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Predictability of real temporal networks

national Science Review 2020年第5期7卷 929-937页

作者： Disheng Tang Wenbo Du Louis Shekhtman Yijie Wang Shlomo Havlin Xianbin Cao Gang Yan School of Electronic and Information Engineering Beihang University Shanghai Institute of Intelligence Science and Technology Tongji University Network Science Institute Northeastern University Department of Physics Bar Ilan University CAS Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences National Engineering Laboratory of Big Data Application Technologies of Comprehensive Transportation School of Physics Science and Engineering Tongji University

Links in most real networks often change over time. Such temporality of links encodes the ordering and causality of interactions between nodes and has a profound effect on network dynamics and *** evidence has shown that the temporal nature of links in many real-world networks is not ***, it is challenging to predict temporal link patterns while considering the entanglement between topological and temporal link patterns. Here, we propose an entropy-rate-based framework, based on combined topological–temporal regularities, for quantifying the predictability of any temporal network. We apply our framework on various model networks, demonstrating that it indeed captures the intrinsic topological–temporal regularities whereas previous methods considered only temporal aspects. We also apply our framework on 18 real networks of different types and determine their predictability. Interestingly,we find that, for most real temporal networks, despite the greater complexity of predictability brought by the increase in dimension, the combined topological–temporal predictability is higher than the temporal predictability. Our results demonstrate the necessity for incorporating both temporal and topological aspects of networks in order to improve predictions of dynamical processes.

关键词： temporal network predictability network entropy predictive algorithm

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A new heuristics model of simulating pedestrian dynamics based on Voronoi diagram

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Chinese Physics B 2021年第1期30卷 623-639页

作者： Xin-Sen Wu Hao Yue Qiu-Mei Liu Xu Zhang Chun-Fu Shao Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport Ministry of TransportBeijing Jiaotong UniversityBeijing 100044China College of Civil Engineering and Architecture Henan University of TechnologyZhengzhou 450001China

A new heuristics model based on the Voronoi diagram is presented to simulate pedestrian dynamics with the noncrowded state, in which these mechanisms of preference demand evading and surpassing, microscopic anti-deadlock, and site-fine-tuning are considered. The preference demand describes the willingness determination of detouring or following other pedestrians. In the evading and surpassing mechanisms, in order to achieve a balance between avoiding conflicts and minimizing detour distances, a new pair of concepts: "allow-areas and denial-areas" are introduced to divide the feasible region for pedestrians detour behaviors, in which the direction and magnitude of detour velocity are determined.A microscopic anti-deadlock mechanism is inserted to avoid deadlock problem of the counter-directional pedestrian. A site-fine-tuning mechanism is introduced to describe the behavior of avoiding getting too close to the neighbors in pedestrian movement. The presented model is verified through multiple scenarios, including the uni-or bi-direction pedestrian flow in the corridor without obstacles, the uni-direction pedestrian flow in the corridor with obstacles, and the pedestrian evacuation from a room with single-exit. The simulation results show that the velocity–density relationship is consistent with empirical data. Some self-organizing phenomena, such as lanes formation and arching are observed in the *** pedestrians detour an obstacle, the avoiding area before the obstacle and the unoccupied area after the obstacle can be observed. When pedestrians evacuate through a bottleneck without panic, the fan-shaped crowd can be found, which is consistent with the actual observation. It is also found that the behavior of following others in an orderly manner is more conducive to the improvement of the overall movement efficiency when the crowd moves in a limited space.

关键词： pedestrian dynamics pedestrian simulation heuristics rules Voronoi diagram

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Volatility Transmission in Chinese Trucking Markets: An application Using BEKK, CCC and DCC-MGARCH Models

Volatility Transmission in Chinese Trucking Markets: An Appl...

