de Lacerda, K. J. C. C.da Silva, L. R.Viswanathan, G. M.Cressoni, J. C....
6页查看更多>>摘要：The theory of Markovian random walks is consolidated and very well understood, however the theory of non-Markovian random walks presents many challenges due to its remarkably rich phenomenology. An important open problem in this context is to study how the diffusive properties of random walk processes change when memoryinduced correlations are introduced. In this work we propose a model of a random walk that evolves in time according to past memories selected from rectangular (flat) and exponentially decaying memory profiles. In this mixed memory profile model, the walker remembers either the last B steps with equal a priori probability or the steps A prior to B with exponentially decaying probability, for a total number of steps equal to A + B. The diffusive behavior of the walk is numerically examined through the Hurst exponent (H). Even in the lack of exact solutions, we are still able to show that the model can be mapped onto a RW model with rectangular memory profile. (c) 2022 Elsevier B.V. All rights reserved.
原文链接:
NSTL
Elsevier
Kotak, Jesal D.Barma, Mustansir
15页查看更多>>摘要：We study the competition between field-induced transport and trapping in a disordered medium by studying biased random walks on random combs and the bond-diluted Bethe lattice above the percolation threshold. While it is known that the drift velocity vanishes above a critical threshold, here our focus is on fluctuations, characterized by the variance of the transit times. On the random comb, the variance is calculated exactly for a given realization of disorder using a 'forward transport' limit which prohibits backward movement along the backbone but allows an arbitrary number of excursions into random-length branches. The disorder-averaged variance diverges at an earlier threshold of the bias, implying a regime of anomalous fluctuations, although the velocity is nonzero. Our results are verified numerically using a Monte Carlo procedure that is adapted to account for ultra-slow returns from long branches. On the Bethe lattice, we derive an upper bound for the critical threshold bias for anomalous fluctuations of the mean transit time averaged over disorder realizations. Finally, as for the passage to the vanishing velocity regime, it is shown that the transition to the anomalous fluctuation regime can change from continuous to first order depending on the distribution of branch lengths. (C) 2022 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Nezhadhaghighi, M. Ghasemi
9页查看更多>>摘要：In two-dimensional statistical mechanics, the Stochastic Loewner equation, introduced by Oded Schramm, provides a powerful technique to study and categorize critical random curves and interfaces. For the first time, a new type of stochastic Loewner equation entitled fractional stochastic Loewner evolution (FSLE) has been proposed. We introduce a wide class of fractal curves using the fractional time series as the driving function of the Loewner equation and local fractional integrodifferential operators. We suggest that, in addition to fractal dimension estimations, the Hurst index of the driving function leads significant differences in the FSLE curves. This modification introduces a new approach to categorize different types of scaling curves based on the Hurst index of the driving function. Such formalizations appear to be appropriate for studying a wide range of two-dimensional curves seen in statistical mechanics and natural phenomena. (C) 2022 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Lai, XinBai, ShuliangLin, Yong
13页查看更多>>摘要：Complex network is a mainstream form of unstructured data in real world. Detecting communities in complex networks bears a wide range of applications. Different from the existing methods, which concentrate on applying statistics, graph theory or combinations, this work presents a new algorithm along a geometric avenue. By utilizing normalized discrete Ricci flow with modified sigma-weight-sum, and employing a limit-free Ricci curvature using *-coupling, this algorithm prevents the graph from collapsing to a point, and eliminates a hyper parameter alpha in discrete Ollivier Ricci curvature. Besides, experiments on real-world networks and artificial networks have shown that this normalized algorithm has a matching or better result, and is more robust with regard to unnormalized one (Ni et al., 2019). The code is available at https://github.com/laiguzi/NormalizedRicciFlow. (C) 2022 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Sun, ZejunSun, YananChang, XinfengWang, Feifei...
20页查看更多>>摘要：The identification of community structures plays a crucial role in analyzing network topology, exploring network functions, and mining potential patterns in complex networks. Many algorithms have been proposed for identifying community structures in static networks from different perspectives. However, most networks in the real world are not static and their structures constantly evolve over time. Identifying community structures in dynamic networks remains a challenging task because of the variability, complexity, and large scale of dynamic networks. In this study, we propose a framework and Matthew effect model for community detection in dynamic networks. Based on this architecture and model, we design a dynamic community detection algorithm called, Dynamic Community Detection based on the Matthew effect (DCDME), which employs a batch processing method to reveal communities incrementally in each network snapshot. DCDME has several desirable benefits: high-quality community detection, parameter-free operation, and good scalability. Extensive experiments on synthetic and real-world dynamic networks have demonstrated that DCDME has many advantages and outperforms several state-of-the-art algorithms.
