-1條件下，利用Gleeble-3500熱模擬試驗機進行了等溫壓縮試驗。對實驗獲得的流動應力曲線進行了修正，降低了摩擦與絕熱溫升等因素對流動應力的影響。采用考慮材料參數演化的修正Arrhenius模型和反向傳播人工神經網絡（BP-ANN）模型對鈦合金熱變形過程中的流動應力進行預測，并通過統計分析對預測模型精度進行了評估。將2種預測模型擴展的應力、應變數據植入有限元，模擬了熱壓縮實驗過程。結果表明，Ti-55511合金的流變應力與應變速率呈正相關，與溫度呈負相關，合金軟化機制主要為再結晶。修正后的Arrhenius模型和BP-ANN模型都能描述流體的流動行為，BP-ANN模型在α+β區(qū)域的擬合精度高于修正后的Arrhenius模型，而在β區(qū)域的擬合精度低于修正后的Arrhenius模型。;To investigate the hot flow behavior of Ti-55511 alloy in near-β region, isothermal compression tests were conducted at the temperature of 973-1223 K and the strain rate of 0.001–1 s-1 by Gleeble-3500 thermomechanical simulation equipment. The flow stress curves obtained from experiments were corrected, and the influence of friction and adiabatic temperature rise on flow stress was reduced. The corrected Arrhenius model with consideration of material parameter evolution and the back-propagation artificial neural network (BP-ANN) model were used for flow stress prediction of Ti alloys during hot deformation process, and the precision of these prediction models were evaluated by statistical analysis. The stress and strain data extended by the two prediction models were implanted into finite element to simulate the hot compression process. Results show that the flow stress of Ti-55511 alloy has a positive correlation with strain rate and a negative correlation with temperature. The alloy softening mechanism is primarily the recrystallization. Both the corrected Arrhenius model and BP-ANN model can describe the flow behavior of fluid, and the fitting accuracy of BP-ANN model is higher than that of corrected Arrhenius model in α+β region but lower than that of corrected Arrhenius model in β region."/>