Article
Physics, Multidisciplinary
Zhenyuan Fang, Shichao Zhu, Xin Fu, Fang Liu, Helai Huang, Jinjun Tang
Summary: This study proposes a Copula-based approach to analyze the correlation relationship among traffic flow parameters and model their multivariate distribution at urban road intersections. By constructing bivariate joint distribution models using different Copula functions, the study finds that this approach can accurately construct distributions and reproduce the dependence structure between variables.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2022)
Article
Physics, Multidisciplinary
Chintaman Santosh Bari, Satish Chandra, Ashish Dhamaniya
Summary: This study analyzes the variations in service headway for different vehicle classes, leader-follower pairs, and locations in toll plazas operating under mixed traffic conditions. The results show that the best-fitted distribution for different vehicle classes and locations is the Generalized Extreme Value distribution.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2022)
Article
Public, Environmental & Occupational Health
Di Yang, Kun Xie, Kaan Ozbay, Zifeng Zhao, Hong Yang
Summary: This study proposes a multivariate copula-based modeling framework to jointly model crash count and conflict risk measures. The framework not only shows superior in-sample crash count prediction accuracy, but also demonstrates the potential to identify high-risk locations.
ANALYTIC METHODS IN ACCIDENT RESEARCH
(2021)
Article
Computer Science, Artificial Intelligence
Marwa K. H. Hassan, Muhammad Aslam
Summary: This paper introduces a new DUS-neutrosophic multivariate inverse Weibull distribution that can handle imprecise or interval observations in data. Statistical properties, functions, and maximum likelihood estimation methods are derived for this distribution. Monte-Carlo simulation is used to study the behavior of maximum likelihood estimates. Comparison with existing distributions under classical statistics shows that the proposed distribution provides smaller values of Akaike's information criteria and Bayesian information criteria. This study can be extended to other statistical distributions as future research.
COMPLEX & INTELLIGENT SYSTEMS
(2023)
Article
Mathematics
Zhiwei Bai, Hongkui Wei, Yingying Xiao, Shufang Song, Sergei Kucherenko
Summary: By using Vine copula, the joint probability density function of multidimensional variables can be decomposed into the product of marginal PDF and bivariate copula functions, transforming multidimensional dependent problems into two-dimensional dependent problems. A novel Vine copula-based approach is proposed for analyzing variance-based sensitivity measures, accurately estimating the main and total sensitivity indices of dependent input variables. Test cases and engineering examples demonstrate the accuracy and applicability of the proposed methods.
Article
Meteorology & Atmospheric Sciences
Dineshkumar Muthuvel, Mahesha Amai
Summary: This study examined the impact of concurrent droughts on crop yield in India using a copula-based multivariate approach. Results showed that concurrent droughts could lead to significant yield losses, with a teleconnection between ENSO and concurrent monsoon droughts.
INTERNATIONAL JOURNAL OF CLIMATOLOGY
(2022)
Article
Statistics & Probability
Zheng Wei, Daeyoung Kim
Summary: This paper presents a new model-free exploratory method for descriptive modeling that identifies and measures the regression dependence between an ordinal response variable and categorical explanatory variables. The proposed methodology includes checkerboard copula score, checkerboard copula regression, and checkerboard copula association measure. It investigates the properties and performance of these methods through simulation and real data.
JOURNAL OF MULTIVARIATE ANALYSIS
(2021)
Article
Computer Science, Interdisciplinary Applications
Liang Han, Haijun Liu, Wengang Zhang, Lin Wang
Summary: This study evaluates the performance of different models in geo-material parametric data and finds that copula models generally have lower model uncertainty compared to the conventional multivariate normal distribution model, with the elliptical copula model ranking first. For a balanced evaluation of performance and complexity, the conventional multivariate normal distribution model is favored.
COMPUTERS AND GEOTECHNICS
(2023)
Article
Mathematics
Tariq Saali, Mhamed Mesfioui, Ani Shabri
Summary: This paper presents a multivariate extension of Raftery copula and establishes several properties of the proposed copula. The multivariate Kendall's tau, Spearman's rho, and density function of the suggested copula are derived. The lower and upper tail dependence of the copula are also determined. The dependence parameter estimator is examined using the maximum likelihood procedure, and a simulation study demonstrates satisfactory performance. Finally, the proposed copula is successfully applied to a real data set on black cherry trees.
