application of renyi and tsallis entropies to topic modeling optimization abstract this study proposes to minimize renyi and tsallis entropies for finding the optimal number of topics t in topic modeling tm a promising tool to obtain knowledge about large text collections tm is a method whose properties are underresearched in particular parameter optimization in such models has been hindered by the use of monotonous quality functions with no clear thresholds in this research topic models obtained from large text collections are viewed as nonequilibrium complex systems where the number of topics is regarded as an equivalent of temperature this allows calculating free energy of such systems a value through which both renyi and tsallis entropies are easily expressed numerical experiments with four tm algorithms and two text collections show that both entropies as functions of the number of topics yield clear minima in the middle area of the range of t on the marked up dataset the minima of three algorithms correspond to the value of t detected by humans it is concluded that tsallis and especially renyi entropy can be used for t optimization instead of shannon entropy that decreases even when t becomes obviously excessive additionally some algorithms are found to be better suited for revealing local entropy minima finally we test whether the overall content of all topics taken together is resistant to the change of t and find out that this dependence has a quasi periodic structure which demands further research

statistical mechanics and phase transitions in clustering a new approach to clustering based on statistical physics is presented the problem is formulated as fuzzy clustering and the association probability distribution is obtained by maximizing the entropy at a given average variance the corresponding lagrange multiplier is related to the temperature and motivates a deterministic annealing process where the free energy is minimized at each temperature critical temperatures are derived for phase transitions when existing clusters split it is a hierarchical clustering estimating the most probable cluster parameters at various average variances

an extended car following model considering multi anticipative average velocity effect under v2v environment abstract vehicle to vehicle for short v2v communication technology is regarded as a promising technology to improve traffic efficiency and safety in this paper an extended car following model is proposed to simulate traffic flow by considering multi anticipative average velocity effect including the average velocity and the mean expected velocity field effect of preceding vehicles group under v2v environment the stability condition of this model is obtained by applying the linear stability theory the phase diagram comparison and analysis shows that the multi anticipative average velocity effect can effectively enhance the stabilization of traffic system in particular the average velocity effect plays a more important role than that of the mean expected velocity field effect in improving the stability of traffic flow the mkdv equation is derived to describe the evolution characteristics of traffic density waves by using the reductive perturbation method furthermore the numerical simulation is carried out to validate the theoretical results and indicates that the traffic jam can be suppressed efficiently via taking into account multi anticipative average velocity effect

option pricing formulas based on a non gaussian stock price model options are financial instruments that depend on the underlying stock we explain their non gaussian fluctuations using the nonextensive thermodynamics parameter q a generalized form of the black scholes bs partial differential equation and some closed form solutions are obtained the standard bs equation q 1 which is used by economists to calculate option prices requires multiple values of the stock volatility known as the volatility smile using q 1 5 which well models the empirical distribution of returns we get a good description of option prices using a single volatility

finding the number of clusters in a dataset one of the most difficult problems in cluster analysis is identifying the number of groups in a dataset most previously suggested approaches to this problem are either somewhat ad hoc or require parametric assumptions and complicated calculations in this article we develop a simple yet powerful nonparametric method for choosing the number of clusters based on distortion a quantity that measures the average distance per dimension between each observation and its closest cluster center our technique is computationally efficient and straightforward to implement we demonstrate empirically its effectiveness not only for choosing the number of clusters but also for identifying underlying structure on a wide range of simulated and real world datasets in addition we give a rigorous theoretical justification for the method based on information theoretic ideas specifically results from the subfield of electrical engineering known as rate distortion theory allow us to describe the behavior of the dist

a new car following model considering the related factors of a gyroidal road abstract a novel car following model was proposed to describe the motion of the vehicles on a single lane gyroidal road we explore the related effects of gyroidal road upon uniform traffic flow analytically and numerically the analytical result shows that the related factors of gyroidal road including the friction coefficient radius of curvature and slope have great influences on the stability of the uniform flow respectively the modified kdv korteweg de vries equation is derived in the unstable area and the kink solution is obtained near the critical point a series of simulations are conducted to verify the effects upon uniform traffic flow under different road conditions it is shown that the amplitudes of the headway oscillation wave were affected by the friction coefficient radius of curvature and slope respectively the numerical results are in good agreement with the analytical results

