Showing papers in "Physica A-statistical Mechanics and Its Applications in 2005"
TL;DR: It is argued that recurrent fuzzy relationships, which were simply ignored in previous studies, should be considered in forecasting and recommended that different weights be assigned to various fuzzy relationships.
Abstract: This study proposes weighted models to tackle two issues in fuzzy time series forecasting, namely, recurrence and weighting. It is argued that recurrent fuzzy relationships, which were simply ignored in previous studies, should be considered in forecasting. It is also recommended that different weights be assigned to various fuzzy relationships. In previous studies, these fuzzy relationships were treated as if they were equally important, which might not have properly reflected the importance of each individual fuzzy relationship in forecasting. The weighted models are compared with the local regression models in which weight functions also play an important role. Both models are different by nature, but certain theoretical backgrounds in local regression models are adopted. By using the Taiwan stock index as the forecasting target, the empirical results show that the weighted model outperforms one of the conventional fuzzy time series models.
444 citations
TL;DR: In this article, the authors studied the temporal dependence of the parameters describing the WTW topology, exploiting the peculiar reciprocity structure of WTW to recover the directed nature of international trade channels.
Abstract: The World Trade Web (WTW), the network defined by the international import/export trade relationships, has been recently shown to display some important topological properties which are tightly related to the Gross Domestic Product of world countries. While our previous analysis focused on the static, undirected version of the WTW, here we address its full evolving, directed description. This is accomplished by exploiting the peculiar reciprocity structure of the WTW to recover the directed nature of international trade channels, and by studying the temporal dependence of the parameters describing the WTW topology.
421 citations
TL;DR: In this paper, the Laplace transform theory was used for synchronization of the fractional Lu system, and the suitable conditions for achieving synchronization of this fractional differential system were derived by using the La Place transform theory.
Abstract: Chaos synchronization of the fractional Lu system is theoretically and numerically studied by two methods. The suitable conditions for achieving synchronization of this fractional differential system are derived by using the Laplace transform theory. Numerical simulations coincide with the theoretical analysis.
362 citations
TL;DR: The main empirical results are the broad distributions of various quantities and the existence of weight-topology correlations which show that weights are relevant and that in general the modeling of complex networks must go beyond topology.
Abstract: We review the main tools which allow for the statistical characterization of weighted networks. We then present two case studies, the airline connection network and the scientific collaboration network which are representatives of critical infrastructure and social system, respectively. The main empirical results are (i) the broad distributions of various quantities and (ii) the existence of weight-topology correlations. These measurements show that weights are relevant and that in general the modeling of complex networks must go beyond topology. We review a model which provides an explanation for the features observed in several real-world networks. This model of weighted network formation relies on the dynamical coupling between topology and weights, considering the rearrangement of new links are introduced in the system.
340 citations
TL;DR: In this article, a stabilization theorem for processes of opinion dynamics is presented, applicable to a wide class of models of continuous opinion dynamics based on averaging (like the models of Hegselmann-Krause and Weisbuch-Deffuant).
Abstract: A stabilization theorem for processes of opinion dynamics is presented. The theorem is applicable to a wide class of models of continuous opinion dynamics based on averaging (like the models of Hegselmann–Krause and Weisbuch–Deffuant). The analysis detects self-confidence as a driving force of stabilization.
337 citations
TL;DR: An algorithm to detect community structure in complex networks based on spectral methods and takes into account weights and link orientation is developed, which proves to be successful both in clustering words, and in uncovering mental association patterns.
Abstract: We develop an algorithm to detect community structure in complex networks. The algorithm is based on spectral methods and takes into account weights and link orientation. Since the method detects efficiently clustered nodes in large networks even when these are not sharply partitioned, it turns to be specially suitable for the analysis of social and information networks. We test the algorithm on a large-scale data-set from a psychological experiment of word association. In this case, it proves to be successful both in clustering words, and in uncovering mental association patterns.
295 citations
290 citations
TL;DR: In this article, the authors show that a dune can become vegetated when the wind power is sufficiently low and that a much higher wind stress is needed to destroy the vegetation and re-activate the dunes.
