A simulation model was proposed to investigate the relationship between train delays and passenger delays and to predict the dynamic passenger distribution in a large-scale rail transit network. It was assumed that th...A simulation model was proposed to investigate the relationship between train delays and passenger delays and to predict the dynamic passenger distribution in a large-scale rail transit network. It was assumed that the time varying original-destination demand and passenger path choice probability were given. Passengers were assumed not to change their destinations and travel paths after delay occurs. CapaciW constraints of train and queue rules of alighting and boarding were taken into account. By using the time-driven simulation, the states of passengers, trains and other facilities in the network were updated every time step. The proposed methodology was also tested in a real network, for demonstration. The results reveal that short train delay does not necessarily result in passenger delays, while, on the contrary, some passengers may get benefits from the short delay. However, large initial train delay may result in not only knock-on train and passenger delays along the same line, but also the passenger delays across the entire rail transit network.展开更多
Public transit planning is a user-oriented problem, respectful of financial issues and involves different stakeholders such as the general public, the transportation provider and the local government. One of the main ...Public transit planning is a user-oriented problem, respectful of financial issues and involves different stakeholders such as the general public, the transportation provider and the local government. One of the main components of public transit planning is the transit network design (TND) problem. This research is an attempt to perform transit network design and analysis in the city of Sanandaj, Iran using the capabilities of GIS and Honeybee algorithm. Objectives of this study are formulating a multi-objective model of the TND problem, developing a GIS-based procedure for solving the TND problem and examination of the solutions using artificial metaheuristic methods such as honeybee algorithm. The transit network design approach in this research, aims to reduce the walking distance, the total travel distance and the total number of stops needed for a suitable transit service in Sanandaj, Iran. One of the contributions of this research is developing a transit network design with utilizing a spectrum of GIS software modelling functionalities and using the abilities of the artificial intelligence in modelling and assessment of the transit network.展开更多
The public transit system in Sanandaj has been under review and modification for the last several years. The goal is to reduce the traffic congestion and the share of private car usage in the city and increase the ver...The public transit system in Sanandaj has been under review and modification for the last several years. The goal is to reduce the traffic congestion and the share of private car usage in the city and increase the very low share of the public transit. The bus routes in Sanandaj are not connected. There is no connected transit network with the ability to transfer between the routes in locations outside of the downtown terminal. The routes mostly connect the downtown core directly to the peripheries without providing travel options for passengers between peripheries. Although there has been some improvement in the transit system, lack of service in many populated districts of Sanandaj and town nearby makes the transit system unpopular and unreliable. This research is an attempt to provide solutions for the transit network design (TND) problem in Sanandaj using the capabilities of GIS and artificial intelligence methods. GIS offers several tools that enable the decision-makers to investigate the spatial correlations between different features. One of the contributions of this research is developing a transit network design with utilizing a spectrum of GIS software modeling functionalities. The visual ability of GIS is used to generate TNDs. Many studies focus on artificial intelligence as the main method to generate the TNDs, but the focus of this research is to combine GIS and artificial intelligence capabilities in order to generate a multi-objective GIS-based procedure to construct different bus network designs and explore and evaluate them to find the suitable transit network alternative.展开更多
Current urban rail transit has become a major mode of transportation, and passenger is an important factor of urban rail transport, so this article is based on passenger and the degree of the road network structure, c...Current urban rail transit has become a major mode of transportation, and passenger is an important factor of urban rail transport, so this article is based on passenger and the degree of the road network structure, calculating the point intensity of stations of urban rail transit, and then reaching a station importance by integrating many point intensities in a survey cycle time, and getting the station importance of urban rail transit network through concrete examples.展开更多
This paper discusses the control strategy for energy management in railway transit network with wayside(substation)supercapacitor(SC)energy storage system(ESS).Firstly,the structure of the wayside energy storage syste...This paper discusses the control strategy for energy management in railway transit network with wayside(substation)supercapacitor(SC)energy storage system(ESS).Firstly,the structure of the wayside energy storage system is introduced.Secondly,the model of energy storage system is built and the control strategy is described.Thirdly,in order to estimate the required energy storage system,a useful method is proposed to predict the instantaneous regenerative energy magnitude which is delivered to each substation.Finally,the ESS configuration for each substation is determined.A simplified mathematical model of the whole metro network is established and the main features of the control strategy are developed.Numerical simulations show the efficacy of suggested control strategy and the energy saving obtained for railway transit network.展开更多
