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Attaining the stabilizing solution of model unavailable modified algebraic Riccati equation using Q-learning algorithm

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Information Sciences 2025年 717卷

作者： Jie Gao Tao Feng Fei Yan School of Information Science and Technology Southwest Jiaotong University Chengdu Sichuan PR China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Chengdu PR China

This paper attempts first to solve the discrete-time modified algebraic Riccati equation (MARE) when the system model is completely unavailable. To achieve this, a new iterative algorithm is proposed to solve the MARE based on its equivalent discrete-time algebraic Riccati equation (DARE) which has an identical solution. The algorithm iterates between two steps: 1) the solution improvement of the equivalent DARE; 2) the input weighting improvement. It is proved theoretically that the algorithm strictly converges to the stabilizing solution of the MARE. As an outstanding advantage over the existing methods, the initiation of the algorithm becomes fairly simple which can be initialized by an arbitrary positive input weighting for the single-input scenario or a pre-given input weighting matrix of a sufficiently large magnitude for the multi-input scenario. Furthermore, the proposed algorithm provides an iterative structure which is particularly suitable for developing the Q-learning (QL) algorithm where only the input/output data of the related linear quadratic regulator (LQR) problem is required, therefore the MARE can be solved successfully without using the system model. Finally, numerical simulation examples are given to verify the effectiveness of the theoretical results and the developed algorithm.

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Distributed Minimum-Energy Containment Control of Continuous-Time Multi-Agent Systems by Inverse Optimal Control

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IEEE/CAA Journal of Automatica Sinica 2024年第6期11卷 1533-1535页

作者： Fei Yan Xiangbiao Liu Tao Feng School of Information Science and Technology Southwest Jiaotong UniversityChengdu 611756China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Chengdu 611756China

Dear Editor,This letter focuses on the distributed optimal containment control of continuous-time multi-agent systems(CTMASs)with respect to the minimum-energy performance index over fixed *** achieve this,we firstly investigate the optimal containment control problem using the inverse optimal control method,where all states of followers asymptotically converge to the convex hull spanned by the leaders while some quadratic performance indexes get minimized.A sufficient condition for existence of the distributed optimal containment control protocol is *** introducing the parametric algebraic Riccati equation(PARE),it is strictly proved that the global performance index can be used to approximate the standard minimumenergy performance index as the parameters tends to *** consequence,the standard minimum-energy cooperative containment control can be solved by local steady state feedback protocols.

关键词： optimal infinity algebraic

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Fare Structure Optimization of Intercity Railway With Regional Passenger Income Disparities

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IET Intelligent Transport Systems 2025年第1期19卷

作者： Ninghai Li Baohua Mao Junsheng Huang Fang Wen Gang Xu Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport Beijing Jiaotong University Beijing China College of Urban Transportation and Logistics Shenzhen Technology University Shenzhen China

The fare structure of intercity railways is crucial for passenger service and sustainable operation. The Current distance-based fare structure (CFS) and a regional distance-based fare structure (RDFS) are investigated to achieve breakeven under limited subsidies. Passenger choice behaviors are measured by a nested-logit (NL) model with prospect theory, considering regional passenger income disparities. A nonlinear programming model is proposed to determine the fare structure and departure headway, of which the objective function maximizes the social welfare, including operator revenue and passenger turnover. A multiple-population genetic algorithm with an elite strategy is designed to solve the problem. The case study shows that the proposed RDFS can effectively increase operator revenue by 5.88%, while sacrificing only 1.73% of the turnover compared to the current fare structure. Under limited subsidies, the RDFS reduces the required passenger demand by 5.70% for achieving breakeven. RDFS consistently shows the highest social welfare under varying passenger income levels among cities and commuter proportions.

