arXiv subjects

Bing-Hong Wang

Publications and source records attributed to Bing-Hong Wang.

At least 73 records · Page 4Linked to original sources

arXiv2010

Universal role of migration in the evolution of cooperation

We study the role of unbiased migration in cooperation in the framework of spatial evolutionary game on a variety of spatial structures, involving regular lattice, continuous plane and complex networks. A striking finding is that migration plays a universal role in cooperation, regardless of the spatial structures. For high degree of migration, cooperators cannot survive due to the failure of forming cooperator clusters to resist attacks of defectors. While for low degree of migration, cooperation is considerably enhanced compared to statically spatial game, which is due to the strengthening of the boundary of cooperator clusters by the occasionally accumulation of cooperators along the boundary. The cooperator cluster thus becomes more robust than that in static game and defectors nearby the boundary can be assimilated by cooperators, so the cooperator cluster expands, which facilitates cooperation. The general role of migration will be substantiated by sufficient simulations associated with heuristic explanations.

physics.soc-ph↗

arXiv2010

Exp-function method for solving the Burgers-Fisher equation with variable coefficients

In this paper, the exp-function method with the aid of symbolic computational system is used to obtain generalized travelling wave solutions of a Burgers-Fisher equation with variable coefficients. It is shown that the exp-function method, with the help of symbolic computation, provides a straightforward and powerful mathematical tool to solve the nonlinear evolution equation with variable coefficients in mathematical physics.

nlin.SI↗

arXiv2009

Scaling property and opinion model for interevent time of terrorism attack

The interevent time of terrorism attack events is investigated by empirical data and model analysis. Empirical evidence shows it follows a scale-free property. In order to understand the dynamic mechanism of such statistic feature, an opinion dynamic model with memory effect is proposed on a two-dimension lattice network. The model mainly highlights the role of individual social conformity and self-affirmation psychology. An attack event occurs when the order parameter of the system reaches a critical value. Ultimately, the model reproduces the same statistical property as the empirical data and gives a good understanding of terrorism attack.

physics.soc-ph↗

arXiv2009

Highly accurate recommendation algorithm based on high-order similarities

In this Letter, we introduce a modified collaborative filtering (MCF) algorithm, which has remarkably higher accuracy than the standard collaborative filtering. In the MCF, instead of the standard Pearson coefficient, the user-user similarities are obtained by a diffusion process. Furthermore, by considering the second order similarities, we design an effective algorithm that depresses the influence of mainstream preferences. The corresponding algorithmic accuracy, measured by the ranking score, is further improved by 24.9% in the optimal case. In addition, two significant criteria of algorithmic performance, diversity and popularity, are also taken into account. Numerical results show that the algorithm based on second order similarity can outperform the MCF simultaneously in all three criteria.

physics.data-an↗

arXiv2009

Improved Collaborative Filtering Algorithm via Information Transformation

In this paper, we propose a spreading activation approach for collaborative filtering (SA-CF). By using the opinion spreading process, the similarity between any users can be obtained. The algorithm has remarkably higher accuracy than the standard collaborative filtering (CF) using Pearson correlation. Furthermore, we introduce a free parameter $β$ to regulate the contributions of objects to user-user correlations. The numerical results indicate that decreasing the influence of popular objects can further improve the algorithmic accuracy and personality. We argue that a better algorithm should simultaneously require less computation and generate higher accuracy. Accordingly, we further propose an algorithm involving only the top-$N$ similar neighbors for each target user, which has both less computational complexity and higher algorithmic accuracy.

cs.LG↗

arXiv2009

Effect of user tastes on personalized recommendation

In this paper, based on a weighted projection of the user-object bipartite network, we study the effects of user tastes on the mass-diffusion-based personalized recommendation algorithm, where a user's tastes or interests are defined by the average degree of the objects he has collected. We argue that the initial recommendation power located on the objects should be determined by both of their degree and the users' tastes. By introducing a tunable parameter, the user taste effects on the configuration of initial recommendation power distribution are investigated. The numerical results indicate that the presented algorithm could improve the accuracy, measured by the average ranking score, more importantly, we find that when the data is sparse, the algorithm should give more recommendation power to the objects whose degrees are close to the users' tastes, while when the data becomes dense, it should assign more power on the objects whose degrees are significantly different from user's tastes.

physics.data-an↗

arXiv2009

Optimal transport on supply-demand networks

Previously, transport networks are usually treated as homogeneous networks, that is, every node has the same function, simultaneously providing and requiring resources. However, some real networks, such as power grid and supply chain networks, show a far different scenario in which the nodes are classified into two categories: the supply nodes provide some kinds of services, while the demand nodes require them. In this paper, we propose a general transport model for those supply-demand networks, associated with a criterion to quantify their transport capacities. In a supply-demand network with heterogenous degree distribution, its transport capacity strongly depends on the locations of supply nodes. We therefore design a simulated annealing algorithm to find the optimal configuration of supply nodes, which remarkably enhances the transport capacity, and outperforms the degree target algorithm, the betweenness target algorithm, and the greedy method. This work provides a start point for systematically analyzing and optimizing transport dynamics on supply-demand networks.

