based　on　the　neural　network,　and　an　off-line　iterative　hybrid　simulation　method　based　on　neural　networks was　implemented.　Taking　the　tuned　damping　structure　as　examples,　the　dynamic　metamodels　of　the　tuned　mass　damper　and　tuned　liquid　damper　were　established　based　on　the　long-short　time　memory　(LSTM) neural　network,　and　the　model　was　iteratively　simulated　globally　with　the　9-story　benchmark　model　to　calculate　the　response　of　the　damping　structure.　The　error　of　damper　reaction　predicted　by　LSTM　neural　network　model　is　within　5.16%.　The　global　iterative　method　can　converge　after　a　limited　number　of　iterations,　and　the　peak　error　of　the　structural　response　is　within　7.85%.　©　2023　Tianjin　University　and　John　Wiley　&　Sons　Australia,　Ltd.