Tilfani, OussamaKristoufek, LadislavFerreira, PauloBoukfaoui, My Youssef El...
16页查看更多>>摘要：Heterogeneity of effects between economic variables has been a frequently discussed topic for many years now. However, the estimation of such scale-dependent effects has proved challenging. Here, we propose a multivariate multiscale regression approach based on the combination of detrended fluctuation analysis and detrended cross-correlation analysis, but the idea can be easily translated into other time and frequency domain frameworks. As illustrations, we pick two classic economic models - the Taylor's rule and the money demand function for the USA and Japan - and we uncover evident scale-dependence in the individual effects not visible by the simple regression tools. Importantly, the proposed framework can be used in any discipline where studying the effects at various scales is of interest. Further applications are thus certainly at hand. (C) 2021 Published by Elsevier B.V.
原文链接:
NSTL
Elsevier
Alcala, Samuel MartinezZanette, Damian H.
10页查看更多>>摘要：We study the structural properties of a class of model social networks representing blood sibling and sibling-in-law relationships, in the case where the size of the married population varies between successive generations. These kinship networks are characterized by Poissonian degree distributions and the presence of a connected component encompassing a large part of the population, along with high values of clustering and assortativity. By means of numerical simulations and comparison with Erdos-Renyi networks of the same size and connectivity, we show that global clustering and assortativity remain high unless the size of the married population drops drastically. In contrast, the largest connected component collapses when the married population shrinks to just about two thirds of its size in the previous generation. (C) 2021 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Li, Jiang-ChengTao, ChenLi, Hai-Feng
16页查看更多>>摘要：In a complex financial system, what is the forecasting performance of macro and micro evolution models of Econophysics on asset prices? For this problem, from the perspective of machine learning, we study the dynamic forecasting and liquidity assessment of financial markets, based on econophysics and Bayesian methods. We establish eight dynamic prediction methods, based on our proposed likelihood estimation and Bayesian estimation methods of macro and micro evolution models of econophysics. Combined machine learning thinking and real data, we empirically study and simulate the out-of-sample dynamic forecasting analysis of eight proposed methods and compare with the benchmark GARCH model. A variety of loss functions, superior predictive ability test (SPA), Akaike and Bayesian information criterion (AIC and BIC) methods are introduced to further evaluate the forecasting performance of our proposed methods. The research of out of sample prediction shows that (1) the method of the simplified stochastic model with Bayesian method for only sample return has the best forecasting performance; (2) the method of the stochastic model with Bayesian method for only return samples has the worst forecasting performance. For the liquidity assessment problem, there is a strong correlation between the trading probability evaluated by the proposed eight methods and the real turnover rate, and an increase of liquidity is correspond to the increase of asset risk. In other words, it suggests that all proposed methods can well evaluate market liquidity. (C) 2021 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Fu, XinXu, ChengyaoLiu, YutengChen, Chi-Hua...
17页查看更多>>摘要：It is of great reference significance to exploring spatial dependence of urban traffic activities and researching internal causes of regional traffic state changes for road network optimization and residents' travel behavior analysis. Based on trajectory data of taxis in Ningbo city of China, this study calculates average driving speed of taxis in different blocks during characteristic period and generates the global Moran's I and the LISA clustering diagram. On this basis, the spatial clustering characteristics of congestion on working days and non-working days are analyzed. Furthermore, in order to further characterize the changes of congestion from the perspective of spatial migration, a method of measuring geometric displacement is adopted to describe spatio-temporal migration trend of traffic states, four indicators designed to identify urban frequently congested areas, including migration direction, angle, distance, and low-value area. The results show that the high-clustering area are located urban fringe and the low-clustering area are located at geometric center of major urban areas. Spatial-temporal migration law of low-value areas in city-center is obvious. Difference between trend is compared with non-working days, the offset and azimuth of low-value area in downtown on working days are even bigger. The accurate capture of the characteristics of congestion space migration at the urban scale will help to formulate more targeted congestion management strategies. (C) 2021 Published by Elsevier B.V.
原文链接:- NSTL
- Elsevier
Paraguassu, Pedro, VMorgado, Welles A. M.
9页查看更多>>摘要：Thermodynamic quantities, like heat, entropy, or work, are random variables, in stochastic systems. Here, we investigate the statistics of the heat exchanged by a Brownian particle subjected to a logarithm-harmonic potential. We derive analytically the characteristic function and its moments for the heat. Through numerical integration, and numerical simulation, we calculate the probability distribution as well, characterizing fully the statistical behavior of the heat. The results are also investigated in the asymptotic limit, where we encounter the characteristic function in terms of hypergeometric functions. (C) 2021 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Shang, Xue-ChengLi, Xin-GangXie, Dong-FanJia, Bin...