physics.data-an↗

arXiv2009

Emergence of target waves in paced populations of cyclically competing species

We investigate the emergence of target waves in a cyclic predator-prey model incorporating a periodic current of the three competing species in a small area situated at the center of the square lattice. The periodic current acts as a pacemaker, trying to impose its rhythm on the overall spatiotemporal evolution of the three species. We show that the pacemaker is able to nucleate target waves that eventually spread across the whole population, whereby three routes leading to this phenomenon can be distinguished depending on the mobility of the three species and the oscillation period of the localized current. First, target waves can emerge due to the synchronization between the periodic current and oscillations of the density of the three species on the spatial grid. The second route is similar to the first, the difference being that the synchronization sets in only intermittently. Finally, the third route towards target waves is realized when the frequency of the pacemaker is much higher than that characterizing the oscillations of the overall density of the three species. By considering mobility and the frequency of the current as variable parameters, we thus provide insights into the mechanisms of pattern formation resulting from the interplay between local and global dynamics in systems governed by cyclically competing species.

q-bio.PE↗

arXiv2009

Degree correlation effect of bipartite network on personalized recommendation

In this paper, by introducing a new user similarity index base on the diffusion process, we propose a modified collaborative filtering (MCF) algorithm, which has remarkably higher accuracy than the standard collaborative filtering. In the proposed algorithm, the degree correlation between users and objects is taken into account and embedded into the similarity index by a tunable parameter. The numerical simulation on a benchmark data set shows that the algorithmic accuracy of the MCF, measured by the average ranking score, is further improved by 18.19% in the optimal case. In addition, two significant criteria of algorithmic performance, diversity and popularity, are also taken into account. Numerical results show that the presented algorithm can provide more diverse and less popular recommendations, for example, when the recommendation list contains 10 objects, the diversity, measured by the hamming distance, is improved by 21.90%.

physics.data-an↗

arXiv2009

Ultra accurate personalized recommendation via eliminating redundant correlations

In this paper, based on a weighted projection of bipartite user-object network, we introduce a personalized recommendation algorithm, called the \emph{network-based inference} (NBI), which has higher accuracy than the classical algorithm, namely \emph{collaborative filtering}. In the NBI, the correlation resulting from a specific attribute may be repeatedly counted in the cumulative recommendations from different objects. By considering the higher order correlations, we design an improved algorithm that can, to some extent, eliminate the redundant correlations. We test our algorithm on two benchmark data sets, \emph{MovieLens} and \emph{Netflix}. Compared with the NBI, the algorithmic accuracy, measured by the ranking score, can be further improved by 23% for \emph{MovieLens} and 22% for \emph{Netflix}, respectively. The present algorithm can even outperform the \emph{Latent Dirichlet Allocation} algorithm, which requires much longer computational time. Furthermore, most of the previous studies considered the algorithmic accuracy only, in this paper, we argue that the diversity and popularity, as two significant criteria of algorithmic performance, should also be taken into account. With more or less the same accuracy, an algorithm giving higher diversity and lower popularity is more favorable. Numerical results show that the present algorithm can outperform the standard one simultaneously in all five adopted metrics: lower ranking score and higher precision for accuracy, larger Hamming distance and lower intra-similarity for diversity, as well as smaller average degree for popularity.

physics.soc-ph↗

arXiv2009

Reducing the Heterogeneity of Payoffs: an Effective Way to Promote Cooperation in Prisoner's Dilemma Game

In this paper, the total payoff of each agent is regulated to reduce the heterogeneity of the distribution of the total payoffs. It is found there is an optimal regulation strength where the fraction of cooperation is prominently promoted, too weak or too strong of the strength will have little effects or result in the disappearance of the cooperators. It is also found that most of the cooperators are not distributed in isolation but form the cooperator clusters, and to promote the cooperation the only way is to enlarge the size of the cooperator clusters. Finally, we try to explain the emergence of larger clusters and prove the existence of the optimal regulation strength. Our works provide insight into the understanding of the relations between the distribution of payoffs and the cooperative behaviors.

physics.soc-ph↗

arXiv2009

Optimal View Angle in Collective Dynamics of Self-propelled Agents

We study a system of self-propelled agents in which each agent has a part of omnidirectional or panoramic view of its sensor disc, the field of vision of the agent in this case is only a sector of a disc bounded by two radii and the included arc. The inclination of these two radii is characterized as the view angle. Contrary to our intuition, we find that, the non-omnidirectional-view for swarm agents with periodic boundary conditions in noiseless Vicsek model can accelerate the transient process of the emergence of the ordered state. One consequent implication is that, there are generally superfluous communications in the Vicsek Model, which may even obstruct the possible fast swarm emergence. This phenomenon may invoke further efforts and attentions to explore the underlying mechanism of the emergence in self-propelled agents.