Understanding the interdependent nature of multimodal public transit networks(PTNs)is vital for ensuring the resilience and robustness of transportation systems.However,previous studies have predominantly focused on a...Understanding the interdependent nature of multimodal public transit networks(PTNs)is vital for ensuring the resilience and robustness of transportation systems.However,previous studies have predominantly focused on assessing the vulnerability and characteristics of single-mode PTNs,neglecting the impacts of heterogeneous disturbances and shifts in travel behavior within multimodal PTNs.Therefore,this study introduces a novel resilience assessment framework that comprehensively analyzes the coupling mechanism,structural and functional characteristics of bus-rail transit networks(BRTNs).In this framework,a network performance metric is proposed by considering the passengers’travel behaviors under various disturbances.Additionally,stations and subnetworks are classified using the k-means algorithm and resilience metric by simulating various disturbances occurring at each station or subnetwork.The proposed framework is validated via a case study of a BRTN in Beijing,China.Results indicate that the rail transit network(RTN)plays a crucial role in maintaining network function and resisting external disturbances in the interdependent BRTN.Furthermore,the coupling interactions between the RTN and bus transit network(BTN)exhibit distinct characteristics under infrastructure component disruption and functional disruption.These findings provide valuable insights into emergency management for PTNs and understanding the coupling relationship between BTN and RTN.展开更多
A bus network design problem in a suburban area of Hong Kong is studied.The objective is to minimize the weighted sum of the number of transfers and the total travel time of passengers by restructuring bus routes and ...A bus network design problem in a suburban area of Hong Kong is studied.The objective is to minimize the weighted sum of the number of transfers and the total travel time of passengers by restructuring bus routes and determining new frequencies.A mixed integer optimization model is developed and was solved by a Hybrid Enhanced Artificial Bee Colony algorithm(HEABC).A case study was conducted to investigate the effects of different design parameters,including the total number of bus routes available,the maximum route duration within the study area and the maximum allowable number of bus routes that originated from each terminal.The model and results are useful for improving bus service policies.展开更多
Synchronization of networked phase oscillators depends essentially on the correlation between the topological structure of the graph and the dynamical property of the elements. We propose the concept of ＇reduced freq...Synchronization of networked phase oscillators depends essentially on the correlation between the topological structure of the graph and the dynamical property of the elements. We propose the concept of ＇reduced frequency＇, a measure which can quantify natural frequencies of each pair of oscillators. Then we introduce an evolving network whose linking rules are controlled by its own dynamical property. The simulation results indicate that when the linking probability positively correlates with the reduced frequency, the network undergoes a first-order phase transition. Meanwhile, we discuss the circumstance under which an explosive synchronization can be ignited. The numerical results show that the peculiar butterfly shape correlation between frequencies and degrees of the nodes contributes to an explosive synchronization transition.展开更多
We present a percolation process in which the classical Erdts-Rtnyi （ER） random evolutionary network is intervened by the product rule （PR） from some moment to. The parameter to is continuously tunable over the re...We present a percolation process in which the classical Erdts-Rtnyi （ER） random evolutionary network is intervened by the product rule （PR） from some moment to. The parameter to is continuously tunable over the real interval [0, 1]. This model becomes the random network under the Achlioptas process at to = 0 and the ER network at to = 1. For the percolation process at to≤1, we introduce a relatively slow-growing point, after which the largest cluster begins growing faster than that in the ER model. A weakly discontinuous transition is generated in the percolation process at to ≤ 0.5. We take the relatively slow-growing point as the lower pseudotransition point and the maximum gap point of the order parameter as the upper pseudotransition point. The critical point can be approximately predicted by each fitting function of the two points about to. This contributes to understanding the rapid mergence of the large clusters at the critical point. The numerical simulations indicate that the lower pseudotransition point and the upper pseudotransition point are equal in the thermodynamic limit. When to 〉 0.5, the percolation processes generate a continuous transition. The scaling analyses of several quantities are presented, including the relatively slow-growing point, the duration of the relatively slow-growing process, as well as the relatively maximum strength between the percolation percolation at to 〈 1 and the ER network about different to. The presented mechanism can be viewed as a two-stage percolation process that has many potential applications in the growth processes of real networks.展开更多
