最优速度模型与元胞自动机模型的比较研究

用解析分析与数值仿真的手段研究了一种典型的车辆跟驰模型(OV模型)与元胞自动机模型(NS模型)之间的区别与联系.首先通过对模型规则的分析,证明了确定NS模型是OV模型的一种离散形式.随后针对两模型更复杂的具体形式,通过数值仿真的手段进行了模型的密度-流量关系与模型在开放边界下的动态特性的研究.实验结果表明,从现象来看,OV模型与NS模型具有非常近似的性质,但两种模型的机制不相同,并且各自具有不能相互替代的优势.为交通流模型的使用和改进提供了参考.     

计算二维声腔传递矩阵的正方形线声源模型

在比较现有二维矩形声腔的声源计算模型特点的基础上,提出了一种新的正方形线声源计算模型,用于计算基于模态级数叠加法的压力响应函数.分析表明,此模型不仅可以克服点声源模型的奇异性,而且在合理选择模型的几何尺寸的前提下能得到比面源模型更为均匀的压力分布,提高了传递函数计算的准确率.数值试验考察了此模型的实际应用效果,表明新的线声源数学模型较圆形线声源更为简便,可以提高计算效率. 关键词： 传递矩阵 正方形线声源模型 二维声腔 模态级数叠加法     

Performance of default risk model with barrier option framework and maximum likelihood estimation: Evidence from Taiwan

We investigate the performance of a default risk model based on the barrier option framework with maximum likelihood estimation. We provide empirical validation of the model by showing that implied default barriers are statistically significant for a sample of construction firms in Taiwan over the period 1994-2004. We find that our model dominates the commonly adopted models, Merton model, Z-score model and ZETA model. Moreover, we test the n-year-ahead prediction performance of the model and find evidence that the prediction accuracy of the model improves as the forecast horizon decreases. Finally, we assess the effect of estimated default risk on equity returns and find that default risk is able to explain equity returns and that default risk is a variable worth considering in asset-pricing tests, above and beyond size and book-to-market.     

自适应听觉感知时频分析模型

提出了一种具有强度自适应机制的仿听觉感知时频分析模型—Adaptive Ear Wig Distribution(AEWD),该模型是O'Donovan的Ear Wig Distribution(EWD)模型的扩展。AEWD的主要改进在于使用Patterson等近几年来提出的Cascade Compressive Gammachirp(Cascade cGC)模型,替换原有模型使用的Gammatone(GT)模型构造频域平滑窗,从而使AEWD模型具有了随输入信号功率而自适应调整的能力。相较于EWD模型,AEWD描述的时频分布更加符合听觉感知实际。最后,文中给出了一些典型信号的计算实例,说明了AEWD模型的有效性。      

分数阶FitzHugh-Nagumo模型神经元的动力学特性及其同步

通过对分数阶FitzHugh-Nagumo模型神经元的研究,当外加电流强度作为分岔参数时,发现这种模型神经元从静息态到周期放电态所经历的Hopf分岔点不同于相应的整数阶模型神经元的分岔点;而且分数阶FitzHugh-Nagumo模型神经元呈现周期放电的外加电流强度的范围比相应的整数阶模型神经元的范围小,然而放电频率却比相应的整数阶模型神经元的放电频率高.同时还揭示在周期放电的情况下分数阶FitzHugh-Nagumo模型神经元之间的同步速率比相应的整数阶模型神经元之间的同步速率快.在数值模拟分数阶微分方程 关键词： 分数阶 Hopf分岔 FitzHugh-Nagumo模型 同步     

Cosmology with a variable Chaplygin gas

We consider a new generalized Chaplygin gas model that includes the original Chaplygin gas model as a special case. In such a model the generalized Chaplygin gas evolves as from dust to quiescence or phantom. We show that the background evolution for the model is equivalent to that for a coupled dark energy model with dark matter. The constraints from the current type Ia supernova data favour a phantom-like Chaplygin gas model.     

The predictive performance of a path-dependent exotic-option credit risk model in the emerging market

Most empirical research of the path-dependent, exotic-option credit risk model focuses on developed markets. Taking Taiwan as an example, this study investigates the bankruptcy prediction performance of the path-dependent, barrier option model in the emerging market. We adopt Duan’s (1994) [11], (2000) [12] transformed-data maximum likelihood estimation (MLE) method to directly estimate the unobserved model parameters, and compare the predictive ability of the barrier option model to the commonly adopted credit risk model, Merton’s model. Our empirical findings show that the barrier option model is more powerful than Merton’s model in predicting bankruptcy in the emerging market. Moreover, we find that the barrier option model predicts bankruptcy much better for highly-leveraged firms. Finally, our findings indicate that the prediction accuracy of the credit risk model can be improved by higher asset liquidity and greater financial transparency.     