nlin.AO↗

arXiv2009

Information filtering based on transferring similarity

In this Brief Report, we propose a new index of user similarity, namely the transferring similarity, which involves all high-order similarities between users. Accordingly, we design a modified collaborative filtering algorithm, which provides remarkably higher accurate predictions than the standard collaborative filtering. More interestingly, we find that the algorithmic performance will approach its optimal value when the parameter, contained in the definition of transferring similarity, gets close to its critical value, before which the series expansion of transferring similarity is convergent and after which it is divergent. Our study is complementary to the one reported in [E. A. Leicht, P. Holme, and M. E. J. Newman, Phys. Rev. E {\bf 73} 026120 (2006)], and is relevant to the missing link prediction problem.

physics.data-an↗

arXiv2009

Consensus of self-driven agents with avoidance of collisions

In recent years, many efforts have been addressed on collision avoidance of collectively moving agents. In this paper, we propose a modified version of the Vicsek model with adaptive speed, which can guarantee the absence of collisions. However, this strategy leads to an aggregated state with slowly moving agents. We therefore further introduce a certain repulsion, which results in both faster consensus and longer safe distance among agents, and thus provides a powerful mechanism for collective motions in biological and technological multi-agent systems.

physics.data-an↗

arXiv2008

Accelerating consensus of self-driven swarm via adaptive speed

In resent years, Vicsek model has attracted more and more attention and been well developed. However, the in-depth analysis on the convergence time are scarce thus far. In this paper, we study some certain factors that mainly govern the convergence time of Vicsek model. By extensively numerical simulations, we find the convergence time scales in a power law with $r^2\ln N$ in the noise-free case, where $r$ and $N$ are horizon radius and the number of particles. Furthermore, to accelerate the convergence, we propose a new model in which the speed of each particle is variable. The convergence time can be remarkably shortened compared with the standard Vicsek model.

cond-mat.dis-nn↗

arXiv2008

How target waves emerge in population dynamics

Based on a multi-agent model, we investigate how target waves emerge from a population dynamics with cyclical interactions among three species. We show that the periodically injecting source in a small central area can generate target waves in a two-dimensional lattice system. By detecting the temporal period of species' concentration at the central area, three modes of target waves can be distinguished. Those different modes result from the competition between local and global oscillations induced by cyclical interactions: Mode A corresponds to a synchronization of local and global oscillations, Mode B results from an intermittent synchronization, and Mode C corresponds to the case when the frequency of the local oscillation is much higher than that of the global oscillation. This work provides insights into pattern formation in biologic and ecologic systems that are totally different from the extensively studied diffusion systems driven by chemical reactions.

physics.bio-ph↗

arXiv2008

Scaling of critical connectivity of mobile ad hoc communication networks

In this paper, critical global connectivity of mobile ad hoc communication networks (MAHCN) is investigated. We model the two-dimensional plane on which nodes move randomly with a triangular lattice. Demanding the best communication of the network, we account the global connectivity $η$ as a function of occupancy $σ$ of sites in the lattice by mobile nodes. Critical phenomena of the connectivity for different transmission ranges $r$ are revealed by numerical simulations, and these results fit well to the analysis based on the assumption of homogeneous mixing . Scaling behavior of the connectivity is found as $η\sim f(R^βσ)$, where $R=(r-r_{0})/r_{0}$, $r_{0}$ is the length unit of the triangular lattice and $β$ is the scaling index in the universal function $f(x)$. The model serves as a sort of site percolation on dynamic complex networks relative to geometric distance. Moreover, near each critical $σ_c(r)$ corresponding to certain transmission range $r$, there exists a cut-off degree $k_c$ below which the clustering coefficient of such self-organized networks keeps a constant while the averaged nearest neighbor degree exhibits a unique linear variation with the degree k, which may be useful to the designation of real MAHCN.

cs.NI↗

arXiv2008

Modeling Human Dynamics with Adaptive Interest

Recently, increasing empirical evidence indicates the extensive existence of heavy tails in the interevent time distributions of various human behaviors. Based on the queuing theory, the Barabási model and its variations suggest the highest-priority-first protocol a potential origin of those heavy tails. However, some human activity patterns, also displaying the heavy-tailed temporal statistics, could not be explained by a task-based mechanism. In this paper, different from the mainstream, we propose an interest-based model. Both the simulation and analysis indicate a power-law interevent time distribution with exponent -1, which is in accordance with some empirical observations in human-initiated systems.

physics.soc-ph↗