Abstract: Sand dunes form an important and unique system that can be mobile or fixed by vegetation. The common mobility indices of sand dunes, which are related to the wind and the amount of precipitation and potential evaporation, do not work in many dune fields around the world. The reasons for that lie in the singular physical characteristics of the sandy soil. Sand has high hydraulic conductivity causing a high rate of infiltration of rain water to the groundwater. Sand particles lack cohesion and that makes wind erosion the main limiting factor for vegetation. Hence, wind power, manifested by the drift potential (DP), is a good index for the limiting factor of plants on sand. The physical–biological interaction is further developed by hysteresis, which shows that a dune can become vegetated when the wind power is sufficiently low. Once vegetated, a much higher wind stress is needed to destroy the vegetation and re-activate the dunes.
289 citations
TL;DR: The reliability of electric transmission systems is examined using a scale-free model of network topology and failure propagation, and the results suggest that scale- free network models are usable to estimate aggregate electric grid reliability.
Abstract: The reliability of electric transmission systems is examined using a scale-free model of network topology and failure propagation. The topologies of the North American eastern and western electric grids are analyzed to estimate their reliability based on the Barabasi–Albert network model. A commonly used power system reliability index is computed using a simple failure propagation model. The results are compared to the values of power system reliability indices previously obtained using standard power engineering methods, and they suggest that scale-free network models are usable to estimate aggregate electric grid reliability.
278 citations
TL;DR: In this article, a new three-dimensional continuous quadratic autonomous chaotic system, modified from the Lorenz system, was reported, in which each equation contains a single quadralatic crossproduct term, which is different from the original Lorenz, Rossler, Chen, Lu systems.
Abstract: This paper reports a new three-dimensional continuous quadratic autonomous chaotic system, modified from the Lorenz system, in which each equation contains a single quadratic cross-product term, which is different from the Lorenz, Rossler, Chen, Lu systems. Basic properties of the new system are analyzed by means of Lyapunov exponent spectrum and bifurcation diagrams. Analysis results show that this system has complex dynamics with some interesting characteristics.
260 citations
TL;DR: In this article, a stochastic SIR model with or without distributed time delay is proposed and the stability of disease-free equilibrium is studied. But, the model is not suitable for the case where the introduction of noise modifies the threshold for an epidemic to occur.
Abstract: We propose a stochastic SIR model with or without distributed time delay and we study the stability of disease-free equilibrium. The numerical simulation of the stochastic SIR model shows that the introduction of noise modifies the threshold of system for an epidemic to occur and the threshold stochastic value is found.
TL;DR: A cell-centered approach to developmental biology Why can / should we use the potts model as discussed by the authors, and how to use the Potts model in the context of developmental biology.
Abstract: A cell-centered approach to developmental biology Why can / should we use the potts model
TL;DR: In this article, a revision of Newton's law of viscosity appearing in the role of the deviatoric stress tensor in the Navier-Stokes equation is proposed for the case of compressible fluids, both gaseous and liquid.