关键词： fare structure intercity railway NL prospect theory social welfare

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Role of mountains and rivers in the formation of logistics enterprises'spatial pattern in the central urban areas of Chongqing

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Journal of Mountain Science 2022年第7期19卷 2060-2074页

作者： LIU Si-jing ZHU Cheng-jia HE Nan-nan LI Guo-qi School of Transportation and Logistics Southwest Jiaotong UniversityChengdu611756China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Chengdu611756China National United Engineering Laboratory of Integrated and Intelligent Transportation Chengdu611756China

The complex landforms of a Shan-shui City(Shan-shui refers to mountains and rivers)significantly impact the selection of locations for logistics *** paper takes Chongqing,one of the most typical Shan-shui Cities in China,as the research object,and adopts spatial analysis methods and a mediating effect model,to explore the role of mountains and rivers in the formation of logistics enterprises’spatial pattern on the street *** study results reveal that 90% of the logistics enterprises in the central urban areas of Chongqing are located in the low-altitude area below 353m above sea level,and distributed in a north-south direction along the mountains,as a result of blockage by mountain ranges,such as those of Zhongliang Mountain and Tongluo *** than 70% of the logistics enterprises are located less than 5 km from either the Yangtze River or Jialing River,spreading along the *** addition,more than half of the logistics enterprises in commercial and financial,and residential land are located within the urban core area,while 80.83% of the logistics enterprises located in warehousing land and industrial land are concentrated in the urban expansion *** areas with high land prices,the negative effect of altitude on logistics enterprise agglomeration is weakened,while the promotion effect of river proximity on logistics enterprise agglomeration is *** the urban core area with the advantage of low altitude and proximity to the Jialing and Yangtze Rivers,the role of mountains and rivers on logistics enterprises is not apparent;in contrast,in the urban expansion area with more complex landforms,land price can be an effective means for the government to macro-manage the spatial pattern of logistics enterprises in a Shan-shui City.

关键词： Logistics enterprise Spatial pattern Influencing factors Driving mechanism Chongqing

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Multi-Attention Fusion Modeling for Sentiment Analysis of Educational big data

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big data Mining and Analytics 2020年第4期3卷 311-319页

作者： Guanlin Zhai Yan Yang Heng Wang Shengdong Du the School of Information Science and Technology National Engineering Laboratory of Integrated Transportation Big Data Application TechnologySouthwest Jiaotong UniversityChengdu 611756China

As an important branch of natural language processing,sentiment analysis has received increasing *** teaching evaluation,sentiment analysis can help educators discover the true feelings of students about the course in a timely manner and adjust the teaching plan accurately and timely to improve the quality of education and *** at the inefficiency and heavy workload of college curriculum evaluation methods,a Multi-Attention Fusion Modeling(Multi-AFM)is proposed,which integrates global attention and local attention through gating unit control to generate a reasonable contextual representation and achieve improved classification *** results show that the Multi-AFM model performs better than the existing methods in the application of education and other fields.

关键词： educational big data sentiment analysis aspect-level attention

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Distribution Vehicle Routing Optimization Based on 3D Loading 4th

Distribution Vehicle Routing Optimization Based on 3D Loadin...

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

作者： Luo, Xuan Zhang, Jin Yin, Tingyu Zhu, Hongxing Qiu, Mingyue School of Transportation and Logistics Southwest Jiaotong University Chengdu611756 China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Southwest Jiaotong University Chengdu611756 China Comprehensive Transportation Big Data Application Technology Laboratory Chengdu611756 China

ISBN: (纸本)9789811640384

The rapid development of e-commerce leads to increasingly fierce competition in the logistics industry. Cost reduction and efficiency has become the key issue for logistics enterprises to survive. Loading optimization and path optimization are the two core issues in distribution activities, and they are inseparable and related. The joint optimization of the two is more in line with the actual distribution optimization needs. Based on the analysis of the interaction between routing and loading, this paper proposes a multi-objective optimization model with the minimum distribution cost, the minimum number of vehicles and the maximum customer satisfaction as the objectives. A hybrid nesting algorithm based on NSGAII algorithm is designed, in which the packing module is designed by tree search algorithm combined with the deepest and leftmost algorithm. Finally, the real data of China Railway Express Chengdu branch are taken as a case to verify the feasibility of the model and algorithm. Combined with the results of the algorithm, some suggestions are put forward. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Customer satisfaction

