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Science China(Information Sciences) 2015年第7期58卷 128-143页

作者： liu guanjun JIANG ChangJun Department of Computer Science Tongji University Key Laboratory of the Ministry of Education for Embedded System and Service Computing Tongji University

Inter-organizational workflow nets(IWF-nets) can well model the interactions among multiple processes by sending/receiving messages. Compatibility and weak compatibility are crucial properties for *** latter guarantees that a system is deadlock-free and livelock-free while the former also guarantees that it has no dead tasks. Our previous work proved that the(weak) compatibility problem is PSPACE-complete for safe IWF-nets. This paper defines a class of IWF-nets in which some simple circuits are allowed. Necessary and sufficient conditions are presented to decide compatibility and weak compatibility for this class, and they are dependent on the net structures only. Algorithms are developed based on these conditions. In addition, we show that the traditional net structures like siphon cannot be easily used to decide the(weak) compatibility of IWF-nets.

关键词： formal method workflow nets compatibility business process model web services composition

Observable liveness of Petri nets with controllable and observable transitions

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Science China(Information Sciences) 2017年第11期60卷 256-264页

作者： guanjun liu Changjun JIANG Department of Computer Science Tongji University Key Laboratory of Embedded System and Service Computing of Ministry of Education Tongji University E-commerce Transactions and Information Services Collaborative Innovation Center of Shanghai University Knowledge Service Platform Tongji University

Observability and/or controllability are paid much attention to by researchers not only from the control science field[1–3]but also from the computer science field[4–9].Recently,Desel and Kilinc[4]proposed the notion of observable liveness for Petri nets with(un-)observable and(un-)controllable *** purpose of defining observable liveness is to represent that"a user can always enforce the occurrence of any observable transition only by stimulating the net by choosing appropriate enabled controllable transition"[4].An important assumption of

关键词： net cot PN Observable liveness of Petri nets with controllable and observable transitions

Sensor Optimization Selection Model Based on Testability Constraint

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Chinese Journal of Aeronautics 2012年第2期25卷 262-268页

作者： YANG Shuming QIU Jing liu guanjun Laboratory of Science and Technology on Integrated Logistics Support College of Mechatronics Engineering and AutomationNational University of Defense TechnologyChangsha 410073China

Sensor selection and optimization is one of the important parts in design for testability. To address the problems that the traditional sensor optimization selection model does not take the requirements of prognostics and health management especially fault prognostics for testability into account and does not consider the impacts of sensor actual attributes on fault detectability, a novel sensor optimization selection model is proposed. Firstly, a universal architecture for sensor selection and optimization is provided. Secondly, a new testability index named fault predictable rate is defined to describe fault prognostics requirements for testability. Thirdly, a sensor selection and optimization model for prognostics and health management is constructed, which takes sensor cost as objective function and the defined testability indexes as constraint conditions. Due to NP-hard property of the model, a generic algorithm is designed to obtain the optimal solution. At last, a case study is presented to demonstrate the sensor selection approach for a stable tracking servo platform. The application results and comparison analysis show the proposed model and algorithm are effective and feasible. This approach can be used to select sensors for prognostics and health management of any system.

关键词： prognostics and health management design for testability fault predictable rate sensor selection and optimization generic algorithm

Sensor selection of helicopter transmission systems based on physical model and sensitivity analysis

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Chinese Journal of Aeronautics 2014年第3期27卷 643-654页

作者： Lyu Kehong Tan Xiaodong liu guanjun Zhao Chenxu Science and Technology on Integrated Logistics Support Laboratory National University of Defense Technology Department of Electronic Technology Officer’s College of CAPF

In the helicopter transmission systems, it is important to monitor and track the tooth damage evolution using lots of sensors and detection methods. This paper develops a novel approach for sensor selection based on physical model and sensitivity analysis. Firstly, a physical model of tooth damage and mesh stiffness is built. Secondly, some effective condition indicators （Cls） are presented, and the optimal Cls set is selected by comparing their test statistics according to Mann-Kendall test. Afterwards, the selected CIs are used to generate a health indicator （HI） through sen slop estimator. Then, the sensors are selected according to the monotonic relevance and sensitivity to the damage levels. Finally, the proposed method is verified by the simulation and experimental data. The results show that the approach can provide a guide for health monitor- ing of helicopter transmission systems, and it is effective to reduce the test cost and improve the system＇s reliability.