kdv and kink antikink solitons in car following models 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

stability analysis of a new lattice hydrodynamic model by considering lattice s self anticipative density effect abstract in this paper a new lattice hydrodynamic model with consideration of the density difference of a lattice s current density and its anticipative density is proposed the influence of lattice s self anticipative density on traffic stability is revealed through linear stability theory and it shows that lattice s self anticipative density can improve the stability of traffic flow to describe the phase transition of traffic flow the mkdv equation near the critical point is derived by using nonlinear analysis method the propagating behavior of density wave in the unstable region can be described by the kink antikink soliton of the mkdv equation numerical simulation validates the analytical results which shows that traffic jam can be suppressed efficiently by considering lattice s self anticipative density in the modified lattice hydrodynamic model

information distance in multiples information distance is a parameter free similarity measure based on compression used in pattern recognition data mining phylogeny clustering and classification the notion of information distance is extended from pairs to multiples finite lists we study maximal overlap metricity universality minimal overlap additivity and normalized information distance in multiples we use the theoretical notion of kolmogorov complexity which for practical purposes is approximated by the length of the compressed version of the file involved using a real world compression program

the stabilization effect of the density difference in the modified lattice hydrodynamic model of traffic flow abstract a modified lattice hydrodynamic model of traffic flow is proposed by introducing the density difference between the leading and the following lattice the stability condition of the modified model is obtained through the linear stability analysis the results show that considering the density difference leads to the stabilization of the system the burgers equation and mkdv equation are derived to describe the density waves in the stable and unstable regions respectively numerical simulations show that considering the density difference not only could stabilize traffic flow but also makes the lattice hydrodynamic model more realistic

metrics for labelled markov processes the notion of process equivalence of probabilistic processes is sensitive to the exact probabilities of transitions thus a slight change in the transition probabilities will result in two equivalent processes being deemed no longer equivalent this instability is due to the quantitative nature of probabilistic processes in a situation where the process behavior has a quantitative aspect there should be a more robust approach to process equivalence this paper studies a metric between labelled markov processes this metric has the property that processes are at zero distance if and only if they are bisimilar the metric is inspired by earlier work on logics for characterizing bisimulation and is related in spirit to the hutchinson metric

an asymmetric full velocity difference car following model abstract this paper presents a car following model that considers the asymmetric characteristic of the velocity differences of the vehicles in a traffic stream the problems of the prevalent general force gf model and the full velocity difference fvd model were solved furthermore the optimal velocity ov model the gf model and the fvd model are proved to be the special cases of the proposed asymmetric full velocity difference afvd model the mathematical model is presented followed by simulation analysis which demonstrates the properties of the afvd model

a new car following model for autonomous vehicles flow with mean expected velocity field abstract due to the development of the modern scientific technology autonomous vehicles may realize to connect with each other and share the information collected from each vehicle an improved forward considering car following model was proposed with mean expected velocity field to describe the autonomous vehicles flow behavior the new model has three key parameters adjustable sensitivity strength factor and mean expected velocity field size two lemmas and one theorem were proven as criteria for judging the stability of homogeneousautonomous vehicles flow theoretical results show that the greater parameters means larger stability regions a series of numerical simulations were carried out to check the stability and fundamental diagram of autonomous flow from the numerical simulation results the profiles hysteresis loop and density waves of the autonomous vehicles flow were exhibited the results show that with increased sensitivity strength factor or field size the traffic jam was suppressed effectively which are well in accordance with the theoretical results moreover the fundamental diagrams corresponding to three parameters respectively were obtained it demonstrates that these parameters play almost the same role on traffic flux i e before the critical density the bigger parameter is the greater flux is and after the critical density the opposite tendency is in general the three parameters have a great influence on the stability and jam state of the autonomous vehicles flow

differential privacy in probabilistic systems abstract ever since proposed by dwork differential privacy has been a hot topic in academia however few attempts have been made on reasoning about differential privacy at a system level in this paper we propose a formal framework to verify differential privacy in probabilistic systems with a metric on the states of a system we formalize differential privacy by the ratio of the probabilities in the distributions after the same labeled transitions of relevant states we explain how traditional differential privacy can be embedded in our framework and raise an infimum metric the least distance between two states while not violating differential privacy it is proven that the infimum metric is also a metric instance of differential privacy itself furthermore we propose a two level logic a privacy variant of the familiar hennessy milner logic to characterize differential privacy in our framework our results have close relations to probabilistic bisimilarity as well