Abstract: A revision of Newton's law of viscosity appearing in the role of the deviatoric stress tensor in the Navier–Stokes equation is proposed for the case of compressible fluids, both gaseous and liquid. Explicitly, it is hypothesized that the velocity v appearing in the velocity gradient term ∇ v in Newton's rheological law be changed from the fluid's mass-based velocity v m , the latter being the velocity appearing in the continuity equation, to the fluid's volume velocity v v , the latter being a stand-in for the fluid's volume current (volume flux density n v ). A similar v m → v v alteration is proposed for the velocity v appearing in the no-slip tangential velocity boundary condition at solid surfaces. These proposed revisions are based upon both experiment and theory, including re-interpretation of the following three items: (i) experimental “near-continuum” thermophoretic and other low Reynolds number phoretic data for the movement of suspended particles in fluids under the influence of mass density gradients ∇ ρ , caused either by temperature gradients in single-component fluids undergoing heat transfer or by species concentration gradients in inhomogeneous two-component mixtures undergoing mass transfer; (ii) the hierarchical re-ordering of the Burnett terms appearing in the Chapman–Enskog gas-kinetic theory perturbation expansion of the viscous stress tensor from one of being based upon small Knudsen numbers to one of being based upon small Mach numbers; (iii) Maxwell's (1879) ubiquitous v m -based “thermal creep” or “thermal stress” slip boundary condition used in nonisothermal gas-kinetic theory models, recast in the form of a v v -based no-slip condition. The v v vs. v m dichotomy in the case of compressible fluids is shown to lead to a fundamental distinction between the fluid's tracer velocity as recorded by monitoring the spatio-temporal trajectory of a small non-Brownian particle deliberately introduced into the fluid, and the fluid's “optical” or “colorimetric” velocity as monitored, for example, by the introduction of a dye into the fluid or by some photochromic- or fluorescence-based scheme in circumstances where the individual fluid molecules are themselves responsive to being probed by light. Explicitly, it is argued that the fluid's tracer velocity, representing a strictly continuum nonmolecular notion, is v v , whereas its colorimetric velocity, which measures the mean velocity of the molecules of which the fluid is composed, is v m .
TL;DR: This study proposes the use of a Type 2 fuzzy time series model, in which extra observations are used to enrich or to refine the fuzzy relationships obtained from Type 1 models and then to improve forecasting performance.
Abstract: Most conventional fuzzy time series models (Type 1 models) utilize only one variable in forecasting. Furthermore, only part of the observations in relation to that variable are used. To utilize more of that variable's observations in forecasting, this study proposes the use of a Type 2 fuzzy time series model. In such a Type 2 model, extra observations are used to enrich or to refine the fuzzy relationships obtained from Type 1 models and then to improve forecasting performance. The Taiwan stock index, the TAIEX, is used as the forecasting target. The study period extends over the 2000–2003 period. The TAIEX from January to October in each year is used for the estimation, while that covering November and December is used for forecasting. The empirical analyses show that Type 2 model outperforms Type 1 model.
TL;DR: In this paper, the attraction mechanism and the structure of counterionic correlations are discussed in the limit of strong coupling based on recent numerical and analytical investigations and for various geometries (planar, spherical and cylindrical) of charged objects.
Abstract: Charged soft-matter systems—such as colloidal dispersions and charged polymers—are dominated by attractive forces between constituent like-charged particles when neutralizing counterions of high charge valency are introduced. Such counter-intuitive effects indicate strong electrostatic coupling between like-charged particles, which essentially results from electrostatic correlations among counterions residing near particle surfaces. In this paper, the attraction mechanism and the structure of counterionic correlations are discussed in the limit of strong coupling based on recent numerical and analytical investigations and for various geometries (planar, spherical and cylindrical) of charged objects.
TL;DR: The 'faster is slower' effect induced by panic is analyzed and can be explained in terms of increasing clogging delays probability which shows a strong correlation with certain structures that the authors call 'blocking clusters'.
Abstract: In the present work, we studied the room evacuation problem using the social force model introduced by Helbing and coworkers. This model allows to explore different degree of panic. The 'faster is slower' effect induced by panic is analyzed. It can be explained in terms of increasing clogging delays probability which shows a strong correlation with certain structures that we call 'blocking clusters'. Also, the influence of the exit door size over the evacuation efficiency is briefly discussed. Language: en
TL;DR: In this paper, the authors derived the fractional generalization of the Ginzburg-Landau equation from the variational Euler-Lagrange equation for fractal media.
Abstract: We derive the fractional generalization of the Ginzburg–Landau equation from the variational Euler–Lagrange equation for fractal media. To describe fractal media we use the fractional integrals considered as approximations of integrals on fractals. Some simple solutions of the Ginzburg–Landau equation for fractal media are considered and different forms of the fractional Ginzburg–Landau equation or nonlinear Schrodinger equation with fractional derivatives are presented. The Agrawal variational principle and its generalization have been applied.