关键词： Condition indicators Health indicator Helicopter transmissionsystems Mann-Kendall test Physical model Sensitivity analysis Sen slop estimator Sensor selection

A novel testability model for health management of heading attitude system

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Chinese Journal of Aeronautics 2013年第1期26卷 201-208页

作者： liu guanjun Yang Shuming Qiu Jing Yang Peng Laboratory of Science and Technology on Integrated Logistics Support College of Mechatronics Engineering and Automation National University of Defense Technology

Prognostics and health management （PHM） is very important to guarantee the reliability and safety of aerospace systems, and sensing and test are the precondition of PHM. Integrating design for testability into early design stage of system early design stage is deemed as a fundamental way to improve PHM performance, and testability model is the base of testability analysis and design. This paper discusses a hierarchical model-based approach to testability modeling and analysis for heading attitude system health management. Quantified directed graph, of which the nodes represent components and tests and the directed edges represent fault propagation paths, is used to describe fault-test dependency, and quantitative testability information is assigned to nodes and directed edges. The fault dependencies between nodes can be obtained by functional fault analysis methodology that captures the physical architecture and material flows such as energy, heat, data, and so on. By incorporating physics of failure models into component, the dynamic process of a failing or degrading component can be projected onto system behavior, i.e., system symptoms. Then, the analysis of extended failure modes, mechanisms and effects is utilized to construct fault evolution-test dependency. Using this integrated model, the designers and system analysts can assess the test suite＇s fault detectability, fault isolability and fault predictability. And heading attitude system application results show that the proposed model can support testability analysis and design for PHM very well.

关键词： Fault evolution Functional fault analysis Physics of failure model Prognostics and health management Quantified directed graph Testability analysis

Probabilistic Automata-Based Method for Enhancing Performance of Deep Reinforcement Learning Systems

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IEEE/CAA Journal of Automatica Sinica 2024年第11期11卷 2327-2339页

作者： Min Yang guanjun liu Ziyuan Zhou Jiacun Wang the Department of Computer Science Tongji University IEEE the Computer Science and Software Engineering Department Monmouth UniversityWest Long Branch

Deep reinforcement learning(DRL) has demonstrated significant potential in industrial manufacturing domains such as workshop scheduling and energy system ***, due to the model's inherent uncertainty, rigorous validation is requisite for its application in real-world tasks. Specific tests may reveal inadequacies in the performance of pre-trained DRL models, while the “black-box” nature of DRL poses a challenge for testing model behavior. We propose a novel performance improvement framework based on probabilistic automata,which aims to proactively identify and correct critical vulnerabilities of DRL systems, so that the performance of DRL models in real tasks can be improved with minimal model ***, a probabilistic automaton is constructed from the historical trajectory of the DRL system by abstracting the state to generate probabilistic decision-making units(PDMUs), and a reverse breadth-first search(BFS) method is used to identify the key PDMU-action pairs that have the greatest impact on adverse outcomes. This process relies only on the state-action sequence and final result of each trajectory. Then, under the key PDMU, we search for the new action that has the greatest impact on favorable results. Finally, the key PDMU, undesirable action and new action are encapsulated as monitors to guide the DRL system to obtain more favorable results through real-time monitoring and correction mechanisms. Evaluations in two standard reinforcement learning environments and three actual job scheduling scenarios confirmed the effectiveness of the method, providing certain guarantees for the deployment of DRL models in real-world applications.