原文链接:- NSTL
- Elsevier
Pi, BinLi, YuhanFeng, Minyu
12页查看更多>>摘要：Network evolutionary game theory provides a new perspective on how cooperative behaviors emerge in the real world and has been widely investigated. However, most studies assume that players are profiteers and ignore the existence of conformists and that players have memories, which are crucial when people make decisions. In this study, we study a memory-based snowdrift game occurring on networks and propose two strategy-updating rules based on profiteers and conformists while considering the historical strategy, memory strength, payoff information and memory length to discuss the emergence and maintenance of cooperation behaviors. In contrast to previous studies, we introduce the player's degree of cooperation to continuousize player payoffs and we consider it when defining the player's strategy-updating rules. In simulations, we show the evolution of the frequency of cooperation as time progresses and investigate the effects of the payoff parameter, memory strength, memory length and conformist ratio on the frequency of cooperation, and further validate the robustness of our model using different network sizes. Our results show that the memory strength, memory length, and conformist ratio can facilitate the cooperation level of the network over a large parameter area, and that the size of the network has almost no effect on the model, which shows the robustness of our model. Our work may elucidate the study of evolutionary games with conformists and memory effects. (c) 2022 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Yang, YunMa, ChangxiLing, Gang
14页查看更多>>摘要：In order to avoid the huge hidden dangers caused by emergencies, it is particularly vital to make a reasonable pre-location and layout of emergency logistics facilities. A multi objective pre-location model of temporary distribution station for emergency materials was built, which considered the problems of information shortage and uncertain demand after the incident with minimum time, maximum time satisfaction, minimum delivery cost and psychological trauma to the masses. The priority of candidate points was solved by comprehensive evaluation methods, the nominal demand of served points was estimated by triangular fuzzy number theory (TFN), and the location model was solved by non-dominated sorting genetic algorithm. In addition, the optimal schemes without priority and considering it were compared and analyzed, the practicability of the model is verified by concrete examples. The results show the time and cost reduction of 7.754% and 25.651%, an increment of total satisfaction value of the scheme considering location priority. Therefore, the model and algorithm provide theoretical support and practical ideas for solving the location problem, which can better complete the task of the location problem for temporary distribution stations of urban emergency materials. (C) 2022 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Kim, Jeong-YooLee, Kyu-MinPark, Sung-Hoon
15页查看更多>>摘要：This paper develops an evolutionary approach to investigate whether revealing one's own emotions such as selfishness, altruism or envy has evolved in humans through a process of natural selection. This paper finds two results. First, if the revealing trait (revealing or hiding) and the other-regarding trait (selfish or altruistic/envious) are independent so the four types evolve in a correlated way, both of revealing types and hiding types can survive in the long run. For most parameter values, however, revealing altruism fares better than hiding altruism if individuals' interactions are strategic complements, whereas hiding envy fares better than revealing envy if individuals' interactions are strategic substitutes. Second, for most parameter values, only the revealing types survive if the revealing trait and the other-regarding trait are linked so that the four types evolve independently. (C) 2022 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Toman, KellanVoulgarakis, Nikolaos K.
13页查看更多>>摘要：Many predator species attempt to locate prey by following seemingly random paths. Although the underlying physical mechanism of the search remains largely unknown, such search paths are usually modeled by some type of random walk. Here, we introduce the stochastic pursuit-evasion equations that consider the bidirectional interaction between predators and prey. This assumption results in a modulated persistent random walk that is characterized by three interesting properties: power-law or tempered power-law distributed running times, superdiffusive or transient superdiffusive dynamics, and strong directional persistence. Furthermore, the proposed model exhibits a transition from Brownian to Levy-like motion with intensifying predator-prey interaction. Interestingly, persistent random walks with pure-power law distributed running times emerge at the limit of highest predator-prey interaction. We hypothesize that the system ultimately self-organizes into a critical interaction to avoid extinction. (c) 2022 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