TL;DR: In this paper, the authors propose a network description of large market investments, where both stocks and shareholders are represented as vertices connected by weighted links corresponding to shareholdings, and they find that k in scales as a power-law function of v with an exponent β.
Abstract: We propose a network description of large market investments, where both stocks and shareholders are represented as vertices connected by weighted links corresponding to shareholdings. In this framework, the in-degree ( k in ) and the sum of incoming link weights ( v ) of an investor correspond to the number of assets held ( portfolio diversification ) and to the invested wealth ( portfolio volume ), respectively. An empirical analysis of three different real markets reveals that the distributions of both k in and v display power-law tails with exponents γ and α . Moreover, we find that k in scales as a power-law function of v with an exponent β . Remarkably, despite the values of α , β and γ differ across the three markets, they are always governed by the scaling relation β = ( 1 - α ) / ( 1 - γ ) . We show that these empirical findings can be reproduced by a recent model relating the emergence of scale-free networks to an underlying Paretian distribution of ‘hidden’ vertex properties.
TL;DR: A new approach to form complex, engineered, interconnected neuronal network with pre-designed geometry via engineering the self-assembly process of neurons, distinct from previously reported formation of clusterized neural networks.
Abstract: A novel approach was developed to form engineered, electrically viable, neuronal networks, consisting of ganglion-like clusters of neurons. In the present method, the clusters are formed as the cells migrate on low affinity substrate towards high affinity, lithographically defined carbon nanotube templates on which they adhere and assemble. Subsequently, the gangliated neurons send neurites to form interconnected networks with pre-designed geometry and graph connectivity. This process is distinct from previously reported formation of clusterized neural networks in which a network of linked neurons collapses via neuronal migration along the inter-neuron links. The template preparation method is based on photo-lithography, micro-contact printing and carbon nanotube chemical vapor deposition techniques. The present work provides a new approach to form complex, engineered, interconnected neuronal network with pre-designed geometry via engineering the self-assembly process of neurons.
TL;DR: An evolutionary model based on entropy as a selective criterion is formulated and it is shown that it predicts the direction of changes in network structure over evolutionary time and accounts for the high degree of robustness and the heterogenous connectivity distribution, which is often observed in biological and technological networks.
Abstract: This article introduces the concept of network entropy as a characteristic measure of network topology. We provide computational and analytical support for the hypothesis that network entropy is a quantitative measure of robustness. We formulate an evolutionary model based on entropy as a selective criterion and show that (a) it predicts the direction of changes in network structure over evolutionary time and (b) it accounts for the high degree of robustness and the heterogenous connectivity distribution, which is often observed in biological and technological networks. Our model is based on Darwinian principles of evolution and preferentially selects networks according to a global fitness criterion, rather than local preferences in classical models of network growth. We predict that the evolutionarily stable states of evolved networks will be characterized by extremal values of network entropy.
IBM1
TL;DR: It is found that a modest alteration of an initially ‘scale-free’ network can usefully improve robustness against attack, particularly when the fraction of attacked nodes is small, and the modification schemes that are most effective for this purpose are identified.
Abstract: An important property of networked systems is their robustness against removal of network nodes, through either random node failure or targeted attack. Although design methods have been proposed for creating, ab initio, a network that has optimal robustness according to a given measure, one is often instead faced with an existing network that cannot feasibly be substantially modified or redesigned, yet whose robustness can be improved by a lesser degree of modification. We present empirical results that show how robustness, as measured either by the size of the largest connected component or by the shortest path length between pairs of nodes, is affected by several different strategies that alter the network by rewiring a fraction of the edges or by adding new edges. We find that a modest alteration of an initially ‘scale-free’ network can usefully improve robustness against attack, particularly when the fraction of attacked nodes is small, and we identify modification schemes that are most effective for this purpose.
TL;DR: In this paper, a model for anomalous diffusion processes with random jump sizes and random inter-jump time intervals with infinite means (and variances) which do not satisfy the Law of Large Numbers is discussed.
