## 1 Introduction  
Ti-10V-2 Fe-3 Al alloy, a typical near-\(\beta\) titanium alloy, has the advantages of high strength, good toughness, excellent stress-corrosion resistance, etc., so it was widely utilized for key structural parts in the aerospace industry. It is universally acknowledged that stress-strain data play important roles in many areas, for instances speculating work hardening (WH) and dynamic recovery (DRV) [1], characterizing dynamic recrystallization evolution [2], improving processing maps [3], etc. A precise model of flow behaviors is critical to reflect material properties and investigate microscopic deformation mechanisms. The pre-existing literature demonstrates that there are close relationships among flow stress, strain, strain rate and temperature. Therefore, it is important to construct and further accurately predict the highly non-linear flow behaviors of materials. Nowadays, there exist three representative models in characterizing flow behaviors of metals, i.e., the empirical/semiempirical model, the analytical model and the phenomenological model [4; 5; 6]. [PERSON] presented a typical empirical model (\(\sigma=K_{H}\epsilon^{n}\)) for plastic deformation with a lower level of accuracy, in which \(K_{\rm H}\) and \(n\) are constants [7]. Afterwards, [PERSON] et al. [8] proposed an improved empirical model with a higher level of accuracy (correlation coefficient \(R=0.998\)) due to considering the effects of strain rate and strain on stress. However, the empirical model cannot accurately track the highly non-linear flow behaviors at different strain rates and temperatures. Additionally, many parameters of the empirical model need to be recalculated when some new experimental data are involved. The analytical model requires explicit and thorough study of microscopic deformation mechanisms, such as dislocation theory, DRV, DRX, etc. [9]. [PERSON] et al. established an analytical model (\(R\approx 0.988\)), which just considered the phase mixture law and boundary layer characteristics of the hot deformation behaviors of functionally-graded steels [10]. [PERSON] et al. established the analytical constitutive models involving dislocations interaction mechanisms and thermal activation energy for the flow behaviors under different temperatures and strain rates of face centered cubic (FCC) and body centered cubic (BCC) metals [11]. In the investigation of [PERSON] et al., the mobile dislocation density has different influences on flow behaviors at different temperatures and strain rates, so it needs to establish several constitutive models at different deformation conditions; otherwise, the physical-based analytical model cannot accurately characterize the highly non-linear deformation behaviors [11]. Besides, analytical models need many precise experiment data to construct a mathematical model of complicated microscopic deformation mechanisms. Thereby, analytical models have not been widely utilized in characterizing intricate flow behaviors of metals. The phenomenological model involves the mathematical regression equation and intelligence algorithm, and it does not need to deeply investigate complicated microscopic deformation mechanisms. The mathematical regression equations just need to calculate some essential material constants and further be fitted based on limited experimental data. At present, the typical Arrhenius-type equation of the phenomenological model and its modified forms were used to characterize the hot flow behaviors of many materials, such as Ti60 (\(R\approx 0.99\)) [12], Ti-6 Al-4V [13], pure titanium [14], etc. Other phenomenological models involve the representative Johnson-Cook model (\(R=0.9772\)), the Fields-Backofen model (\(R=0.87025\)), the Khan-Huang-Liang model (\(R=0.96559\)), the mechanical threshold stress model (\(R=0.9614\)), etc. ; nevertheless, they have large fluctuant accuracies at different strain rates and temperatures [15]. Additionally, [PERSON] et al.