14页查看更多>>摘要：In this paper, a data-driven two-lane traffic flow model based on cellular automata is proposed. Long Short-Term Memory (LSTM) and Support Vector Machine (SVM) are used to learn the characteristics of car following behavior and lane changing behavior, respectively, from real operation data of vehicles. Under optimal network parameters, the mean absolute errors of the LSTM network for training and testing data are only 0.001 and 0.006, respectively; while the prediction accuracy of the SVM classifier for both data reaches higher than 0.99. Moreover, forward rules and lane changing rules which are more consistent with actual situation are designed. The simulation results show that: (1) the new model can reflect the first-order phase transition from free flow to synchronized flow; (2) the frequency of unsuccessful lane changing is near zero in low-density traffic areas, but increases sharply in high-density regions; and (3) the lane changing duration and unsuccessful lane changing frequency display similar trends as traffic densities increase. (C) 2021 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Zubillaga, Bernardo J.Vilela, Andre L. M.Wang, ChaoNelson, Kenric P....
13页查看更多>>摘要：We propose a three-state microscopic opinion formation model for the purpose of simulating the dynamics of financial markets. In order to mimic the heterogeneous composition of the mass of investors in a market, the agent-based model considers two different types of traders: noise traders and noise contrarians. Agents are represented as nodes in a network of interactions and they can assume any of three distinct possible states. The time evolution of the state of an agent is dictated by probabilistic dynamics that include both local and global influences. A noise trader is subject to local interactions, tending to assume the majority state of its nearest neighbors, whilst a noise contrarian is subject to a global interaction with the behavior of the market as a whole, tending to assume the state of the global minority of the market. The model exhibits the typical qualitative and quantitative features of real financial time series, including distributions of returns with heavy tails, volatility clustering and long-time memory for the absolute values of the returns. The distributions of returns are fitted by means of coupled Gaussian distributions, quantitatively revealing transitions between leptokurtic, mesokurtic and platykurtic regimes in terms of a non-linear statistical coupling which describes the complexity of the system. (C) 2021 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Pacheco-Martinez, H. A.Peraza-Mues, G.Penunuri, F.Carvente, O....
8页查看更多>>摘要：Kinetic energy is transferred through collisions to the millimeter particles that are in contact with the base of a vertically vibrated 3D container. In the early stages of a vibrational annealing process where the dimensionless acceleration is kept constant, the spontaneous appearance and disappearance of unstable clusters of ordered particles near the bottom surface of the container is observed. In later stages of this vibra-tional annealing process, the precursor nuclei stabilize becoming stable crystal seeds which resembles a thermal phase transition. Molecular Dynamics simulations based on these experimental observations are used to study the unstable-stable transition. The Ornstein-Zernike equation using the Percus-Yevick closure is applied to the stages be-fore and after the observation of the stable crystal seeds in order to extract the effective potentials associated with the phase transition. Both the radial distribution function and the effective potentials show a clear correspondence of the spatial correlation as the crystallization phase begins to appear. (C) 2021 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Wang, ChaoMeng, XinGuo, MingxueLi, Hao...
15页查看更多>>摘要：Subway is considered to be one of the most energy-intensive transportation modes for its high operating frequency. However, energy-efficient operations for the subway system are of great importance yet have not been paid much attention to. In this study, we first develop an integrated energy-efficient and transfer-accessible model to minimize the tractive energy consumption and maximize the number of last train connections, which could contribute to the development of high energy-efficient strategies and the construction of wide-accessibility timetables for the subway system. Four tractive modes, which are accelerating-braking (A-B) mode, accelerating-coasting-braking (A-Co-B) mode, accelerating-cruising-braking (A-Cr-B) mode, and the mixed mode, are proposed to facilitate the last train operations. A real-life case study of the Beijing subway network is solved by a tailored genetic algorithm. Results show that the A-B mode is the most energy-intensive with an energy consumption of 466.9 kWh, while the A-Co-B mode becomes the most energy-efficient (402.5 kWh). The A-Cr-B and the mixed modes consume 442.2 kWh and 412.8 kWh, respectively. The findings are of significant value for subway companies in addition to their academic merits. (C) 2021 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Kuikka, VesaMonsivais, DanielKaski, Kimmo K.
9页查看更多>>摘要：In an earlier study one of us had developed a model of influence spreading for analysing human behaviour and interaction with others in a social network. Here we apply this model and corresponding influence centrality measures to real data of mobile phone call detail records. From this we get structures of human ego-centric networks and use a simple model, based on the number of phone calls, to describe the strengths of social relationships. To analyse 48,000 egos in their ego-centric networks we define normalised out-centrality and in-centrality influence measures, by dividing with out-degree and in-degree, respectively. With these and the betweenness centrality measures, we analyse the influence spreading in the ego-centric networks under different scenarios of link strengths between individuals reflecting the network structure being either interaction or connectivity oriented. The model reveals characteristics of social behaviour that are not obvious from the data analysis of raw empirical data or from the results of standard centrality measures. A transition is discovered in behaviour from young to older age groups for both genders and in both normalised out-centrality and in-centrality as well as betweenness centrality results. (C) 2021 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
