Chaos Solitons & Fractals (CHAOS SOLITON FRACT)

Publisher: Elsevier

Journal description

Chaos, Solitons & Fractals provides a medium for the rapid publication of full length original papers, short communications, reviews and tutorial articles in the following subjects:-bifurcation and singularity theory, deterministic chaos and fractals, stability theory, soliton and coherent phenomena, formation of pattern, evolution, complexity theory and neural networksContributions on both fundamental and applied studies are welcome, but the emphasis of the journal will be on applications in the following fields: Physical Sciences classical mechanics, including fluid mechanics; quantum and statistical mechanics; lasers, optics and acoustics; plasma physics and fusion; solid-state and condensed matter physics; chemistry and chemical physics; astronomy and astrophysics; materials science; geophysics; meteorology. Engineering marine engineering; mechanical, aeronautical and astronautical engineering; electrical engineering; chemical engineering; structural and civil engineering. Biomedical and Life Sciences biology; molecular biology; population dynamics; zoology; theoretical ecology. Social Sciences economics; sociology; political science; philosophy and epistemology. All essential colour illustrations and photographs will be reproduced in colour at no charge to the author.

Current impact factor: 1.45

Impact Factor Rankings

2015 Impact Factor Available summer 2016
2014 Impact Factor 1.448
2013 Impact Factor 1.503
2012 Impact Factor 1.246
2011 Impact Factor 1.222
2010 Impact Factor 1.267
2009 Impact Factor 3.315
2008 Impact Factor 2.98
2007 Impact Factor 3.025
2006 Impact Factor 2.042
2005 Impact Factor 1.938
2004 Impact Factor 1.526
2003 Impact Factor 1.064
2002 Impact Factor 0.872
2001 Impact Factor 0.839
2000 Impact Factor 0.742
1999 Impact Factor 0.788
1998 Impact Factor 0.807
1997 Impact Factor 0.698

Impact factor over time

Impact factor

Additional details

5-year impact 1.25
Cited half-life 7.90
Immediacy index 0.35
Eigenfactor 0.01
Article influence 0.35
Website Chaos, Solitons & Fractals website
Other titles Chaos, solitons, and fractals (Online), Chaos, solitons & fractals
ISSN 0960-0779
OCLC 38522998
Material type Document, Periodical, Internet resource
Document type Internet Resource, Computer File, Journal / Magazine / Newspaper

Publisher details


  • Pre-print
    • Author can archive a pre-print version
  • Post-print
    • Author can archive a post-print version
  • Conditions
    • Authors pre-print on any website, including arXiv and RePEC
    • Author's post-print on author's personal website immediately
    • Author's post-print on open access repository after an embargo period of between 12 months and 48 months
    • Permitted deposit due to Funding Body, Institutional and Governmental policy or mandate, may be required to comply with embargo periods of 12 months to 48 months
    • Author's post-print may be used to update arXiv and RepEC
    • Publisher's version/PDF cannot be used
    • Must link to publisher version with DOI
    • Author's post-print must be released with a Creative Commons Attribution Non-Commercial No Derivatives License
    • Publisher last reviewed on 03/06/2015
  • Classification
    ​ green

