Venditti, ClaudiaAdrover, AlessandraGiona, Massimiliano
18页查看更多>>摘要：The motion of non-interacting Brownian particles in the washboard potential is investigated in inertial regimes, when the overdamped approximation does not yield accurate predictions. The analysis is based on homogenization methods, deriving closed-form expressions for the long-term transport properties, i.e. effective velocity and diffusion coefficient. Different reduced models of increasing complexity, improving the overdamped approximation, are developed starting from the basic assumption that the velocity variable can be split into an "almost" deterministic and a fully stochastic contribution. The almost deterministic velocity term can be estimated from a fully deterministic or from a stochastic slow inertial manifold. The latter approach provides accurate predictions for all the asymptotic transport properties. (C) 2021 Elsevier B.V. All rights reserved.
原文链接:
NSTL
Elsevier
Huang, HaichaoChen, JingyaSun, RuiWang, Shuang...
15页查看更多>>摘要：Traffic flow decomposition is an alternative method to explore the composition of traffic flow and improve prediction accuracy. However, most of them suffer from the inability to fully utilize the character of traffic data. This paper presents a novel framework for traffic flow decomposition and modeling named Time Series Decomposition (TSD). The traffic flow is adaptively decomposed into periodic component, residual component and volatile component which are modeled respectively. Empirical Mode Decomposition (EMD) is applied to extract the intrinsic mode functions (IMFs) of traffic flow, the periodic patterns are intuitively presented via Hilbert transform in terms of frequencies. Then the periodic component can be described as a Fourier series based on obtained frequencies. Meanwhile, the residual component is presented by IMF with the lowest frequency. The remaining part is the volatile component modeled by supervised learning. The proposed hybrid model is evaluated on the real-world dataset and compared with classical baseline models. The results demonstrate that TSD can unearth the underlying periodic patterns and provide an explicable composition of the traffic flow. Furthermore, the volatile component ensures the accuracy of single-step prediction while periodic and residual components show promising abilities in improving the multi-step prediction accuracy of short-term traffic flow. (C) 2021 The Author(s). Published by Elsevier B.V.
原文链接:- NSTL
- Elsevier
Pavlova, O. N.Guyo, G. A.Pavlov, A. N.
9页查看更多>>摘要：The possibility of distinguishing between different types of complex oscillations using datasets contaminated with measurement noise is studied based on multiresolution wavelet analysis (MWA). Unlike the conventional approach, which characterizes the differences in terms of standard deviations of detail wavelet coefficients at independent resolution levels, we consider ways to improve the separation between complex motions by applying several measures for the decomposition coefficients. We show that MWA's capabilities in diagnosing dynamics can be expanded by applying detrended fluctuation analysis (DFA) to sets of detail wavelet coefficients or by computing the excess of the probability density function of these sets. (C) 2021 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Briz-Redon, AlvaroIftimi, AdinaMontes, Francisco
14页查看更多>>摘要：Predicting the occurrence of traffic accidents is essential for establishing preventive measures and reducing the impact of traffic accidents. In particular, it is fundamental to make predictions using fine spatio-temporal units. In this paper, the daily risk of traffic accident occurrence across the road network of Valencia (Spain) is modeled through logistic regression models. The spatio-temporal dependence between the observations is accounted for through the inclusion of lagged binary covariates representing the previous occurrence of a traffic accident within a spatio-temporal window centered at each combination of day and segment of the network. A temporal distance of 28 days and a fifth-order spatial distance are set as the limits of such dependence. Furthermore, the models include fixed effects in terms of several socio-demographic, network-related, and weather-related covariates. Temporal (month and day of the week) and spatial (boroughlevel) effects are also considered. The predictive quality of the models is examined through the Matthews correlation coefficient and the prediction accuracy index. The results indicate that the incorporation of spatio-temporal dependence improves the predictive ability of the models. However, while the inclusion of temporally-lagged covariates representing short-and mid-term temporal dependence yields more accurate predictions, the higher-order spatial lags barely alter model performance. (C) 2021 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Xie, RongrongDeng, ShengfengDeng, WeibingPato, Mauricio P....
9页查看更多>>摘要：A generalized Poisson ensemble is constructed using the maximum entropy principle based on the non-extensive entropy. It is found that the correlations which are introduced among the eigenvalues lead to statistical distributions with heavy tails. As a consequence, long-range statistics, measured by the number variance, show super-Poissonian behavior and the short-range ones, measured by the nearest-neighbor-distribution show, with respect to Poisson, enhancement at small and large separations. Potential applications were found for the sequence data of protein and DNA, which display good agreement with the model. In particular, the ensuing parameter lambda of the generalized Poisson ensemble can be utilized to facilitate protein classification. (C) 2021 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Czart, Wojciech R.Kapcia, Konrad J.Micnas, RomanRobaszkiewicz, Stanislaw...