a refined complexity analysis of degree anonymization in graphs motivated by a strongly growing interest in graph anonymization we study the np hard degree anonymity problem asking whether a graph can be made k anonymous by adding at most a given number of edges herein a graph is k anonymous if for every vertex in the graph there are at least k 1 other vertices of the same degree our algorithmic results shed light on the performance quality of a popular heuristic due to liu and terzi acm sigmod 2008 in particular we show that the heuristic provides optimal solutions if many edges need to be added based on this we develop a polynomial time data reduction yielding a polynomial size problem kernel for degree anonymity parameterized by the maximum vertex degree in terms of parameterized complexity analysis this result is in a sense tight since we also show that the problem is already np hard for h index three implying np hardness for smaller parameters such as average degree and degeneracy

lattice hydrodynamic modeling of two lane traffic flow with timid and aggressive driving behavior abstract in this paper a new two lane lattice hydrodynamic traffic flow model is proposed by considering the aggressive or timid characteristics of driver s behavior the effect of driver s characteristic on the stability of traffic flow is examined through linear stability analysis it is shown that for both the cases of lane changing or without lane changing the stability region significantly enlarges reduces as the proportion of aggressive timid drivers increases to describe the propagation behavior of a density wave near the critical point nonlinear analysis is conducted and mkdv equation representing kink antikink soliton is derived the effect of anticipation parameter with more aggressive timid drivers is also investigated and found that it has a positive negative effect on the stability of two lane traffic flow dynamics simulation results are found consistent with the theoretical findings which confirm that the driver s characteristics play a significant role in a two lane traffic system

combined effects of drivers disturbance risk preference heterogeneity and the nearest following vehicle headway on traffic flow instability analytical studies abstract driver s disturbance risk preference is defined as the driver s reaction degree to the disturbance which is a kind of the driver s attributes and can be expressed by the disturbance risk preference coefficient this paper proposes a new car following model and firstly attempts to analytically investigate the combined effects of drivers disturbance risk preference heterogeneity and the nearest following vehicle headway on traffic flow instability under some specific traffic scenarios solution of the model yields many insights including the following 1 when drivers disturbance risk preference increases from the following driver to the preceding driver traffic flow instability increases and the bigger the disturbance risk preference coefficient ratio of the preceding driver s coefficient to the following driver s coefficient the bigger the increasing effect and vice versa at this scenario the nearest following vehicle headway increases traffic flow instability 2 when drivers disturbance risk preference is homogeneous drivers disturbance risk preference and the nearest following vehicle headway have no effects on traffic flow instability 3 when drivers disturbance risk preference reduces from the following driver to the preceding driver for the general traffic situation traffic flow instability reduces and the smaller the disturbance risk preference coefficient ratio of the preceding driver s coefficient to the following driver s coefficient the bigger the reducing effect and vice versa at this scenario if the coefficient ratio reduces from the following to the preceding or is homogeneous the nearest following vehicle headway increases traffic flow instability otherwise the effects of the nearest following vehicle headway on traffic flow instability cannot be confirmed

proportional differential effects in traffic car following model system abstract traffic flow system s stability analysis can be seen as a typical control system problem which has three kinds of damping ratio properties from the viewpoint of control theory to discover the damping ratio characteristics of traffic flow system under sudden outer impulse firstly we proposed a new method to build the traffic flow model based on state space theory secondly we deduced one form of state transfer matrix from system closed loop transfer function reversely lastly we fully investigated the proportional differential effects in the traffic car following model system analytically and numerically for unsteady traffic flow system with the proportional differential pd term in order to suppress the traffic jam we derived a kind of decoupled delay feedback control algorithm which used h norm and the numerical simulation method to find the feedback gain k and delay time the traffic flow system s transient performance formula was presented with and without pd term and we found out the important impact of pd term on traffic flow system stability the numerical simulation results substantiate our theoretical and analytical results