Article
Physics, Multidisciplinary
Shubo Wu, Yajie Zou, Lingtao Wu, Yue Zhang
Summary: Time headway distribution is important in traffic flow analysis and estimation. Previous studies proposed different statistical distributions, but model uncertainty makes it difficult to find certain types of distributions for different traffic conditions. To overcome this, a Bayesian model averaging (BMA) approach considers the advantages of different distributions. Six time headway datasets were collected from different traffic facilities in Guangzhou, China. The study finds that no single distribution is universally appropriate, but the BMA approach accurately describes time headway distribution under different traffic conditions.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2023)
Article
Thermodynamics
Zihao Yang, Weinan Huang, Sheng Dong, Huajun Li
Summary: The present study focuses on the bivariate distribution of wind speed and air density using a mixture copula model. The model captures the multimodal characteristics of the joint distribution and allows for a thorough assessment of offshore wind energy potential. The assumption of constant air density cannot be justified in predicting the energy production of a wind farm and an accurate description of its probabilistic structure is required.
ENERGY CONVERSION AND MANAGEMENT
(2023)
Article
Environmental Sciences
Zachary P. Brodeur, Scott Steinschneider
Summary: The study introduces a generalized error model for generating synthetic forecasts for water resources management, utilizing Skew Generalized Error Distribution and Copula method for simulation and validation. Two case studies conducted in Northern California demonstrate the flexibility and applicability of the model.
WATER RESOURCES RESEARCH
(2021)
Article
Engineering, Civil
Hanqing Xia, Xiaoming Liu, Zechao Ma, Fang Zhu, Lin Zhang, Yingjie Zhao, Yuanrong Wang
Summary: This paper proposes a method for estimating the speed and position of unsampled vehicles using sampled data from connected automated vehicles. A velocity estimation model incorporating a speed correction factor and a position estimation model based on optimizing IDM parameters are developed. Experimental results demonstrate the accuracy and practicality of the proposed method under different density and penetration rate conditions.
JOURNAL OF ADVANCED TRANSPORTATION
(2023)
Article
Engineering, Civil
Fateh Chebana, Taha B. M. J. Ouarda
Summary: The objective of this study is to construct a model that integrates both multivariate and non-stationarity aspects and conduct hypothesis testing. Dynamic copulas are considered for the copula part and a series of association measures are obtained through rolling windows.
JOURNAL OF HYDROLOGY
(2021)
Article
Environmental Sciences
P. Sathish Kumar, G. Dharani, J. Santhanakumar, Dilip Kumar Jha, Vikas Pandey, S. Venkatnarayanan, J. Prince Prakash Jebakumar, C. Muthukumar, R. Arthur James
Summary: This study investigated the spatial variation of phytoplankton community along the Tamil Nadu coast and found that human activities and nutrient inputs have altered the coastal ecosystem. The dominance of pennate diatoms, attributed to higher NO3- concentrations, in the phytoplankton community highlights the impact of agricultural discharge. Cluster analysis revealed distinct differences in physicochemical parameters between the northern and southern districts of the TN coast.
FRONTIERS IN MARINE SCIENCE
(2023)
Article
Engineering, Civil
Jinjun Tang, Fang Liu, Yajie Zou, Weibin Zhang, Yinhai Wang
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2017)
Article
Engineering, Electrical & Electronic
Shaoxin Yuan, Benjamin Wright, Yajie Zou, Yinhai Wang
IET INTELLIGENT TRANSPORT SYSTEMS
(2017)
Article
Engineering, Civil
Yajie Zou, Xinzhi Zhong, John Ash, Ziqiang Zeng, Yinhai Wang, Yanxi Hao, Yichuan Peng
JOURNAL OF ADVANCED TRANSPORTATION
(2017)
Article
Statistics & Probability
Yajie Zou, John E. Ash, Byung-Jung Park, Dominique Lord, Lingtao Wu
JOURNAL OF APPLIED STATISTICS
(2018)
Article
Engineering, Civil
Yajie Zou, Jinjun Tang, Lingtao Wu, Kristian Henrickson, Yinhai Wang
PROCEEDINGS OF THE INSTITUTION OF CIVIL ENGINEERS-TRANSPORT
(2017)
Article
Transportation
Yajie Zou, Hang Yang, Yunlong Zhang, Jinjun Tang, Weibin Zhang
TRANSPORTMETRICA A-TRANSPORT SCIENCE
(2017)
Article
Engineering, Civil
Hang Yang, Yajie Zou, Zhongyu Wang, Bing Wu
CANADIAN JOURNAL OF CIVIL ENGINEERING
(2018)
Article
Computer Science, Artificial Intelligence
Jinjun Tang, Fang Liu, Wenhui Zhang, Ruimin Ke, Yajie Zou
EXPERT SYSTEMS WITH APPLICATIONS
(2018)
Article
Physics, Multidisciplinary
Jinjun Tang, Shen Zhang, Xinqiang Chen, Fang Liu, Yajie Zou
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2018)
Article
Multidisciplinary Sciences
Xin Ye, Ke Wang, Yajie Zou, Dominique Lord
Article
Transportation Science & Technology
Yajie Zou, Xin Ye, Kristian Henrickson, Jinjun Tang, Yinhai Wang
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2018)
Article
Engineering, Civil
Yichuan Peng, Mohamed Abdel-Aty, Jaeyoung Lee, Yajie Zou
JOURNAL OF TRANSPORTATION ENGINEERING PART A-SYSTEMS
(2018)
Article
Green & Sustainable Science & Technology
Yajie Zou, Xinzhi Zhong, Jinjun Tang, Xin Ye, Lingtao Wu, Muhammad Ijaz, Yinhai Wang
Article
Chemistry, Multidisciplinary
Yajie Zou, Lusa Ding, Hao Zhang, Ting Zhu, Lingtao Wu
Summary: This study proposes a vehicle acceleration prediction model based on machine learning methods and driving behavior analysis, which significantly improves the prediction accuracy of vehicle acceleration and classifies drivers into homogeneous and heterogeneous groups based on behavioral semantics.