Abstract: The paper discusses a model for anomalous diffusion processes. Their one-point probability density functions (p.d.f.) are exact solutions of fractional diffusion equations. The model reflects the asymptotic behavior of a jump (anomalous random walk) process with random jump sizes and random inter-jump time intervals with infinite means (and variances) which do not satisfy the Law of Large Numbers. In the case when these intervals have a fractional exponential p.d.f., the fractional Komogorov–Feller equation for the corresponding anomalous diffusion is provided and methods of finding its solutions are discussed. Finally, some statistical properties of solutions of the related Langevin equation are studied. The subdiffusive case is explored in detail. The emphasis is on a rigorous presentation which, however, would be accessible to the physical sciences audience.
TL;DR: This work presents an analysis of communality structure in networks based on the application of simulated annealing techniques and uses as “cost function” the already introduced modularity Q (1), which isbased on the relative number of links within a commune against the number of Links that would correspond in case the links were distributed randomly.
Abstract: We present an analysis of communality structure in networks based on the application of simulated annealing techniques. In this case we use as “cost function” the already introduced modularity Q (1), which is based on the relative number of links within a commune against the number of links that would correspond in case the links were distributed randomly. We compare the results of our approach against other methodologies based on betweenness analysis and show that in all cases a better community structure can be attained.
TL;DR: The security of Fridrich's algorithm against brute-force attack, statistical attack, known-plain text attack and select-plaintext attack is analyzed by investigating the properties of the involved chaotic maps and diffusion functions.
Abstract: The security of Fridrich's algorithm against brute-force attack, statistical attack, known-plaintext attack and select-plaintext attack is analyzed by investigating the properties of the involved chaotic maps and diffusion functions. Based on the given analyses, some means are proposed to strengthen the overall performance of the focused cryptosystem.
TL;DR: In this paper, three different versions of optimal velocity models are examined and the stability conditions of the models are obtained by using the linear stability theory, and the general solutions are given for, which can lead to specific solutions in previous work.
Abstract: The jams in the congested traffic are related with various density waves, which might be governed by the nonlinear wave equations, such as the Korteweg–de-Vries (KdV) equation, the Burgers equation and the modified Korteweg–de-Vries (mKdV) equation. Three different versions of optimal velocity models are examined. The stability conditions of the models are obtained by using the linear stability theory. The KdV equation near the neutral stability line and the mKdV equation around the critical point are derived by applying the reductive perturbation method, respectively. The traffic jams could be thus described by the KdV and kink–antikink soliton solutions for the two kinds of equations. The general solutions are given for, which can lead to specific solutions in previous work. Moreover, they are applied to solve a new model—the full velocity difference model and the corresponding KdV and kink–antikink soliton solutions could be quickly obtained, which demonstrates the general solutions presented herein are useful.
TL;DR: A refined fuzzy time-series model is proposed that can refine the lengths of intervals during the formulation of fuzzy relationships, and hence capture the fuzzy relationships more appropriately, so that the forecasting results can be improved.
Abstract: Fuzzy time-series models have been used to model observations, where each one of them contains multiple values. The formulation of fuzzy relationships and the lengths of intervals are considered to be two of the critical factors that affect forecasting results. Unfortunately, the lengths of the intervals were determined during the early stages of forecasting in these models, and they thus often failed to reflect the distribution of observations. This study therefore proposes a refined fuzzy time-series model to further refine the lengths of intervals. This model can refine the lengths of intervals during the formulation of fuzzy relationships, and hence capture the fuzzy relationships more appropriately. As a result, the forecasting results can be improved. Both the stock index and enrollment are used as the targets in the empirical analysis.
TL;DR: A special technique is introduced considering human behavior to make the rules more reasonable in pedestrian movement by simulating the two-dimension pedestrian movement in corridor, and the phase transition phenomena of pedestrian movement, including the walkers moving bottom-up and top-down are presented.