on maximum entropy principle superstatistics power law distribution and renyi parameter abstract the equilibrium distributions of probabilities are derived on the basis of the maximum entropy principle mep for the renyi and tsallis entropies new s forms for the renyi and tsallis distribution functions are found which are normalised with corresponding entropies in contrast to the usual z forms normalised with partition functions z the superstatistics based on the gibbs distribution of energy fluctuations gives rise to a distribution function of the same structure that the renyi and tsallis distributions have the long range tail of the renyi distribution is the power law distribution with the exponent s expressed in terms of the free renyi parameter q as s 1 1 q the condition s 0 gives rise to the requirement q q can be uniquely determined with the use of a further extension of mep as the condition for maximum of the difference between the renyi and boltzmann entropies for the same power law distribution dependent on q it is found that the maximum is realized for q within the range from 0 25 to 0 5 and the exponent s varies from 1 3 to 2 in dependence on parameters of stochastic systems

nonextensive information theoretic kernels on measures positive definite kernels on probability measures have been recently applied to classification problems involving text images and other types of structured data some of these kernels are related to classic information theoretic quantities such as shannon s mutual information and the jensen shannon js divergence meanwhile there have been recent advances in nonextensive generalizations of shannon s information theory this paper bridges these two trends by introducing nonextensive information theoretic kernels on probability measures based on new js type divergences these new divergences result from extending the the two building blocks of the classical js divergence convexity and shannon s entropy the notion of convexity is extended to the wider concept of q convexity for which we prove a jensen q inequality based on this inequality we introduce jensen tsallis jt q differences a nonextensive generalization of the js divergence and define a k th order jt q difference between stochastic processes we then define a new family of nonextensive mutual information kernels which allow weights to be assigned to their arguments and which includes the boolean js and linear kernels as particular cases nonextensive string kernels are also defined that generalize the p spectrum kernel we illustrate the performance of these kernels on text categorization tasks in which documents are modeled both as bags of words and as sequences of characters

stochastic multi value cellular automata models for bicycle flow in this paper the stochastic randomization is introduced in two different multi value cellular automata ca models in order to model the bicycle flow it is shown that with the randomization effect considered the multiple states in the deterministic multi value ca models disappear and the unique flow density relations fundamental diagrams exist the fundamental diagrams the spacetime plots of the two models are studied in detail it is found that the transition from free flow to congested flow is smooth in one model while it is of second order in the other model the comparison of the results of the two models indicates that in the bicycle flow the priority of the movement should be given to slow bicycles in order to reach a larger maximum flow rate

intermittent unstable structures induced by incessant constant disturbances in the full velocity difference car following model abstract in this paper we study traffic flow patterns induced by incessant constant disturbances in the full velocity difference car following model it is found that intermittent unstable structures may occur in the convectively unstable traffic flow under certain situations a phenomenological explanation of the phenomenon is given the incessant constant disturbances mainly function to maintain the stationary oscillating structure while the stationary oscillating structure is not always stable the intermittent instability of it leads to the intermittent unstable structures the similarity of the stationary oscillating structure to the transition layer in the local cluster effect is pointed out the dependence of the phenomenon on the headway of the initially uniform traffic the safety distance x c the sensitivity parameters and and the noise term is also investigated

the car following model considering traffic jerk abstract based on optimal velocity car following model a new model considering traffic jerk is proposed to describe the jamming transition in traffic flow on a highway traffic jerk means the sudden braking and acceleration of vehicles which has a significant impact on traffic movement the nature of the model is researched by using linear and nonlinear analysis method a thermodynamic theory is formulated to describe the phase transition and critical phenomenon in traffic flow the time dependent ginzburg landau tdgl equation and the modified korteweg de vries mkdv equation are derived to describe the traffic flow near the critical point and the traffic jam in addition the connection between the tdgl and the mkdv equations are also given

kdv burgers equation in a new continuum model based on full velocity difference model considering anticipation effect abstract in this paper a new continuum model based on full velocity difference car following model is developed with the consideration of driver s anticipation effect by applying the linear stability theory the new model s linear stability is obtained through nonlinear analysis the kdv burgers equation is derived to describe the propagating behavior of traffic density wave near the neutral stability line numerical simulation shows that the new model possesses the local cluster and it is capable of explaining some particular traffic phenomena numerical results show that when considering the effects of anticipation the traffic jams can be suppressed efficiently the key improvement of this new model is that the anticipation effect can improve the stability of traffic flow