Mixing search on complex networks

In this article, we derive the first passage time (FPT) distribution and the mean first passage time (MFPT) of random walks from multiple sources on networks. On the basis of analysis and simulation, we find that the MFPT drops substantially when particle number increases at the first stage, and converges to the shortest distance between the sources and the destination when particle number tends to infinite. Given the fact that a Brownian particle from a high-degree node often needs a large number of steps to reach an expected low-degree node, which is the bottleneck for a single random walk, we propose a mixing search model to improve the efficiency of search processes by using random walks from multiple sources to continue the searches from high-degree nodes to destinations. We compare our model with the mixing navigation model proposed by Zhou on complex networks and find that our model converges much faster with lower hardware cost than Zhou’s model. Moreover, simulations on scale-free networks show that the search efficiency of our model is much higher than that of a single random walk, and comparable to that of multiple random walks which have much higher hardware cost than our model. Finally, we discuss the traffic cost of our model, and propose an absorption strategy for our model to recover the additional walkers in networks. Simulations indicate that this strategy reduces the traffic cost of our model effectively.     

Stationary solutions for a modified Peyrard-Bishop DNA model with up to third-neighbor interactions

We investigate a DNA model that takes into account stacking interactions with neighbors up to three bases away. The model is a generalization of the well-known Peyrard-Bishop (PB) model and is motivated by studies that suggest that nearest-neighbor models for base-pair interaction in a DNA chain might not be enough to capture the mechanism and dynamics of DNA base-pair opening. We study stationary solutions of the modified model and investigate their stability. A comparison with the PB model reveals that under a wide range of parameter values the main characteristics of the original model --such as the hyperbolicity of the equilibrium at the origin-- are preserved, but new types of stationary solutions emerge.     

Population Risk Improvement with Model Compression: An Information-Theoretic Approach

It has been reported in many recent works on deep model compression that the population risk of a compressed model can be even better than that of the original model. In this paper, an information-theoretic explanation for this population risk improvement phenomenon is provided by jointly studying the decrease in the generalization error and the increase in the empirical risk that results from model compression. It is first shown that model compression reduces an information-theoretic bound on the generalization error, which suggests that model compression can be interpreted as a regularization technique to avoid overfitting. The increase in empirical risk caused by model compression is then characterized using rate distortion theory. These results imply that the overall population risk could be improved by model compression if the decrease in generalization error exceeds the increase in empirical risk. A linear regression example is presented to demonstrate that such a decrease in population risk due to model compression is indeed possible. Our theoretical results further suggest a way to improve a widely used model compression algorithm, i.e., Hessian-weighted K-means clustering, by regularizing the distance between the clustering centers. Experiments with neural networks are provided to validate our theoretical assertions.     

Jamming Transition in Kinetically Constrained Models with Reflection Symmetry

A class of kinetically constrained models with reflection symmetry is proposed as an extension of the Fredrickson–Andersen model. It is proved that the proposed model on the square lattice exhibits a freezing transition at a non-trivial density. It is conjectured by numerical experiments that the known mechanism of the singular behaviors near the freezing transition in a previously studied model (spiral model) is not responsible for that in the proposed model.     

Analogue correction method of errors and its application to numerical weather prediction

In this paper, an analogue correction method of errors (ACE) based on a complicated atmospheric model is further developed and applied to numerical weather prediction (NWP). The analysis shows that the ACE can effectively reduce model errors by combining the statistical analogue method with the dynamical model together in order that the information of plenty of historical data is utilized in the current complicated NWP model. Furthermore, in the ACE, the differences of the similarities between different historical analogues and the current initial state are considered as the weights for estimating model errors. The results of daily, decad and monthly prediction experiments on a complicated T63 atmospheric model show that the performance of the ACE by correcting model errors based on the estimation of the errors of 4 historical analogue predictions is not only better than that of the scheme of only introducing the correction of the errors of every single analogue prediction, but is also better than that of the T63 model.     