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Dynamic train dwell time forecasting:a hybrid approach to address the influence of passenger flow fluctuations

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Railway engineering Science 2023年第4期31卷 351-369页

作者： Zishuai Pang Liwen Wang Shengjie Wang Li Li Qiyuan Peng School of Transportation and Logistics Southwest Jiaotong UniversityChengdu 610031China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Southwest Jiaotong UniversityChengdu 610031China

Train timetables and operations are defined by the train running time in sections,dwell time at stations,and headways between *** estimation of these factors is essential to decision-making for train delay reduction,train dispatching,and station capacity *** the present study,we aim to propose a train dwell time model based on an averaging mechanism and dynamic updating to address the challenges in the train dwell time prediction problem(e.g.,dynamics over time,heavy-tailed distribution of data,and spatiotemporal relationships of factors)for real-time train *** averaging mechanism in the present study is based on multiple state-of-the-art base predictors,enabling the proposed model to integrate the advantages of the base predictors in addressing the challenges in terms of data attributes and data ***,considering the influence of passenger flow on train dwell time,we use a dynamic updating method based on exponential smoothing to improve the performance of the proposed method by considering the real-time passenger amount fluctuations(e.g.,passenger soars in peak hours or passenger plunges during regular periods).We conduct experiments with the train operation data and passenger flow data from the Chinese high-speed railway *** results show that due to the advantages over the base predictors,the averaging mechanism can more accurately predict the dwell time at stations than its counterparts for different prediction horizons regarding predictive errors and ***,the experimental results show that dynamic smoothing can significantly improve the accuracy of the proposed model during passenger amount changes,i.e.,15.4%and 15.5%corresponding to the mean absolute error and root mean square error,*** on the proposed predictor,a feature importance analysis shows that the planned dwell time and arrival delay are the two most important factors to dwell ***,planned time has positive influen

关键词： Train operations Dwell time Passenger flow Averaging mechanism Dynamic smoothing

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MIRROR: Multi-Modal Pathological Self-Supervised Representation Learning via Modality Alignment and Retention

arXiv

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arXiv 2025年

作者： Wang, Tianyi Fan, Jianan Zhang, Dingxin Liu, Dongnan Xia, Yong Huang, Heng Cai, Weidong School of Computer Science The University of Sydney SydneyNSW2006 Australia National Engineering Laboratory for Integrated AeroSpace-Ground-Ocean Big Data Application Technology School of Computer Science and Engineering Northwestern Polytechnical University Xi’an710072 China Research & Development Institute of Northwestern Polytechnical University in Shenzhen Shenzhen518057 China Ningbo Institute of Northwestern Polytechnical University Ningbo315048 China Department of Computer Science University of Maryland College ParkMD20742 United States

Histopathology and transcriptomics are fundamental modalities in cancer diagnostics, encapsulating the morphological and molecular characteristics of the disease. Multi-modal self-supervised learning has demonstrated remarkable potential in learning pathological representations by integrating diverse data sources. Conventional multi-modal integration methods primarily emphasize modality alignment, while paying insufficient attention to retaining the modality-specific intrinsic structures. However, unlike conventional scenarios where multi-modal inputs often share highly overlapping features, histopathology and transcriptomics exhibit pronounced heterogeneity, offering orthogonal yet complementary insights. Histopathology data provides morphological and spatial context, elucidating tissue architecture and cellular topology, whereas transcriptomics data delineates molecular signatures through quantifying gene expression patterns. This inherent disparity introduces a major challenge in aligning these modalities while maintaining modality-specific fidelity. To address these challenges, we present MIRROR, a novel multi-modal representation learning framework designed to foster both modality alignment and retention. MIRROR employs dedicated encoders to extract comprehensive feature representations for each modality, which is further complemented by a modality alignment module to achieve seamless integration between phenotype patterns and molecular profiles. Furthermore, a modality retention module safeguards unique attributes from each modality, while a style clustering module mitigates redundancy and enhances disease-relevant information by modeling and aligning consistent pathological signatures within a clustering space. Extensive evaluations on The Cancer Genome Atlas (TCGA) cohorts for cancer subtyping and survival analysis highlight MIRROR’s superior performance, demonstrating its effectiveness in constructing comprehensive oncological feature representations and be