Publications in this journal

  • [Show abstract] [Hide abstract]
    Chaos Solitons & Fractals 12/2015; 81:146–149. DOI:10.1016/j.chaos.2015.09.015
  • Zengshan Li · Diyi Chen · Jianwei Zhu · Yongjian Liu
    Chaos Solitons & Fractals 12/2015; 81:111-116. DOI:10.1016/j.chaos.2015.09.012
  • Chaos Solitons & Fractals 12/2015; 81:98-102. DOI:10.1016/j.chaos.2015.08.028
  • Chaos Solitons & Fractals 12/2015; 81:103-110. DOI:10.1016/j.chaos.2015.09.004
  • Ling Tang · Huiling Lv · Fengmei Yang · Lean Yu
    Chaos Solitons & Fractals 12/2015; 81:117-135. DOI:10.1016/j.chaos.2015.09.002
  • Chaos Solitons & Fractals 12/2015; 81:150-161. DOI:10.1016/j.chaos.2015.09.008
  • [Show abstract] [Hide abstract]
    ABSTRACT: In previous epidemiological studies that address adaptive vaccination decisions, individuals generally act within a single network, which models the population structure. However, in reality, people are typically members of multiplex networks, which have various community structures. For example, a disease transmission network, which directly transmits infectious diseases, does not necessarily correspond with an information propagation network, in which individuals directly or indirectly exchange information concerning health conditions and vaccination strategies. The latter network may also be used for strategic interaction (strategy adaptation) concerning vaccination. Therefore, in order to reflect this feature, we consider the vaccination dynamics of structured populations whose members simultaneously belong to two types of networks: disease transmission and information propagation. Applying intensive numerical calculations, we determine that if the disease transmission network is modeled using a regular graph, such as a lattice population or random regular graph containing individuals of equivalent degrees, individuals should base their vaccination decisions on a different type of network. However, if the disease transmission network is a degree-heterogeneous graph, such as the Barabási–Albert scale-free network, which has a heterogeneous degree according to power low, then using the same network for information propagation more effectively prevents the spread of epidemics. Furthermore, our conclusions are unaffected by the relative cost of vaccination.
    Chaos Solitons & Fractals 11/2015; 80. DOI:10.1016/j.chaos.2015.04.018
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    ABSTRACT: Cascading failure is one of the most central topics in the field of complex networks. In this paper, the cascading failure model is extended to the case of interdependent networks, and the effect of coupling preference on systems robustness is intensively investigated. It is found that the performance of coupling preference on robustness is dependent on coupling probability. Disassortative coupling is more robust for sparse coupling while assortative coupling performs better for dense coupling. We provide an explanation for this constructive phenomenon via examining cascading process from the microscopic point of view. Our work can be useful to the design and optimization of interdependent networked systems.
    Chaos Solitons & Fractals 11/2015; 80. DOI:10.1016/j.chaos.2015.03.005
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    ABSTRACT: The main point of this paper is to present how a generalised self-organisation framework can lead to a higher performance within adaptive networks. We take a simple example in the distributed task allocation to explain this framework, where each agent and its neighbourhood form a local network. The whole system is built up by many localised components, whose performance is highly influenced by the interdependent network structures. The basic queuing theory concepts are adopted to characterise the function of the agents, where they send and receive tasks locally. Through the load flow-in and flow-out, an adaptive control mechanism is applied to learn the rewiring parameters continuously. After that, a universal energy-based Metropolis rewiring method is used to quantify the structure adaptation, driving the network to a favourable one. This function-learning-adaptation (FLA) framework is implemented by the agents in a local, informative and quantitative manner, which can be widely used in many real-world applications.
    Chaos Solitons & Fractals 11/2015; 80. DOI:10.1016/j.chaos.2015.06.005
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    ABSTRACT: Based on the observance in human society, the satisfaction level of an individual as a result of an obtained payoff depends on personal tendency to some extent; we establish a new model for spatial prisoner’s dilemma games. We describe individual satisfaction as a stochastically deviated value around each of the four payoffs stipulated by a payoff matrix, which is maintained throughout the life of a certain agent. When strategy updating, an agent who refers to his own satisfaction level cannot see neighbors’ satisfaction levels but can only observe neighbors’ accumulated payoffs. By varying the update rule and underlying topology, we perform numerical simulations that reveal cooperation is significantly enhanced by this change. We argue that this enhancement of cooperation is analogous to a stochastic resonance effect, like the payoff noise effects Perc (2006).
    Chaos Solitons & Fractals 11/2015; 80. DOI:10.1016/j.chaos.2015.02.025
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    ABSTRACT: Epilepsy is a typical neural disease in nervous system, and the control of seizures is very important for treating the epilepsy. It is well known that the drug treatment is the main strategy for controlling the epilepsy. However, there are about 10–15 percent of patients, whose seizures cannot be effectively controlled by means of the drug. Alternatively, the deep brain stimulus (DBS) technology is a feasible method to control the serious seizures. However, theoretical explorations of DBS are still absent, and need to be further made. Presently, we will explore to control the absence seizures by introducing the DBS to a basal ganglia thalamocortical network model. In particular, we apply DBS onto substantia nigra pars reticulata (SNr) and the cortex to explore its effects on controlling absence seizures, respectively. We can find that the absence seizure can be well controlled within suitable parameter ranges by tuning the period and duration of current stimulation as DBS is implemented in the SNr. And also, as the DBS is applied onto the cortex, it is shown that for the ranges of present parameters, only adjusting the duration of current stimulation is an effective control method for the absence seizures. The obtained results can have better understanding for the mechanism of DBS in the medical treatment.
    Chaos Solitons & Fractals 11/2015; 80. DOI:10.1016/j.chaos.2015.02.014