The significance of network structure indicators for the planning and management of conventional public transit is widely acknowledged.In order to improve and enrich the conventional public transit assessment system,t...The significance of network structure indicators for the planning and management of conventional public transit is widely acknowledged.In order to improve and enrich the conventional public transit assessment system,two network structure indicators are proposed.Firstly,according to the obvious defects lying in the traditional no-linear coefficient,the realistic no-linear coefficient γRNL,a modified no-linear coefficient indicator,is put forward,which takes into account the effects of barriers in a city.Secondly,to cover the gap of an indicator which can reflect the coverage homogeneity of a transit network,the length dimension LDis proposed on the basis of Fractal Theory.Finally,a case study is applied to verify the validity and practicability of the two indicators in problem diagnosis using regression analysis.The results validate that γRNLcan evaluate the detour of bus lines more reasonably than the previous no-linear coefficient because it reflects the layout of bus lines,and LDcan represent the rate of change of the network density,adding a new member to the scheme of network structure indicators for public transit.展开更多
Phase transitions widely exist in nature and occur when some control parameters are changed. In neural systems, their macroscopic states are represented by the activity states of neuron populations, and phase transiti...Phase transitions widely exist in nature and occur when some control parameters are changed. In neural systems, their macroscopic states are represented by the activity states of neuron populations, and phase transitions between different activity states are closely related to corresponding functions in the brain. In particular, phase transitions to some rhythmic synchronous firing states play significant roles on diverse brain functions and disfunctions, such as encoding rhythmical external stimuli, epileptic seizure, etc. However, in previous studies, phase transitions in neuronal networks are almost driven by network parameters （e.g., external stimuli）, and there has been no investigation about the transitions between typical activity states of neuronal networks in a self-organized way by applying plastic connection weights. In this paper, we discuss phase transitions in electrically coupled and lattice-based small-world neuronal networks （LBSW networks） under spike-timing-dependent plasticity （STDP）. By applying STDP on all electrical synapses, various known and novel phase transitions could emerge in LBSW networks, particularly, the phenomenon of self-organized phase transitions （SOPTs）： repeated transitions between synchronous and asynchronous firing states. We further explore the mechanics generating SOPTs on the basis of synaptic weight dynamics.展开更多
The dynamic characteristic of complex network failure and recovery is one of the main research topics in complex networks. Real world systems such as traffic jams and Internet recovery could be described by the comple...The dynamic characteristic of complex network failure and recovery is one of the main research topics in complex networks. Real world systems such as traffic jams and Internet recovery could be described by the complex network theory. We propose a model to study the recovery process in complex networks. Two different recovery mechanisms are considered in three kinds of networks： external recovery and internal recovery. By simulating the process of the nodes recovery in networks, it is found that the system exhibits the feature of first-order phase transition only when the external recovery is considered. Internal recovery cannot induce such a kind of transitions. As external recovery and internal recovery coexist on networks, the systems will retain the most efficient part of external recovery and internal recovery. Meanwhile, a hysteresis could be observed when increasing or decreasing the failure probability. Finally, a largest degree node protection strategy is proposed for improving the robustness of networks.展开更多
We study the percolation transition in a one-species cluster aggregation network model, in which the parameter α describes the suppression on the cluster sizes. It is found that the model can exhibit four types of pe...We study the percolation transition in a one-species cluster aggregation network model, in which the parameter α describes the suppression on the cluster sizes. It is found that the model can exhibit four types of percolation transitions, two continuous percolation transitions and two discontinuous ones. Continuous and discontinuous percolation transitions can be distinguished from each other by the largest single jump. Two types of continuous percolation transitions show different behaviors in the time gap. Two types of discontinuous percolation transitions are different in the time evolution of the cluster size distribution. Moreover, we also find that the time gap may also be a measure to distinguish different discontinuous percolations in this model.展开更多
We numerically study the effect of the channel noise on the spiking synchronization of a scale-free Hodgkin-Huxley neuron network with time delays. It is found that the time delay can induce synchronization transition...We numerically study the effect of the channel noise on the spiking synchronization of a scale-free Hodgkin-Huxley neuron network with time delays. It is found that the time delay can induce synchronization transitions at an intermediate and proper channel noise intensity, and the synchronization transitions become strongest when the channel noise intensity is optimal. The neurons can also exhibit synchronization transitions as the channel noise intensity is varied, and this phenomenon is enhanced at around the time delays that can induce the synchronization transitions. It is also found that the synchronization transitions induced by the channel noise are dependent on the coupling strength and the network average degree, and there is an optimal coupling strength or network average degree with which the synchronization transitions become strongest. These results show that by inducing synchronization transitions, the channel noise has a big regulation effect on the synchronization of the neuronal network. These findings could find potential implications for the information transmission in neural systems.展开更多