关键词： Self-supervised learning

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An aggregate flow based scheduler in multi-task cooperated UAVs network

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Chinese Journal of Aeronautics 2020年第11期33卷 2989-2998页

作者： Xiaohuan LI Ziqi XIE Jin YE Xin TANG Chunhai LI Fengzhu TANG Rong YU School of Information and Communication Guilin University of Electronic TechnologyGuilin 541004China Guangxi Key Laboratory of Multimedia Communications and Network Technology School of ComputerElectronics and InformationGuangxi UniversityNanning 530004China National Engineering Laboratory for Comprehensive Transportation Big Data Application Technology(Guangxi) Nanning 530001China School of Automation Guangdong University of TechnologyGuangzhou 510006China

Unmanned Aerial Vehicles(UAVs)cooperative multi-task system has become the research focus in recent ***,the existing network frameworks of UAVs are not flexible and efficient enough to deal with the complex multi-task scheduling,because they are not able to perceive the different *** this paper,a novel cooperated UAVs network framework for multi-task scheduling is *** is a three-layer network including a core layer,an aggregation layer and an execution layer,which enhances the efficiency of multi-task distribution,aggregation and ***,an Aggre Gate Flow(AGFlow)based scheduler is dedicatedly designed to maximize the task completion rate,whose key point is to aggregate flows belonging to one task during the multi-task transmission of UAVs network and to allocate priority by calculating the urgency-level of each *** results demonstrate that,compared with that of state-of-the-art scheduler,the average task completion rate of AGFlow based scheduler is raised by 0.278.

关键词： Mixed-flow scheduling Multi-task Task completion rate Unmanned Aerial Vehicles(UAVs) Urgency-level

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Coordinated Congestion Pricing for Bi-Modal Multi-Region Urban Networks 27

Coordinated Congestion Pricing for Bi-Modal Multi-Region Urb...

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27th IEEE International Conference on Intelligent transportation Systems, ITSC 2024

作者： He, Xiangyu Zhao, Yu Liu, Yafei Sun, Zhanbo School of Transportation and Logistics Southwest Jiaotong University National Engineering Laboratory of Integrated Transportation Big Data Application Technology Chengdu China

ISBN: (纸本)9798331505929

Extensive studies have explored designing pricing schemes for single-mode or homogeneous networks. The development of bi-modal Macroscopic Fundamental Diagrams (3D-MFD) facilitates real-time coordinated control strategies for bi-modal multi-regional urban networks. This research explores the traffic dynamics of mixed networks with urban networks and expressways, proposing two 3D-MFD-based coordinated pricing schemes for bi-modal multi-region urban networks. The first scheme utilizes a Model Predictive Control (MPC) approach to integrating toll rates into the 3D-MFD-based optimization problem. The second scheme applies feedback control theory to simultaneously determine the dynamic price and estimate the value of Time (VOT) and trip length distribution of commuters. The proposed coordinated pricing schemes are further compared with uncoordinated pricing schemes. Numerical examples indicate that coordinated pricing by comprehensively considering the traffic flow and demand across different regions of the urban network achieves more effective congestion alleviation. © 2024 IEEE.

关键词： Predictive control systems

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