19页查看更多>>摘要：In the paper, we study the thermodynamic and electromagnetic properties of the Penson-Kolb (PK) model, i.e., the tight-binding model for fermionic particles with the pair-hopping interaction J. We focus on the case of repulsive J (i.e., J < 0), which can stabilize ale eta-pairing superconductivity with Cooper-pair center-of-mass momentum (q)over-right-arrow = (Q)over-right-arrow, (Q)over-right-arrow = (pi/a, pi/a, ...). Numerical calculations are performed for several d- dimensional hypercubic lattices: d = 2 (the square lattice, SQ), d = 3 (the simple cubic lattice) and d = infinity hypercubic lattice (for arbitrary particle concentration 0 < n < 2 and temperature T). The ground state J versus n phase diagrams and the crossover to the Bose-Einstein condensation regime are analyzed and the evolution of the superfluid characteristics are examined within the (broken symmetry) Hartree-Fock approximation (HFA). The critical fields, the coherence length, the London penetration depth, and the Ginzburg ratio are determined at T = 0 and T > 0 as a function of n and pairing strength. The analysis of the effects of the Fock term on the ground state phase boundaries and on selected PK model characteristics is performed as well as the influence of the phase fluctuations on the eta-pairing superconductivity is investigated. Within the Kosterlitz-Thouless scenario, the critical temperatures T-KT are estimated for d = 2 SQ lattice and compared with the critical temperature T-c obtained from HFA. We also determine the temperature T-m at which minimal gap between two quasiparticle bands vanishes in the eta-phase. Our results for repulsive J are contrasted with those found earlier for the PK model with attractive J (i.e., with J > 0). (C) 2021 The Author( s ). Published by Elsevier B.V.
原文链接:- NSTL
- Elsevier
Datta, AmitavaWinkelstein, PeterSen, Surajit
14页查看更多>>摘要：We introduce a novel agent based model where each agent carries an effective viral load that captures the instantaneous state of infection of the agent. We simulate the spread of a pandemic and subsequently validate it by using publicly available COVID-19 data. Our simulation tracks the temporal evolution of a virtual city or community of agents in terms of contracting infection, recovering asymptomatically, or getting hospitalized. The virtual community is divided into family groups with 2-6 individuals in each group. Agents interact with other agents in virtual public places like at grocery stores, on public transportation and in offices. We initially seed the virtual community with a very small number of infected individuals and then monitor the disease spread and hospitalization over a period of fifty days, which is a reasonable time-frame for the initial spread of a pandemic. An uninfected or asymptomatic agent is randomly selected from a random family group in each simulation step for visiting a random public space. Subsequently, an uninfected agent contracts infection if the public place is occupied by other infected agents. We have calibrated our simulation rounds according to the size of the population of the virtual community for simulating realistic exposure of agents to a contagion. Our simulation results are consistent with the publicly available hospitalization and ICU patient data from three distinct regions of varying sizes in New York state. Our model can predict the trend in epidemic spread and hospitalization from a set of simple parameters and could be potentially useful in predicting the disease evolution based on available data and observations about public behavior. Our simulations suggest that relaxing the social distancing measures may increase the hospitalization numbers by some 30% or more. (C) 2021 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Wang, JianweiWang, SiyuanWang, Ziwei
13页查看更多>>摘要：Different from the previous research framework of cascading failure driven by intentional attack or random failure, this paper considers the occurrence of cascading failure from a new perspective, i.e., the spontaneous phenomenon of cascading failure. When the network changes from the low peak period to the high peak period, the global distribution of load changes, which leads to the cascading failure of the network. This phenomenon is called the spontaneous phenomenon of cascading failure. We introduce the concept of reachable region and construct a new cascading failure model, which mainly focus on how the dynamic changes of reachable area drive the dynamic behavior of cascade failures. Through simulation on two infrastructure networks, we found that: (1) The size of reachable area is positively correlated with network robustness. The larger the reachable area is, the smaller the load fluctuation of the whole network is, and the cascading failures are more easily alleviated and the network robustness is higher. But when the edge load capacity increases, the robustness of the network is not necessarily improved, which indicates the existence of capacity paradox. (2) The size of reachable area is negatively correlated with network capacity redundancy. The larger the reachable area is, the lower the capacity redundancy of the whole network will be and the less network resources will be wasted. (3) Combining with the network topology and the phenomenon of "key edge" we find that the edge with less betweenness centrality usually needs to invest higher resource protection. (C) 2021 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Krbalek, MilanSeba, FrantisekKrbalkova, Michaela
14页查看更多>>摘要：This article deals with specific states of traffic flow on a two-lane freeway, in which statistical fluctuations of microscopic quantities (inter-vehicle gaps) are significantly higher than in systems with absolutely random events (Poisson systems). These anomalous states (super-random) are detected in empirical traffic data, specifically in the fast lane at traffic densities up to 25 vehicles per kilometer. The origin of these states is then explained mathematically (using the theory of balance particle systems and tools of random matrix theory), physically (by means of an one-dimensional particle gas subjected to local perturbations caused by overtaking cars) and empirically (using an analogy with phenomena observed in photon counting experiments). In the article we show that overtaking maneuvers, when vehicles from a slow lane are injected into a fast-lane stream of faster moving vehicles, disrupt a local balance in microstructure of fast-lane stream and cause atypical arrangement of vehicular positions, that is very rare, generally. With help of original numerical model we demonstrate that the anomalous states detected are identical to equilibrium states formed in a stochastic particle gas with a potential containing, in addition to a repulsive component, also an attractive component. (C) 2021 Published by Elsevier B.V.
原文链接:- NSTL
- Elsevier