theoretical analysis of the density wave in a new continuum model and numerical simulation abstract considered the effect of traffic anticipation in the real world a new anticipation driving car following model ad cf was proposed by zheng et al based on ad cf model adopted an asymptotic approximation between the headway and density a new continuum model is presented in this paper the neutral stability condition is obtained by applying the linear stability theory additionally the korteweg de vries kdv equation is derived via nonlinear analysis to describe the propagating behavior of traffic density wave near the neutral stability line the numerical simulation and the analytical results show that the new continuum model is capable of explaining some particular traffic phenomena

a new lattice model accounting for multiple optimal current differences anticipation effect in two lane system abstract this paper extends a two lane lattice hydrodynamic traffic flow model to take into account the driver s anticipation effect in sensing the multiple optimal current differences based on the proposed model we derive analytically the effect of driver s anticipation of multiple optimal current differences on the instability of traffic dynamics the phase diagrams have been plotted and discussed that the stability region enhances with anticipation effect in sensing multiple optimal current differences through simulation it is found that the oscillation of density wave around critical density decreases with an increase in lattice number and anticipation time for transient and steady state the simulation results are in good agreement with the theoretical analysis which show that considering the driver s anticipation of multiple optimal current differences in two lane lattice model stabilizes the traffic flow and suppresses the traffic jam efficiently

generalized statistics framework for rate distortion theory abstract variational principles for the rate distortion rd theory in lossy compression are formulated within the ambit of the generalized nonextensive statistics of tsallis for values of the nonextensivity parameter satisfying 0 q 1 and q 1 alternating minimization numerical schemes to evaluate the nonextensive rd function are derived numerical simulations demonstrate the efficacy of generalized statistics rd models

hierarchical dirichlet processes we consider problems involving groups of data where each observation within a group is a draw from a mixture model and where it is desirable to share mixture components between groups we assume that the number of mixture components is unknown a priori and is to be inferred from the data in this setting it is natural to consider sets of dirichlet processes one for each group where the well known clustering property of the dirichlet process provides a nonparametric prior for the number of mixture components within each group given our desire to tie the mixture models in the various groups we consider a hierarchical model specifically one in which the base measure for the child dirichlet processes is itself distributed according to a dirichlet process such a base measure being discrete the child dirichlet processes necessarily share atoms thus as desired the mixture models in the different groups necessarily share mixture components we discuss representations of hierarchical dirichlet processes

solitons and kinks in a general car following model we study a general car following model of traffic flow on an infinitely long single lane road which assumes that a car s acceleration depends on time delayed values of its own speed the headway between it and the car ahead and the rate of change of headway but makes minimal assumptions about the functional form of that dependence we present a detailed characterization of the onset of linear instability in particular we find a specific limit on the delay time below which the marginal wave number at the onset of instability is zero and another specific limit on the delay time above which steady flow is always unstable crucially the threshold of absolute stability generally does not coincide with an inflection point of the steady state velocity function when the marginal perturbation at onset has wave number 0 we show that burgers and korteweg de vries kdv equations can be derived under the usual assumptions and that corrections to the kdv equation select a single member of the one parameter set of its one soliton solutions by driving a slow evolution of the soliton parameter while in previous models this selected soliton has always marked the threshold of a finite amplitude instability of linearly stable steady flow we find that it can alternatively be a stable small amplitude jam that occurs when steady flow is linearly unstable the model reduces to the usual modified korteweg de vries mkdv equation only in the special situation that the threshold of absolute stability coincides with an inflection point of the steady state velocity function in general near the threshold of absolute stability the model reduces instead to a kdv equation in the regime of small solitons while near an inflection point it reduces to a hayakawa nakanishi equation like the mkdv equation the hayakawa nakanishi equation admits a continuous family of kink solutions and the selection criterion arising from the corrections to this equation can be written down explicitly language en

study on the interval integration effect of vehicle s self delayed velocity on traffic stability in micro traffic modeling abstract a new car following model is proposed in this paper to study the interval integration effect of vehicle s self delayed velocity information on traffic flow the stability condition of the new model is derived through linear analysis and the result shows that the traffic stability can be improved when a longer interval of vehicle s self delayed velocity information is taken into account also it is revealed that the traffic information in the time interval which is far from the present time is more positive in stabilizing traffic flow comparing to the traffic information in the time interval which is close to the present time through nonlinear analysis the mkdv equation is derived to describe the propagation properties of density wave in the unstable region finally the theoretical results are confirmed by numerical simulation