Abstract: The pedestrian movement is more complex than vehicular flow for the reason that people are more flexible and intelligent than cars. Without the limit of "lanes" pedestrian movement is loose and free. Furthermore, they are easily affected by other walkers as well as the environment around. In this paper, a special technique is introduced considering human behavior to make the rules more reasonable. By simulating the two-dimension pedestrian movement in corridor, the phase transition phenomena of pedestrian movement, including the walkers moving bottom-up and top-down, are presented. Studying on the effect of possibility of exchange position between face-to-face pedestrians propose that the considerable exchange possibility is about 0.20 in the scope studied in this paper. Language: en
TL;DR: In this paper, a statistical significance test for the Hurst exponent was proposed and applied to real financial data sets, showing no long-term memory in some financial returns, suggesting that Brownian motion cannot be rejected as a model for price dynamics.
Abstract: A fundamental hypothesis of quantitative finance is that stock price variations are independent and can be modeled using Brownian motion. In recent years, it was proposed to use rescaled range analysis and its characteristic value, the Hurst exponent, to test for independence in financial time series. Theoretically, independent time series should be characterized by a Hurst exponent of 1/2. However, finite Brownian motion data sets will always give a value of the Hurst exponent larger than 1/2 and without an appropriate statistical test such a value can mistakenly be interpreted as evidence of long term memory. We obtain a more precise statistical significance test for the Hurst exponent and apply it to real financial data sets. Our empirical analysis shows no long-term memory in some financial returns, suggesting that Brownian motion cannot be rejected as a model for price dynamics.
TL;DR: The results indicate that proteins, regardless of their structural class, show small-world network property, which provides indications of modularity in protein networks.
Abstract: Protein structures can be studied as complex networks of interacting amino acids. We study proteins of different structural classes from the network perspective. Our results indicate that proteins, regardless of their structural class, show small-world network property. Various network parameters offer insight into the structural organisation of proteins and provide indications of modularity in protein networks.
TL;DR: In this article, a convective/diffusive/production-type transport equation, ρ D m v ^ / Dt + ∇ · j v = π v, was derived for the evolution of the fluid's specific volume v ^ = 1 / ρ.
Abstract: The transport and production of the generally non-conserved extensive property of volume V within a flowing gas or liquid is addressed. Specifically, a convective/diffusive/production-type transport equation, ρ D m v ^ / Dt + ∇ · j v = π v , governing the transport of volume, is derived for the evolution of the fluid's specific volume v ^ = 1 / ρ . Here, ρ is the density, D m / Dt the material derivative, j v the diffusive flux density vector of volume, and π v the temporal rate of production of volume. This equation governs the transport of volume in precisely the same sense as do its counterparts governing the transport of other extensive properties, including mass, individual species mass in multicomponent mixtures, energy, entropy, momentum, and the like. Constitutive expressions are developed for both j v and π v in terms of the local specific-volume gradient ∇ v ^ and the physicochemical properties of the extensive property being transported, which volume inseparably accompanies. The resulting expressions are valid for situations wherein the state of the system is governed by a single independent variable, such as composition in an isothermal binary mixture, or temperature in a single-component system (the fluid in both cases being assumed effectively isobaric, consistent with the local mechanical equilibrium hypothesis of irreversible thermodynamics). The phenomenological volume diffusivity coefficient α v appearing in the constitutive equation j v = - α v ρ ∇ v ^ for the diffusive flux density is shown to be equal to either the binary molecular diffusivity D in the former case or to the thermometric diffusivity α in the latter case. In the important dual circumstances where a “law of additive volumes” is applicable to the fluid, and where the extensive property accompanying the volume being transported is a conserved property, volume itself becomes a conserved property. In that case one has that π v = 0 for the production term in the volume transport equation. Inseparably related to the notion of a diffusive flux density j v of volume is the concept of a convective volume velocity v v . The latter velocity is shown to be related via the formula v v = v m + j v to the fluid's ubiquitous barycentric velocity v m appearing in the continuity equation governing the transport of mass. In the binary mixture case these two velocities are, respectively, identified with the well-known volume- and mass-average velocities of the fluid.