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2020 IEEE International Conference on Artificial Intelligence and Computer applications, ICAICA 2020

作者： Xiao, Wei Xu, Chuan Liu, Hongling Liu, Xiaobo School of Transportation and Logistic National Engineering Laboratory of Integrated Transportation Big Data Application Technology Southwest Jiaotong University Chengdu Sichuan China School of Transportation and Logistics National United Engineering Laboratory of Integrated and Intelligent Transportation National Engineering Laboratory of Integrated Transportation Big Data Application Technology Southwest Jiaotong University Chengdu Sichuan China Southwest Jiaotong University Department of Transportation and Logistic Chengdu Sichuan China

ISBN: (数字)9781728170053

ISBN: (纸本)9781728170046

This paper aims at investigating whether volatility spillover effects exist among sub-segments in heavy truck trucking market of Southwest China based on trading data from online freight exchange (OFEX) platform, in which the sub-segments are classified by truck length, roughly as short bed sub-segment and long bed sub-segment. Model conditional correlations were modeled via the Multivariate Generalized Autoregressive Conditional Heteroskedasticity (MGARCH) model in the paper, followed by the analysis of volatility spillovers between sub-segments. Firstly, a Student's t distribution based BEKK (Baba, Engle, Kraft and Kroner) model is applied to analyzing the persistence effect as well as the volatility spillovers between sub-segments. Secondly, the change of interdependence degree between abovementioned markers is evaluated via the constant and dynamic conditional correlation models. We observed the constant long-term cross-volatility within the short bed sub-segment while multiple dynamic one-way volatility transmissions are observed, from the long bed sub-segment to the short bed sub-segment. In addition, an indication weight based on estimations of dynamic conditional correlation model is proposed to help marketing researchers to determine the weights of indices components when constructing trucking index in the future. © 2020 IEEE.

关键词： Trucks

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Optimal Scheduling of Single-Line Electric Buses with Battery Swapping 8

Optimal Scheduling of Single-Line Electric Buses with Batter...

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8th IEEE International Conference on Intelligent transportation engineering, ICITE 2023

作者： Guo, Yuyan Liu, Tao Institute of System Science and Engineering School of Transportation and Logistics Southwest Jiaotong University National Engineering Laboratory of Integrated Transportation Big Data Application Technology Chengdu China

ISBN: (纸本)9798350314212

With the advantages of zero emission and comfortable riding experience, battery-electric buses (BEBs) are widely adopted in public transit agencies as a green alternative to conventional diesel buses. Battery swapping technology is an efficient and promising charging technology to address the issues of battery range anxiety and long battery charging time. This study developed a two-stage optimization model to optimize the single-line battery-electric bus scheduling problem considering battery swapping. At the first stage, a bi-objective integer programming model is established to determine the minimum BEB fleet size, together with the BEB-to-trip assignment and battery swapping schedule. At the second stage, an integer linear programming model is formulated to determine the required minimum number of batteries. An e-constraint method is designed to investigate the trade-off between the required minimum fleet size and the number of back-up batteries. Finally, a real-world case study of a BEB line in Chengdu, China, is conducted to demonstrate the effectiveness of the optimization model and solution method. Sensitivity analyses are further conducted to understand the impacts of some key parameters, including battery capacity, number of trips, cycle time, and battery swapping time. The results show that battery capacity and cycle time have significant influences on BEB-to-trip assignment results and battery swapping schedule. © 2023 IEEE.

关键词： Sensitivity analysis

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Clause-level Relationship-aware Math Word Problems Solver

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Machine Intelligence Research 2022年第5期19卷 425-438页

作者： Chang-Yang Wu Xin Lin Zhen-Ya Huang Yu Yin Jia-Yu Liu Qi Liu Gang Zhou Anhui Province Key Laboratory of Big Data Analysis and Application School of Data ScienceUniversity of Science and Technology of ChinaHefei 230026China Institute of Artificial Intelligence Hefei Comprehensive National Science CenterHefei 230088China Laboratory of Mathematical Engineering and Advanced Computing Information Engineering UniversityZhengzhou 450001China

