臺灣位處地震帶，一旦發生大規模災害，將會造成橋梁倒塌或損壞及用路人傷亡，因此需要評估橋梁於不同地震強度下的損壞狀況，降低災害發生機率。然而台灣橋梁眾多，若要對每座橋梁皆進行結構分析，在運作上將會有時間及預算限制之困難。
國內現行研究以橋梁下部結構-橋柱性能的耐震能力為主，較少同時考量橋梁整體結構，亦未將上部結構資料納入分析。然而上部結構耐震能力不足時，可能造成落橋等災害，影響用路人通行安全。
本研究同時考慮橋梁上、下部各構件之耐震容量，進行41筆案例模型側推分析，透過損傷評估，求得四個損傷等級各節點有效地表加速度(EPA)下之損傷超越機率，作為案例輸出因子。本研究利用專家問卷、SPSS篩選彙整16個顯著影響因子，建立2844筆案例資料庫。應用生物共生演算法最小平方差支持向量機(SOS-LSSVM)建立橋梁整體耐震能力推論模式，將案例資料隨機分成10組，利用交叉驗證準則的概念進行訓練與測試。藉由模式訓練與測試，找出輸入(影響因子)與輸出(各損傷等級損傷超越機率)的映射關係，做出合理的推論。
預測結果顯示SOS-LSSVM其結果優於其他推論方法，表示本研究應用SOS-LSSVM此模式更能有效且準確地做出預測。震時，橋管單位可以本研究模式結果，將推論結果代入橋梁通行失敗機率公式，進行排序，作為依序進行現場勘查之依據。

Taiwan is located in the Circum-Pacific Seismic Zone. Earthquakes may cause the bridge to collapse, so we need to assess the condition of bridges damaged at different earthequake intensity to prevent the loss. However, there are thousands of bridges in Taiwan and it takes a lot of time and cost to do seismic evaluation on each bridge.
Most research about seismic evaluation of the bridge focus on the capacity of pillars in Taiwan. Actually, the bridge may collapse if the capacity of upper structure is insufficient.
This research takes into account the capacity of portions of a bridge to do the seismic capacity evaluation on 41 bridge models. After doing pushover analysis and damage assessment, the probability of damage can be aquired at four levels as the output in the inference model.
The next step is filtering the 16 input factors with the questionnaire distributed to exports and SPSS, and establishing the database with 2844 data. Finally, the Symbiotic Organisms Search- Least Squares SVM (SOS-LSSVM) is applied to the database and the data is divided into 10 folds randomly. The concept of Cross-Validation is used for training and testing to find the relations between input and output data by SOS-LSSVM and establish Inference Model of Bridge Seismic Capacity.
The result of SOS-LSSVM is better than other predictive methods. Hence, SOS-LSSVM can speculate damage probability of bridge effectively. If earthquake happens in the future, the governmrnt can use this inference model to aquire a damage probability at each level, substitute into equation of passage failure probability, sort the result, and follow the result to do the bridge survey in sequence.

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