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    ABSTRACT: Traffic process is ubiquitous in many critical infrastructures. In this paper, we introduce a mechanism to dynamically allocate the delivering capacity into the data-packet traffic model on the coupled Internet autonomous-system-level network of South Korea and Japan, and focus on its effect on the transport efficiency. In this mechanism, the total delivering capacity is constant and the lowest-load node will give one unit delivering capacity to the highest-load node at each time step. It is found that the delivering capacity of busy nodes and non-busy nodes can be well balanced and the effective betweenness of busy nodes with interconnections is significantly reduced. Consequently, the transport efficiency such as average traveling time and packet arrival rate is remarkably improved. Our work may shed some light on the traffic dynamics in coupled networks.
    Chaos Solitons & Fractals 11/2015; 80:56-61. DOI:10.1016/j.chaos.2015.05.030
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    ABSTRACT: A new model of mixed strategy system for spatial prisoner’s dilemma games is proposed. As an alternative to the typical mixed strategy system, wherein a behavior of either cooperation or defection is stochastically determined for each neighbor based on the agent’s overall strategy, in our mixed strategy system, the agent instead correlates his strategies with those of his neighbors. For example, he tends to offer cooperation more frequently to his neighbor who is cooperative more often. This model provides results with significantly enhanced cooperation compared with those obtained with the conventional mixed strategy model. Interestingly, some of the evolutionary paths followed under strong dilemma situations can be divided into two specific periods: Defector-Enduring (D-END), when the number of defectors rapidly decreases, and the subsequent Defector-Expanding (D-EXP), when the surviving defectors’ clusters start to expand, allowing the global cooperation fraction to fall to a lower level. The D-END and D-EXP periods seem analogous to the END and EXP periods presented by the author in previous studies.
    Chaos Solitons & Fractals 11/2015; 80:39-46. DOI:10.1016/j.chaos.2015.03.021
  • Guanghu Zhu · Xinchu Fu · Qinggan Tang · Kezan Li
    Chaos Solitons & Fractals 11/2015; 80:117-124. DOI:10.1016/j.chaos.2015.08.004
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    ABSTRACT: Time delay induced-multiple synchronous behaviors are simulated in neuronal network composed of many inhibitory neurons and appear at different time delays shorter than a period of endogenous bursting of individual neurons. It is different from previous investigations wherein only one of multiple synchronous behaviors appears at time delay shorter than a period of endogenous firing and others appear at time delay longer than the period duration. The bursting patterns of the synchronous behaviors are identified based on the dynamics of an individual neuron stimulated by a signal similar to the inhibitory coupling current, which is applied at the decaying branch of a spike and suitable phase within the quiescent state of the endogenous bursting. If a burst of endogenous bursting contains more spikes, the synchronous behaviors appear at more regions of time delay. As the coupling strength increases, the multiple synchronous behaviors appear in a sequence because the different threshold of coupling current or strength is needed to achieve synchronous behaviors. From regular, to small-world, and to random networks, synchronous degree of the multiple synchronous behaviors becomes weak, and synchronous bursting patterns with lower spikes per burst disappear, which is properly interpreted by the difference of coupling current between neurons induced by different degree and the high threshold of coupling current to achieve synchronization for the absent synchronous bursting patterns. The results of the influence of individual neurons, topology of network, time delay, and coupling strength on the multiple synchronous behaviors are helpful to the understanding of the synchronous dynamics of the neuronal network composed of inhibitory neurons.
    Chaos Solitons & Fractals 10/2015; 80. DOI:10.1016/j.chaos.2015.06.017
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    ABSTRACT: Abstract In order to deeply understand the complex interdependent systems, it is of great concern to take clustering coefficient, which is an important feature of many real-world systems, into account. Previous study mainly focused on the impact of clustering on interdependent networks under random attacks, while we extend the study to the case of the more realistic attacking strategy, targeted attack. A system composed of two interdependent scale-free networks with tunable clustering is provided. The effects of coupling strength and coupling preference on attack vulnerability are explored. Numerical simulation results demonstrate that interdependent links between two networks make the entire system much more fragile to attacks. Also, it is found that clustering significantly increases the vulnerability of interdependent scale-free networks. Moreover, for fully coupled network, disassortative coupling is found to be most vulnerable to random attacks, while the random and assortative coupling have little difference. Additionally, enhancing coupling strength can greatly enhance the fragility of interdependent networks against targeted attacks. These results can not only improve the deep understanding of structural complexity of complex systems, but also provide insights into the guidance of designing resilient infrastructures.
    Chaos Solitons & Fractals 10/2015; 80. DOI:10.1016/j.chaos.2015.06.022
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    ABSTRACT: Understanding the behavioral evolution in evacuation is significant for guiding and controlling the evacuation process. Based on the fact that the population consists of many small groups, here we model the small groups which are separated in space but linked by other methods, such as kinship, on interconnected networks. Namely, the players in the same layer belong to an identical small group, while the players located in different layers belong to different small groups. And the players of different layers establish interaction by edge crossed layers. In addition, players face different dilemmas inside and outside small groups, in detail, the players in the same layer play prisoner's dilemma, but players in different layers play harmony game. By means of numerous simulations, we study the impact of the ratio and strength of link on the behavioral evolution. Because the framework of this work takes the space distribution into account, which is close to the realistic life, we hope that it can provide a new insight to reveal the law of behavioral evolution of evacuation population.
    Chaos Solitons & Fractals 10/2015; 80. DOI:10.1016/j.chaos.2015.06.016