With　the　increasing　size　and　cost　of　the　Olympic　Games　and　the　declining　willingness　and　enthusiasm　of　many　cities　to　bid　for　the　Games,　the　IOC　is　facing　a　decline　in　the　number　of　bids　for　the　Summer　and　Winter　Olympic　Games.　In　order　to　explore　an　innovative　incentive　for　countries　and　cities　to　bid　for　the　Olympic　Games,　we　developed　an　Olympic　Games　weighting　model,　and　an　Olympic　Games　permanent　venue　evaluation　clustering　model.　First,　to　construct　the　Olympic　Games　impact　evaluation　model,　we　collected　data　on　13　indicators　in　7　dimensions　from　18　Olympic　Games　host　cities,　calculated　the　impact　coefficients　of　each　dimension　through　gray　prediction　and　difference　calculation,　and　summarized　the　impact　of　the　Olympic　Games　on　host　cities　through　a　coupled　model　based　on　AHP-EWM(AE):Hosting　the　Olympic　Games　has　the　greatest　impact　on　economy,　reputation,　and　urban　development　opportunities,　and　The　impact　on　the　environment　is　the　least.　Second,　in　order　to　select　the　permanent　host　of　the　Olympic　Games　and　to　investigate　possible　changes,　we　calculated　the　scores　of　cities　that　have　already　hosted　the　Olympic　Games　using　the　TOPSIS　method　and　predicted　the　scores　of　non-bidding　countries　using　the　Lasso　regression　algorithm,　collecting　data　on　13　indicators　for　the　next　18　Olympic　bidding　countries.　Then,　we　clustered　and　ranked　the　non-bidding　countries　with　the　bidding　countries　using　a　K-means　clustering　model　to　select　the　location　of　the　permanent　Olympic　host　country;　finally,　we　used　AE　to　calculate　the　weights　of　the　cities　most　suitable　as　permanent　Olympic　host　countries　for　comparison　and　found　that　this　strategy　would　significantly　boost　the　tourism　aspect　of　the　host　city　(14.80%),　but　also　hinder　its　potential　(-16.31%).　©　2023　IEEE.