Automatically solving math word problems,which involves comprehension,cognition,and reasoning,is a crucial issue in artificial intelligence *** math word problem solvers mainly work on word-level relationship extraction and the generation of expression solutions while lacking consideration of the clause-level *** this end,inspired by the theory of two levels of process in comprehension,we propose a novel clause-level relationship-aware math solver(CLRSolver)to mimic the process of human comprehension from lower level to higher ***,in the lower-level processes,we split problems into clauses according to their natural division and learn their *** the higher-level processes,following human′s multi-view understanding of clause-level relationships,we first apply a CNN-based module to learn the dependency relationships between clauses from word relevance in a local ***,we propose two novel relationship-aware mechanisms to learn dependency relationships from the clause semantics in a global ***,we enhance the representation of clauses based on the learned clause-level dependency *** expression generation,we develop a tree-based decoder to generate the mathematical *** conduct extensive experiments on two datasets,where the results demonstrate the superiority of our framework.

关键词： Artificial intelligence(AI) artificial neural network(ANN) computational mathematics machine intelligence machine learning

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Study on Valid Travel Route Selection of Integrated Passenger transportation 4th

Study on Valid Travel Route Selection of Integrated Passenge...

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4th International Conference on Smart Vehicular technology, transportation, Communication and applications, VTCA 2021

作者： Yang, Yao Kan, Chenyan Chen, Dingjun School of Transportation and Logistics Southwest Jiaotong University Chengdu610031 China National and Local Joint Engineering Laboratory of Comprehensive Intelligent Transportation Southwest JiaoTong University Chengdu610031 China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Chengdu610031 China

ISBN: (纸本)9789811640384

With the vigorous development of the integrated transportation network, the choice of passenger travel route is becoming more and more diversified. Therefore, it is important to build the integrated transportation network by establishing the cost function of valid travel route to measure the route that passengers may choose. Based on passenger travel demand, an optimization model of valid route selection for integrated transportation network was established based on generalized travel cost. According to the characteristics of the model, an improved BFS algorithm based on dynamic updating generalized cost function and determining valid travel route by key nodes was designed to solve the valid route. Finally, a simulation was given to verify the effectiveness of the model and algorithm. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Cost functions

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Research on Equipment Management System of Railway Passenger Station Based on High-Precision Positioning 5th

Research on Equipment Management System of Railway Passenger...

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5th International Conference on Smart Vehicular technology, transportation, Communication and applications, VTCA 2022

作者： Li, Lexi Wang, Bozhou Liu, Zhen Ni, Shaoquan School of Transportation and Logistics Southwest Jiaotong University Sichuan Chengdu610031 China National and Local Joint Engineering Laboratory of Comprehensive Intelligent Transportation Southwest Jiaotong University Chengdu610031 China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Chengdu610031 China

ISBN: (纸本)9789819908479

The equipment management informatization and intelligentization in railway passenger stations is a significant component of the construction of intelligent stations. The current equipment management of railway passenger stations is slowly developing and backward in its approach. This paper studied the weaknesses of equipment management in railway passenger stations, conducted demand analysis, and proposed the development direction of equipment management in railway passenger stations with the support of theoretical basis and technical basis. The technical architecture of the high-precision positioning-based railway passenger station equipment management system was built from the terminal layer, application layer, service layer, data layer and perception layer, and four functional modules were designed for equipment management: equipment real-time dynamic trackment, full life-cycle management, equipment fault responsibility traceability, and incident response. The key technologies required for the construction of the system were studied, including Bayesian fusion-based equipment positioning technology with high accuracy and neural network-based remaining life prediction technology. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Informatization

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Analysis of Factors Influencing Driver Lane-Changing Intentions Based on a Naturalistic Trajectory data Set on Highways 24

Analysis of Factors Influencing Driver Lane-Changing Intenti...