a hierarchy of probabilistic system types we arrange various classes of probabilistic systems studied in the literature in an expressiveness hierarchy our expressiveness criterion is the existence of a system translation from the less expressive type into the more expressive type that preserves and reflects probabilistic bisimilarity we model the different system types as coalgebras of suitable behaviour functors and argue that the corresponding coalgebraic bisimilarity coincides with probabilistic bisimilarity for the classes for which the latter notion has been proposed in the literature the theory of coalgebras provides a unified framework for the presentation of the different classes and the system translations we needed to establish the hierarchy all these translations arise in a standard way from natural transformations between the two behaviour functors involved such a translation generally preserves coalgebraic bisimilarity we exploit a new result that under mild assumptions on the behaviour functors a system translation induced by a natural transformation with injective components also reflects bisimilarity

density waves in the full velocity difference model density waves are investigated in the full velocity difference model fvdm analytically and numerically by the use of nonlinear analysis the burgers korteweg de vries kdv and modified kdv equations are derived for the triangular shock wave the soliton wave and the kink antikink wave respectively appearing in the stable region out of the coexisting curve near the spinodal line and in the unstable region within the spinodal line it is shown numerically that the triangular shock wave and the soliton wave are determined by the initial perturbation configuration and different initial perturbations will produce different waveforms in the stable region or near the spinodal line

bifurcation analysis of traffic flow through an improved car following model considering the time delayed velocity difference abstract in this paper a new car following model with consideration of time delayed velocity difference is proposed to investigate the effect of time delayed velocity on traffic flow via bifurcation analysis based on this model the linear stability analysis is carried out and the corresponding stability condition is obtained then the hopf bifurcation analysis is performed in term of theoretical analysis and numerical simulation the result shows that there exist hopf bifurcation critical points and the position of the critical points is found to be located on the boundary of the instability region finally the influence of the delay time and sensitivity of velocity difference on hopf bifurcation is discussed respectively

nonlinear analysis of traffic flow on a gradient highway abstract we investigate the slope effects upon traffic flow on a single lane gradient uphill downhill highway analytically and numerically the stability condition neutral stability condition and instability condition are obtained by the use of linear stability theory it is found that stability of traffic flow on the gradient varies with the slopes the burgers korteweg de vries kdv and modified korteweg de vries mkdv equations are derived to describe the triangular shock waves soliton waves and kink antikink waves in the stable meta stable and unstable region respectively a series of simulations are carried out to reproduce the triangular shock waves kink antikink waves and soliton waves results show that amplitudes of the triangular shock waves and kink antikink waves vary with the slopes the soliton wave appears in an upward form when the average headway is less than the safety distance and a downward form when the average headway is more than the safety distance moreover both the kink antikink waves and the solitary waves propagate backwards the numerical simulation shows a good agreement with the analytical result

the effect of headway variation tendency on traffic flow modeling and stabilization abstract advanced communications technology enables us to obtain the headway variation tendency hvt of the next moment in a car following scenario to maximize the benefits of the new technology we developed a new traffic flow model that takes into consideration the effect of hvt first linear analysis method is used to derive the linear stability condition that determines whether the hvt can improve traffic system stability then using the reductive perturbation method a modified kdv mkdv equation is obtained and the kink antikink solutions are derived the phase diagram of driver sensitivity against equilibrium headway is also plotted by using the neutral stability line derived from linear analysis and the coexisting line derived from nonlinear analysis this diagram demonstrates that hvt does have the ability to improve the stability of traffic stream finally the effect of hvt is validated through numerical simulations where it is evident that the information of hvt can smooth the traffic stream and prevent the formation of traffic congestion

an examination of procedures for determining the number of clusters in a data set a monte carlo evaluation of 30 procedures for determining the number of clusters was conducted on artificial data sets which contained either 2 3 4 or 5 distinct nonoverlapping clusters to provide a variety of clustering solutions the data sets were analyzed by four hierarchical clustering methods external criterion measures indicated excellent recovery of the true cluster structure by the methods at the correct hierarchy level thus the clustering present in the data was quite strong the simulation results for the stopping rules revealed a wide range in their ability to determine the correct number of clusters in the data several procedures worked fairly well whereas others performed rather poorly thus the latter group of rules would appear to have little validity particularly for data sets containing distinct clusters applied researchers are urged to select one or more of the better criteria however users are cautioned that the performance of some of the criteria may be data dependent