In this paper, an artificial neural network model is adopted to study the glass transition temperature of polymers. In our artificial neural networks, the input nodes are the characteristic ratio C-infinity, the avera...In this paper, an artificial neural network model is adopted to study the glass transition temperature of polymers. In our artificial neural networks, the input nodes are the characteristic ratio C-infinity, the average molecular weight M-e between entanglement points and the molecular weight M-mon of repeating unit. The output node is the glass transition temperature T-g, and the number of the hidden layer is 6. We found that the artificial neural network simulations are accurate in predicting the outcome for polymers for which it is not trained. The maximum relative error for predicting of the glass transition temperature is 3.47%, and the overall average error is only 2.27%. Artificial neural networks may provide some new ideas to investigate other properties of the polymers.展开更多
We investigate the phase transitions behavior of the majority-vote model with noise on a topology that consists of two coupled random networks. A parameter p is used to measure the degree of modularity, defined as the...We investigate the phase transitions behavior of the majority-vote model with noise on a topology that consists of two coupled random networks. A parameter p is used to measure the degree of modularity, defined as the ratio of intermodular to intramodular connectivity. For the networks of strong modularity （small p）, as the level of noise f increases, the system undergoes successively two transitions at two distinct critical noises, fc1 and fc2. The first transition is a discontinuous jump from a coexistence state of parallel and antiparallel order to a state that only parallel order survives, and the second one is continuous that separates the ordered state from a disordered state. As the network modularity worsens, fc1 becomes smaller and fc1 does not change, such that the antiparallel ordered state will vanish if p is larger than a critical value of pc. We propose a mean-field theory to explain the simulation results.展开更多
Based on the Ising spin, the phase transition on fractal scale-free networks with tree-like skeletons is studied, where the loops are generated by local links. The degree distribution of the tree-like skeleton satisfi...Based on the Ising spin, the phase transition on fractal scale-free networks with tree-like skeletons is studied, where the loops are generated by local links. The degree distribution of the tree-like skeleton satisfies the power-law form P（k）～ k^-δ.It is found that when δ≥3, the renormalized scale-free network will have the same degree distribution as the original network. For a special case of δ = 4.5, a ferromagnetic to paramagnetic transition is found and the critical temperature is determined by the box-covering renormalization method. By keeping the structure of the fractal scale-free network constant, the numerical relationship between the critical temperature and the network size is found, which is the form of power law.展开更多
基金Project(51008229)supported by the National Natural Science Foundation of ChinaProject supported by Key Laboratory of Road and Traffic Engineering of Tongji University,China
文摘A simulation model was proposed to investigate the relationship between train delays and passenger delays and to predict the dynamic passenger distribution in a large-scale rail transit network. It was assumed that the time varying original-destination demand and passenger path choice probability were given. Passengers were assumed not to change their destinations and travel paths after delay occurs. CapaciW constraints of train and queue rules of alighting and boarding were taken into account. By using the time-driven simulation, the states of passengers, trains and other facilities in the network were updated every time step. The proposed methodology was also tested in a real network, for demonstration. The results reveal that short train delay does not necessarily result in passenger delays, while, on the contrary, some passengers may get benefits from the short delay. However, large initial train delay may result in not only knock-on train and passenger delays along the same line, but also the passenger delays across the entire rail transit network.
文摘Public transit planning is a user-oriented problem, respectful of financial issues and involves different stakeholders such as the general public, the transportation provider and the local government. One of the main components of public transit planning is the transit network design (TND) problem. This research is an attempt to perform transit network design and analysis in the city of Sanandaj, Iran using the capabilities of GIS and Honeybee algorithm. Objectives of this study are formulating a multi-objective model of the TND problem, developing a GIS-based procedure for solving the TND problem and examination of the solutions using artificial metaheuristic methods such as honeybee algorithm. The transit network design approach in this research, aims to reduce the walking distance, the total travel distance and the total number of stops needed for a suitable transit service in Sanandaj, Iran. One of the contributions of this research is developing a transit network design with utilizing a spectrum of GIS software modelling functionalities and using the abilities of the artificial intelligence in modelling and assessment of the transit network.