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24th COTA International Conference of transportation Professionals: Resilient, Intelligent, Connected, and Lowcarbon Multimodal transportation, CICTP 2024

作者： Wang, Guangchen Lu, Guangquan Wang, Jinghua Liu, Miaomiao School of Transportation Science and Engineering Beihang Univ. Beijing China Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control National Engineering Laboratory for Comprehensive Transportation Big Data Application Technology Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang Univ. Beijing China

ISBN: (数字)9780784485484

ISBN: (纸本)9780784485484

Accurately analyzing and predicting driver lane-changing intentions is of paramount importance, as it significantly enhances the safety of self-driving vehicles in their decision-making processes, holding great promise for the future of intelligent transportation systems. This study extracts fundamental lane-changing characteristic parameters from the Next Generation Simulation (NGSIM) trajectory data set and employs Structural Equation Modeling (SEM) to construct a model that elucidates the factors influencing drivers’ lane-changing intentions. Furthermore, it provides insight into how lane-changing intentions are influenced by lane-changing behavior and explores the intricate connection between intention and associated risks. The results emphasize the substantial negative impact of the longitudinal speed difference between the self-vehicle and the preceding vehicle on lane-changing intentions. Additionally, the consideration of lane-changing risk plays a pivotal role in drivers’ decisions to engage in lane-changing behavior. These findings have significant implications for a deeper comprehension of lane-changing intentions, guiding lane-changing decisions, and enhancing overall traffic safety. © ASCE.

关键词： Autonomous vehicles

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The influence of continuous tunnel driving on high-speed rail drivers’ brain responses

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Tunnelling and Underground Space technology 2025年 163卷

作者： Guo, Zizheng Pang, Huishan Li, Guofa Li, Zhenning Xu, Hui Green, Paul School of Transportation and Logistics Southwest Jiaotong University Chengdu610031 China Intelligent Comprehensive Transportation Key Laboratory of Sichuan Province Chengdu610031 China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Chengdu610031 China College of Mechanical and Vehicle Engineering Chongqing University Chongqing400044 China State Key Laboratory of Internet of Things for Smart City University of Macau Macau999078 China China Railway Chengdu Group Co. Ltd. Chengdu610031 China and the Department of Industrial and Operations Engineering University of Michigan Ann ArborMI48109 United States

The impact of tunnels on driver performance is significant, yet it remains understudied in the context of high-speed rail. This study investigated the effects of continuous tunnel driving on high-speed rail drivers’ mental fatigue and brain functional connectivity using electroencephalography (EEG) and graph theory. Forty-two participants performed simulated driving tasks in continuous tunnel and plain scenarios. Results demonstrated that tunnel scenarios significantly elevated subjective fatigue and prolonged reaction times (p © 2025 Elsevier Ltd

关键词： Network theory (graphs)

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Multimodal or intermodal: greenhouse gas emissions in less than container load in China–Pakistan trade

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Environment Systems and Decisions 2023年第2期43卷 265-280页

作者： Shoukat, Rizwan School of Transportation and Logistics Southwest Jiaotong University Chengdu China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Chengdu China Lab of National United Engineering Laboratory of Integrated and Intelligent Transportation No. 111 North Second Ring Road Chengdu China

The most important factors to consider in transportation are the items being transported, the origin and destination locations, the length of the trip, the mode of transportation required (truck, train, plane, or ship), the shipping due dates, the costs, the level of security, regulation, and monitoring, and the costs. Specifically, the goal of this study is to determine the cost of, delivery time for, and greenhouse gas (GHG) emissions related to the import of less than container load (LCL) from China to Pakistan. For the multiobjective problem, we employed the mixed-integer linear programming (MILP) approach to construct it while keeping the supply and demand constraints in mind. We tackled the problem using a multiobjective evolutionary algorithm and developed Pareto optimal solutions that could trade-off cost, time, and GHG emission in order to achieve the best possible result. According to the data, which was received from one of Pakistan’s top logistics service companies, using intermodal transportation to carry a ten-tonne product from Shanghai in China to Kasur in Pakistan will cost 37 per cent more, take 14 per cent longer, and emit more greenhouse gases than using traditional multimodal transportation. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

关键词： Genetic algorithm GHG emission Intermodal transportation costs Less than container Multiobjective problem

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