density waves in the continuum analog of the full velocity difference model abstract a continuum version of the car following full velocity difference model fvdm is developed using a series expansion of the headway in terms of the density this continuum model obeys the equivalent stability criterion as its discrete counterpart and the burgers and korteweg de vries equations deriving from the analogous continuum model are equivalent to their counterparts from the transformed car following model

reliability of mobile processes with noisy channels to model the behavior of channels in real world mobile systems ying introduced an extension of the calculus by taking channel noise into account unfortunately this extension is not faithful in the sense that its semantics does not coincide with the standard one for the calculus in the noise free case in this paper we consider a simple variant of the calculus the asynchronous calculus a which has been used for modeling some concurrent systems with asynchronous communication to model these systems with noisy channels we propose a faithful extension of a called the a n calculus after giving a probabilistic transitional semantics of a n we introduce bisimilarity in a n and show that it is a partial input congruence if a specification of a system is described as a process p in a and we view the behavior of p in a n as an implementation of the specification then it is interesting to measure how far the behavior in a n is from that in a we thus introduce the notion of reliability degree which is based upon a new approximate bisimulation we find that bisimilar agents may have different reliability degrees and even the agent with the greatest reliability degree may not be satisfactory we thus appeal to shannon s noisy channel coding theorem and show that reliability degrees can be improved by employing coding techniques

an extended continuum model considering optimal velocity change with memory and numerical tests in this paper an extended continuum model of traffic flow is proposed with the consideration of optimal velocity changes with memory the new model s stability condition and kdv burgers equation considering the optimal velocities change with memory are deduced through linear stability theory and nonlinear analysis respectively numerical simulation is carried out to study the extended continuum model which explores how optimal velocity changes with memory affected velocity density and energy consumption numerical results show that when considering the effects of optimal velocity changes with memory the traffic jams can be suppressed efficiently both the memory step and sensitivity parameters of optimal velocity changes with memory will enhance the stability of traffic flow efficiently furthermore numerical results demonstrates that the effect of optimal velocity changes with memory can avoid the disadvantage of historical information which increases the stability of traffic flow on road and so it improve the traffic flow stability and minimize cars energy consumptions

bisimulation through probabilistic testing abstract we propose a language for testing concurrent processes and examine its strength in terms of the processes that are distinguished by a test by using probabilistic transition systems as the underlying semantic model we show how a testing algorithm can distinguish with a probability arbitrarily close to one between processes that are not bisimulation equivalent we also show a similar result in a slightly stronger form for a new process relation called 2 3 bisimulation which lies strictly between that of simulation and bisimulation finally the ultimately strength of the testing language is shown to identify a new process relation called probabilistic bisimulation which is strictly stronger than bisimulation

kdv burgers equation in the modified continuum model considering anticipation effect abstract the new continuum model mentioned in this paper is developed based on optimal velocity car following model which takes the drivers anticipation effect into account the critical condition for traffic flow is derived and nonlinear analysis shows density waves occur in traffic flow because of the small disturbance near the neutral stability line the kdv burgers equation is derived and one of the solutions is given numerical simulation is carried out to show the local cluster described by the model

algebraic laws for nondeterminism and concurrency since a nondeterministic and concurrent program may in general communicate repeatedly with its environment its meaning cannot be presented naturally as an input output function as is often done in the denotational approach to semantics in this paper an alternative is put forth first a definition is given of what it is for two programs or program parts to be equivalent for all observers then two program parts are said to be observation congruent if they are in all program contexts equivalent the behavior of a program part that is its meaning is defined to be its observation congruence class the paper demonstrates for a sequence of simple languages expressing finite terminating behaviors that in each case observation congruence can be axiomatized algebraically moreover with the addition of recursion and another simple extension the algebraic language described here becomes a calculus for writing and specifying concurrent programs and for proving their properties