文摘The public transit system in Sanandaj has been under review and modification for the last several years. The goal is to reduce the traffic congestion and the share of private car usage in the city and increase the very low share of the public transit. The bus routes in Sanandaj are not connected. There is no connected transit network with the ability to transfer between the routes in locations outside of the downtown terminal. The routes mostly connect the downtown core directly to the peripheries without providing travel options for passengers between peripheries. Although there has been some improvement in the transit system, lack of service in many populated districts of Sanandaj and town nearby makes the transit system unpopular and unreliable. This research is an attempt to provide solutions for the transit network design (TND) problem in Sanandaj using the capabilities of GIS and artificial intelligence methods. GIS offers several tools that enable the decision-makers to investigate the spatial correlations between different features. One of the contributions of this research is developing a transit network design with utilizing a spectrum of GIS software modeling functionalities. The visual ability of GIS is used to generate TNDs. Many studies focus on artificial intelligence as the main method to generate the TNDs, but the focus of this research is to combine GIS and artificial intelligence capabilities in order to generate a multi-objective GIS-based procedure to construct different bus network designs and explore and evaluate them to find the suitable transit network alternative.
文摘Current urban rail transit has become a major mode of transportation, and passenger is an important factor of urban rail transport, so this article is based on passenger and the degree of the road network structure, calculating the point intensity of stations of urban rail transit, and then reaching a station importance by integrating many point intensities in a survey cycle time, and getting the station importance of urban rail transit network through concrete examples.
文摘This paper discusses the control strategy for energy management in railway transit network with wayside(substation)supercapacitor(SC)energy storage system(ESS).Firstly,the structure of the wayside energy storage system is introduced.Secondly,the model of energy storage system is built and the control strategy is described.Thirdly,in order to estimate the required energy storage system,a useful method is proposed to predict the instantaneous regenerative energy magnitude which is delivered to each substation.Finally,the ESS configuration for each substation is determined.A simplified mathematical model of the whole metro network is established and the main features of the control strategy are developed.Numerical simulations show the efficacy of suggested control strategy and the energy saving obtained for railway transit network.
基金supported by the National Key R&D Program of China(2021YFB1600100).
文摘Understanding the interdependent nature of multimodal public transit networks(PTNs)is vital for ensuring the resilience and robustness of transportation systems.However,previous studies have predominantly focused on assessing the vulnerability and characteristics of single-mode PTNs,neglecting the impacts of heterogeneous disturbances and shifts in travel behavior within multimodal PTNs.Therefore,this study introduces a novel resilience assessment framework that comprehensively analyzes the coupling mechanism,structural and functional characteristics of bus-rail transit networks(BRTNs).In this framework,a network performance metric is proposed by considering the passengers’travel behaviors under various disturbances.Additionally,stations and subnetworks are classified using the k-means algorithm and resilience metric by simulating various disturbances occurring at each station or subnetwork.The proposed framework is validated via a case study of a BRTN in Beijing,China.Results indicate that the rail transit network(RTN)plays a crucial role in maintaining network function and resisting external disturbances in the interdependent BRTN.Furthermore,the coupling interactions between the RTN and bus transit network(BTN)exhibit distinct characteristics under infrastructure component disruption and functional disruption.These findings provide valuable insights into emergency management for PTNs and understanding the coupling relationship between BTN and RTN.
基金supported by a grant from the Central Policy Unit of the Government of the Hong Kong Special Administrative Region and the Research Grants Council of the Hong Kong Special Administrative Region,China(HKU7026-PPR-12)a grant(201011159026)from the University Research Committee,a grant from the National Natural Science Foundation of China(71271183)a Research Postgraduate Studentship from the University of Hong Kong.
文摘A bus network design problem in a suburban area of Hong Kong is studied.The objective is to minimize the weighted sum of the number of transfers and the total travel time of passengers by restructuring bus routes and determining new frequencies.A mixed integer optimization model is developed and was solved by a Hybrid Enhanced Artificial Bee Colony algorithm(HEABC).A case study was conducted to investigate the effects of different design parameters,including the total number of bus routes available,the maximum route duration within the study area and the maximum allowable number of bus routes that originated from each terminal.The model and results are useful for improving bus service policies.