APPLIED SCIENCES-BASEL
(2022)
Article
Computer Science, Information Systems
Shengxue Zhu, Chongyi Li, Kexin Fang, Yichuan Peng, Yuming Jiang, Yajie Zou
Summary: This study aims to identify dangerous driving behavior by extracting vehicle trajectory through video monitoring, ensuring highway traffic safety. By defining risk index, using various methods for anomaly detection, and optimizing imbalanced classification algorithms, dangerous driving behavior can be effectively recognized.
Article
Transportation Science & Technology
Yue Zhao, Liujiang Kang, Huijun Sun, Jianjun Wu, Nsabimana Buhigiro
Summary: This study proposes a 2-population 3-strategy evolutionary game model to address the issue of subway network operation extension. The analysis reveals that the rule of maximum total fitness ensures the priority of evolutionary equilibrium strategies, and proper adjustment minutes can enhance the effectiveness of operation extension.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)
Article
Transportation Science & Technology
Hongtao Hu, Jiao Mob, Lu Zhen
Summary: This study investigates the challenges of daily storage yard management in marine container terminals considering delayed transshipment of containers. A mixed-integer linear programming model is proposed to minimize various costs associated with transportation and yard management. The improved Benders decomposition algorithm is applied to solve the problem effectively and efficiently.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)
Article
Transportation Science & Technology
Zhandong Xu, Yiyang Peng, Guoyuan Li, Anthony Chen, Xiaobo Liu
Summary: This paper studied the impact of range anxiety among electric vehicle drivers on traffic assignment. Two types of range-constrained traffic assignment problems were defined based on discrete or continuous distributed range anxiety. Models and algorithms were proposed to solve the two types of problems. Experimental results showed the superiority of the proposed algorithm and revealed that drivers with heightened range anxiety may cause severe congestion.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)
Article
Transportation Science & Technology
Chuanjia Li, Maosi Geng, Yong Chen, Zeen Cai, Zheng Zhu, Xiqun (Michael) Chen
Summary: Understanding spatial-temporal stochasticity in shared mobility is crucial, and this study introduces the Bi-STTNP prediction model that provides probabilistic predictions and uncertainty estimations for ride-sourcing demand, outperforming conventional deep learning methods. The model captures the multivariate spatial-temporal Gaussian distribution of demand and offers comprehensive uncertainty representations.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)
Article
Transportation Science & Technology
Benjamin Coifman, Lizhe Li
Summary: This paper develops a partial trajectory method for aligning views from successive fixed cameras in order to ensure high fidelity with the actual vehicle movements. The method operates on the output of vehicle tracking to provide direct feedback and improve alignment quality. Experimental results show that this method can enhance accuracy and increase the number of vehicles in the dataset.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)
Article
Transportation Science & Technology
Mohsen Dastpak, Fausto Errico, Ola Jabali, Federico Malucelli
Summary: This article discusses the problem of an Electric Vehicle (EV) finding the shortest route from an origin to a destination and proposes a problem model that considers the occupancy indicator information of charging stations. A Markov Decision Process formulation is presented to optimize the EV routing and charging policy. A reoptimization algorithm is developed to establish the sequence of charging station visits and charging amounts based on system updates. Results from a comprehensive computational study show that the proposed method significantly reduces waiting times and total trip duration.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)