On the Ricci dark energy model

We study the Ricci dark energy model (RDE) which was introduced as an alternative to the holographic dark energy model. We point out that an accelerating phase of the RDE is that of a constant dark energy model. This implies that the RDE is not a new model of explaining the present accelerating universe.     

Negative compressibility property in hinging open-cell Kelvin structure

A new three-dimensional(3 D) cellular model based on hinging open-cell Kelvin structure is proposed for its negative compressibility property. It is shown that this model has adjustable compressibility and does exhibit negative compressibility for some certain conformations. And further study shows that the images of compressibility are symmetrical about the certain lines, which indicates that the mechanical properties of the model in the three axial directions are interchangeable and the model itself has a certain geometric symmetry. A comparison of the Kelvin model with its anisotropic form with the dodecahedron model shows that the Kelvin model has stronger negative compressibility property in all three directions.Therefore, a new and potential method to improve negative compressibility property can be derived by selecting the system type with lower symmetry and increasing the number of geometric parameters.     

THE TWO-PHOTON DEGENERATE JAYNES－CUMMINGS MODEL WITH AND WITHOUT ROTATING-WAVE APPROXIMATION

We take into account the two-photon process and generalize the Jaynes－Cummings (JC) model to the case of atomic level degenerate in the projections of the angular momenta, and we establish two-photon degenerate JC models with and without the rotating-wave approximation (RWA) quantum theory. Comparing the atom population inversion of the generalized JC model with that of the original JC model, we found that the revival period of the degenerate JC model becomes longer and the maximum amplitude of atomic inversion decreases with RWA. Without RWA, the quantum chaos of the generalized JC model is much weaker than that of the original JC model.     

Holographic Dark Energy Model is Consistent with Pantheon SN Ia Data

We constrain three cosmological models,i.e.,ACDM model, holographic dark energy(HDE) model and R_h = ct model by using the recent Pantheon compilation of type la supernovae(SN la), the direction measurements of Hubble parameter H(z), and the baryon acoustic oscillations(BAO). The spatial curvature is considered in the ACDM model and the HDE model. We show that the HDE model in a spatially flat and HDE dominate universe has the same behavior as Rh = ct model if the characteristic parameter of the HDE model C_0 approaches to infinity. Numerical results show that the ACDM model is the best favoured one among the three models. The HDE model is consistent with observational data, the best fitting value of C_0 is around 0.8, which implies that the Rh = ct model should be modified to be compatible with the present cosmological observational data. Combing all the datasets, we give strict constraint on the Hubble constant,where h_0=0.694 ± 0.020 for the ACDM model and h_0= 0.689 ±0.019 for the HDE model.Our results imply that the tension of Hubble constant between Planck collaborations and Riess et al. has been partially relaxed. The constraint on the spatial curvature is also given,where Ω_(k0) =-0.066 ± 0.165 for the ACDM model andΩ_(k0)=0.029 ± 0.067 for the HDE model.     

考虑碳粒表面还原反应的移动火焰锋面(MFF)模型

在原始移动火焰锋面(MFF)模型的基础上,提出一种考虑碳粒表面还原反应的改进MFF模型。该模型给出了包括表面还原反应和 CO容积反应在内的碳粒燃烧反应速率的显式表达式,便于分析和讨论各种工况下碳粒的燃烧状态和影响因素。与原始的 MFF模型和单膜模型相比,所计算的颗粒温度和燃烧速率更符合严格的连续膜模型的预报结果,而计算时间只为连续膜模型的数十万分之一。研究结果表明,改进的 MFF模型是一种简单可行、适于工程应用的碳粒燃烧理论模型。     

Chiral Thirring–Wess model

The vector type of interaction of the Thirring–Wess model was replaced by the chiral type and a new model was presented which was termed as chiral Thirring–Wess model in Rahaman (2015). The model was studied there with a Faddeevian class of regularization. Few ambiguity parameters were allowed there with the apprehension that unitarity might be threatened like the chiral generation of the Schwinger model. In the present work it has been shown that no counter term containing the regularization ambiguity is needed for this model to be physically sensible. So the chiral Thirring–Wess model is studied here without the presence of any ambiguity parameter and it has been found that the model not only remains exactly solvable but also does not lose the unitarity like the chiral generation of the Schwinger model. The phase space structure and the theoretical spectrum of this new model have been determined in the present scenario. The theoretical spectrum is found to contain a massive boson with ambiguity free mass and a massless boson.