基金Supported by the Open Fund from Guangxi Colleges and Universities Key Laboratory of Complex System Optimization and Big Data Processing under Grant No 2015CSOBDP0101the National Natural Science Foundation of China under Grant No11162019
文摘Synchronization of networked phase oscillators depends essentially on the correlation between the topological structure of the graph and the dynamical property of the elements. We propose the concept of ＇reduced frequency＇, a measure which can quantify natural frequencies of each pair of oscillators. Then we introduce an evolving network whose linking rules are controlled by its own dynamical property. The simulation results indicate that when the linking probability positively correlates with the reduced frequency, the network undergoes a first-order phase transition. Meanwhile, we discuss the circumstance under which an explosive synchronization can be ignited. The numerical results show that the peculiar butterfly shape correlation between frequencies and degrees of the nodes contributes to an explosive synchronization transition.
基金supported by the National Natural Science Foundation of China(Grant Nos.61172115 and 60872029)the High Technology Research and DevelopmentProgram of China(Grant No.2008AA01Z206)+2 种基金the Aeronautics Foundation of China(Grant No.20100180003)the Fundamental Research Funds for theCentral Universities,China(Grant No.ZYGX2009J037)Project 9140A07030513DZ02098,China
文摘We present a percolation process in which the classical Erdts-Rtnyi （ER） random evolutionary network is intervened by the product rule （PR） from some moment to. The parameter to is continuously tunable over the real interval [0, 1]. This model becomes the random network under the Achlioptas process at to = 0 and the ER network at to = 1. For the percolation process at to≤1, we introduce a relatively slow-growing point, after which the largest cluster begins growing faster than that in the ER model. A weakly discontinuous transition is generated in the percolation process at to ≤ 0.5. We take the relatively slow-growing point as the lower pseudotransition point and the maximum gap point of the order parameter as the upper pseudotransition point. The critical point can be approximately predicted by each fitting function of the two points about to. This contributes to understanding the rapid mergence of the large clusters at the critical point. The numerical simulations indicate that the lower pseudotransition point and the upper pseudotransition point are equal in the thermodynamic limit. When to 〉 0.5, the percolation processes generate a continuous transition. The scaling analyses of several quantities are presented, including the relatively slow-growing point, the duration of the relatively slow-growing process, as well as the relatively maximum strength between the percolation percolation at to 〈 1 and the ER network about different to. The presented mechanism can be viewed as a two-stage percolation process that has many potential applications in the growth processes of real networks.
基金Sponsored by the National High Technology Research and Development Program of China(Grant No.214AA110303)
文摘The significance of network structure indicators for the planning and management of conventional public transit is widely acknowledged.In order to improve and enrich the conventional public transit assessment system,two network structure indicators are proposed.Firstly,according to the obvious defects lying in the traditional no-linear coefficient,the realistic no-linear coefficient γRNL,a modified no-linear coefficient indicator,is put forward,which takes into account the effects of barriers in a city.Secondly,to cover the gap of an indicator which can reflect the coverage homogeneity of a transit network,the length dimension LDis proposed on the basis of Fractal Theory.Finally,a case study is applied to verify the validity and practicability of the two indicators in problem diagnosis using regression analysis.The results validate that γRNLcan evaluate the detour of bus lines more reasonably than the previous no-linear coefficient because it reflects the layout of bus lines,and LDcan represent the rate of change of the network density,adding a new member to the scheme of network structure indicators for public transit.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.11135001 and 11174034)
文摘Phase transitions widely exist in nature and occur when some control parameters are changed. In neural systems, their macroscopic states are represented by the activity states of neuron populations, and phase transitions between different activity states are closely related to corresponding functions in the brain. In particular, phase transitions to some rhythmic synchronous firing states play significant roles on diverse brain functions and disfunctions, such as encoding rhythmical external stimuli, epileptic seizure, etc. However, in previous studies, phase transitions in neuronal networks are almost driven by network parameters （e.g., external stimuli）, and there has been no investigation about the transitions between typical activity states of neuronal networks in a self-organized way by applying plastic connection weights. In this paper, we discuss phase transitions in electrically coupled and lattice-based small-world neuronal networks （LBSW networks） under spike-timing-dependent plasticity （STDP）. By applying STDP on all electrical synapses, various known and novel phase transitions could emerge in LBSW networks, particularly, the phenomenon of self-organized phase transitions （SOPTs）： repeated transitions between synchronous and asynchronous firing states. We further explore the mechanics generating SOPTs on the basis of synaptic weight dynamics.