thermodynamics and signatures of criticality in a network of neurons the activity of a neural network is defined by patterns of spiking and silence from the individual neurons because spikes are relatively sparse patterns of activity with increasing numbers of spikes are less probable but with more spikes the number of possible patterns increases this tradeoff between probability and numerosity is mathematically equivalent to the relationship between entropy and energy in statistical physics we construct this relationship for populations of up to n 160 neurons in a small patch of the vertebrate retina using a combination of direct and model based analyses of experiments on the response of this network to naturalistic movies we see signs of a thermodynamic limit where the entropy per neuron approaches a smooth function of the energy per neuron as n increases the form of this function corresponds to the distribution of activity being poised near an unusual kind of critical point we suggest further tests of criticality and give a brief discussion of its functional significance

a cellular automaton model based on empirical observations of a driver s oscillation behavior reproducing the findings from kerner s three phase traffic theory abstract in this paper we propose a new cellular automaton model based on the well known three phase traffic theory the model takes into account the mechanism of a driver s oscillation behavior obtained from engineering experiments in real traffic conditions this mechanism shows the inner competition between speed adaptation and distance adjustment effects the speed adaptation effect leads to synchronized flow whereas a pinch region emerges associated with the spontaneous occurrence of wide moving jams due to distance over adjustment numerical simulations are carried out both with periodic and with open boundary conditions in order to investigate the spatiotemporal features of traffic flow the results indicate that our model is able to reproduce the three distinct traffic phases and exhibit the four congested patterns upstream of an isolated on ramp which is in good consistency with the results predicted from the three phase theory

the influence of continuous historical velocity difference information on micro cooperative driving stability abstract in this paper a new micro cooperative driving car following model is proposed to investigate the effect of continuous historical velocity difference information on traffic stability the linear stability criterion of the new model is derived with linear stability theory and the results show that the unstable region in the headway sensitivity space will be shrunk by taking the continuous historical velocity difference information into account through nonlinear analysis the mkdv equation is derived to describe the traffic evolution behavior of the new model near the critical point via numerical simulations the theoretical analysis results are verified and the results indicate that the continuous historical velocity difference information can enhance the stability of traffic flow in the micro cooperative driving process

estimating the number of clusters in a data set via the gap statistic we propose a method the gap statistic for estimating the number of clusters groups in a set of data the technique uses the output of any clustering algorithm e g k means or hierarchical comparing the change in within cluster dispersion with that expected under an appropriate reference null distribution some theory is developed for the proposal and a simulation study shows that the gap statistic usually outperforms other methods that have been proposed in the literature

full velocity difference model for a car following theory in this paper we present a full velocity difference model for a car following theory based on the previous models in the literature to our knowledge the model is an improvement over the previous ones theoretically because it considers more aspects in car following process than others this point is verified by numerical simulation then we investigate the property of the model using both analytic and numerical methods and find that the model can describe the phase transition of traffic flow and estimate the evolution of traffic congestion

characteristics of traffic flow at a non signalized intersection in the framework of game theory abstract at a non signalized intersection some vehicles violate the traffic rules to pass the intersection as soon as possible these behaviors may cause many traffic conflicts even traffic accidents in this paper a simulation model is proposed to research the effects of these behaviors at a non signalized intersection vehicle s movement is simulated by the cellular automaton ca model the game theory is introduced for simulating the intersection dynamics two types of driver participate the game process cooperator c and defector d the cooperator obey the traffic rules but the defector does not a transition process may occur when the cooperator is waiting before the intersection the critical value of waiting time follows the weibull distribution one transition regime is found in the phase diagram the simulation results illustrate the applicability of the proposed model and reveal a number of interesting insights into the intersection management including that the existence of defectors is benefit for the capacity of intersection but also reduce the safety of intersection

jamming transitions and the effect of interruption probability in a lattice traffic flow model with passing abstract a new lattice hydrodynamic model is proposed by considering the interruption probability effect on traffic flow with passing and analyzed both theoretically and numerically from linear and non linear stability analysis the effect of interruption probability on the phase diagram is investigated and the condition of existence for kink antikink soliton solution of mkdv equation is derived the stable region is enhanced with interruption probability and the jamming transition occurs from uniform flow to kink flow through chaotic flow for higher and intermediate values of non interruption effect of passing it is also observed that there exists conventional jamming transition between uniform flow and kink flow for lower values of non interruption effect of passing numerical simulations are carried out and found in accordance with the theoretical findings which confirm that the effect of interruption probability plays an important role in stabilizing traffic flow when passing is allowed