基金Supported by the National Natural Science foundation of China under Grant No 11474221
文摘The dynamic characteristic of complex network failure and recovery is one of the main research topics in complex networks. Real world systems such as traffic jams and Internet recovery could be described by the complex network theory. We propose a model to study the recovery process in complex networks. Two different recovery mechanisms are considered in three kinds of networks： external recovery and internal recovery. By simulating the process of the nodes recovery in networks, it is found that the system exhibits the feature of first-order phase transition only when the external recovery is considered. Internal recovery cannot induce such a kind of transitions. As external recovery and internal recovery coexist on networks, the systems will retain the most efficient part of external recovery and internal recovery. Meanwhile, a hysteresis could be observed when increasing or decreasing the failure probability. Finally, a largest degree node protection strategy is proposed for improving the robustness of networks.
基金Supported by the National Natural Science Foundation of China under Grant Nos 11575036 and 11505016
文摘We study the percolation transition in a one-species cluster aggregation network model, in which the parameter α describes the suppression on the cluster sizes. It is found that the model can exhibit four types of percolation transitions, two continuous percolation transitions and two discontinuous ones. Continuous and discontinuous percolation transitions can be distinguished from each other by the largest single jump. Two types of continuous percolation transitions show different behaviors in the time gap. Two types of discontinuous percolation transitions are different in the time evolution of the cluster size distribution. Moreover, we also find that the time gap may also be a measure to distinguish different discontinuous percolations in this model.
基金supported by the Natural Science Foundation of Shandong Province of China(Grant No.ZR2012AM013)
文摘We numerically study the effect of the channel noise on the spiking synchronization of a scale-free Hodgkin-Huxley neuron network with time delays. It is found that the time delay can induce synchronization transitions at an intermediate and proper channel noise intensity, and the synchronization transitions become strongest when the channel noise intensity is optimal. The neurons can also exhibit synchronization transitions as the channel noise intensity is varied, and this phenomenon is enhanced at around the time delays that can induce the synchronization transitions. It is also found that the synchronization transitions induced by the channel noise are dependent on the coupling strength and the network average degree, and there is an optimal coupling strength or network average degree with which the synchronization transitions become strongest. These results show that by inducing synchronization transitions, the channel noise has a big regulation effect on the synchronization of the neuronal network. These findings could find potential implications for the information transmission in neural systems.
基金This research was financially supported by NSFC (No. 29874012) and the Special Funds for Major State Basic Research Projects (95-12 and G1999064800).
文摘In this paper, an artificial neural network model is adopted to study the glass transition temperature of polymers. In our artificial neural networks, the input nodes are the characteristic ratio C-infinity, the average molecular weight M-e between entanglement points and the molecular weight M-mon of repeating unit. The output node is the glass transition temperature T-g, and the number of the hidden layer is 6. We found that the artificial neural network simulations are accurate in predicting the outcome for polymers for which it is not trained. The maximum relative error for predicting of the glass transition temperature is 3.47%, and the overall average error is only 2.27%. Artificial neural networks may provide some new ideas to investigate other properties of the polymers.
基金Supported by the National Natural Science Foundation of China under Grant Nos 11405001,11205002 and 11475003
文摘We investigate the phase transitions behavior of the majority-vote model with noise on a topology that consists of two coupled random networks. A parameter p is used to measure the degree of modularity, defined as the ratio of intermodular to intramodular connectivity. For the networks of strong modularity （small p）, as the level of noise f increases, the system undergoes successively two transitions at two distinct critical noises, fc1 and fc2. The first transition is a discontinuous jump from a coexistence state of parallel and antiparallel order to a state that only parallel order survives, and the second one is continuous that separates the ordered state from a disordered state. As the network modularity worsens, fc1 becomes smaller and fc1 does not change, such that the antiparallel ordered state will vanish if p is larger than a critical value of pc. We propose a mean-field theory to explain the simulation results.
基金Project supported by the Natural Science Foundation of Shandong Province,China(Grant No.ZR2014EL002)
文摘Based on the Ising spin, the phase transition on fractal scale-free networks with tree-like skeletons is studied, where the loops are generated by local links. The degree distribution of the tree-like skeleton satisfies the power-law form P（k）～ k^-δ.It is found that when δ≥3, the renormalized scale-free network will have the same degree distribution as the original network. For a special case of δ = 4.5, a ferromagnetic to paramagnetic transition is found and the critical temperature is determined by the box-covering renormalization method. By keeping the structure of the fractal scale-free network constant, the numerical relationship between the critical temperature and the network size is found, which is the form of power law.