关键词： Deep reinforcement learning(DRL) performance improvement framework probabilistic automata real-time monitoring the key probabilistic decision-making units(PDMU)-action pair

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A clustering-based flexible weighting method in AdaBoost and its application to transaction fraud detection

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Science China(Information Sciences) 2021年第12期64卷 69-79页

作者： Chaofan YANG guanjun liu Chungang YAN Changjun JIANG Department of Computer Science Tongji University Shanghai Electronic Transactions and Information Service Collaborative Innovation Center Tongji University

AdaBoost is a famous ensemble learning method and has achieved successful applications in many fields. The existing studies illustrate that AdaBoost easily suffers from noisy points, resulting in a decline of classification performance. The main reason is that it increases the weights of all misclassified samples(especially noisy points) in the same way so that the influence of noisy points can hardly be weakened. In this paper, the clustering algorithm is used to dynamically decide noisy points in the process of *** precisely, we compute a misclassification degree for every cluster in every iteration that is used to decide if a misclassified sample is a noisy point or not in the current iteration. Furthermore, we propose a flexible method to update the weights of the misclassified samples. The experimental results on 22 public datasets show that our method achieves better results than the state-of-the-art methods including AdaBoost,AdaCoast, LogitBoost, and SPLBoost. We also apply our method to the transactions fraud detection, and the experiments on our real big dataset of transactions also illustrate its good performance.

关键词： ensemble learning AdaBoost clustering misclassification degree transaction fraud detection

Detecting Data-flow Errors Based on Petri Nets With Data Operations

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IEEE/CAA Journal of Automatica Sinica 2018年第1期5卷 251-260页

作者： Dongming Xiang guanjun liu Chungang Yan Changjun Jiang Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 201804 China IEEE

In order to guarantee the correctness of business processes, not only control-flow errors but also data-flow errors should be considered. The control-flow errors mainly focus on deadlock, livelock, soundness, and so on. However, there are not too many methods for detecting data-flow errors. This paper defines Petri nets with data operations(PN-DO) that can model the operations on data such as read, write and delete. Based on PN-DO, we define some data-flow errors in this paper. We construct a reachability graph with data operations for each PN-DO, and then propose a method to reduce the reachability graph. Based on the reduced reachability graph, data-flow errors can be detected rapidly. A case study is given to illustrate the effectiveness of our methods.

关键词： Business process modeling data-flow errors Petri nets reachability graph

Optimization of dynamic sequential test strategy for equipment health management

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Journal of Systems Engineering and Electronics 2012年第1期23卷 71-77页

作者： Shuming Yang Jing Qiu guanjun liu Peng Yang Laboratory of Science and Technology on Integrated Logistics Support College of Mechatronics Engineering and Automation National University of Defense Technology Changsha 410073 P. R. China

Testing is the premise and foundation of realizing equipment health management （EHM）. To address the problem that the static periodic test strategy may cause deficient test or excessive test, a dynamic sequential test strategy （DSTS） for EHM is presented. Considering the situation that equipment health state is not completely observable in reality, a DSTS optimization method based on partially observable semi-Markov decision pro- cess （POSMDP） is proposed. Firstly, an equipment health state degradation model is constructed by Markov process, and the control limit maintenance policy is also introduced. Secondly, POSMDP is formulated in great detail. And then, POSMDP is converted to completely observable belief semi-Markov decision process （BSMDP） through belief state. The optimal equation and the corresponding optimal DSTS, which minimize the long-run ex- pected average cost per unit time, are obtained with BSMDP. The results of application in complex equipment show that the proposed DSTS is feasible and effective.

关键词： equipment health management (EHM) dynamic sequential test strategy (DSTS) partially observable semi-Markov decision process (POSMDP) optimal equation.

Partition-based Collaborative Tensor Factorization for POI Recommendation

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IEEE/CAA Journal of Automatica Sinica 2017年第3期4卷 437-446页

作者： Wenjing Luan guanjun liu Changjun Jiang Liang Qi Department of Computer Science and Technology Tongji University IEEE Key Laboratory of Embedded System and Service Computing Tongji University

The rapid development of location-based social networks(LBSNs) provides people with an opportunity of better understanding their mobility behavior which enables them to decide their next *** example,it can help travelers to choose where to go next,or recommend salesmen the most potential places to deliver advertisements or sell *** this paper,a method for recommending points of interest(POIs)is proposed based on a collaborative tensor factorization(CTF)***,a generalized objective function is constructed for collaboratively factorizing a tensor with several feature ***,a 3-mode tensor is used to model all users' check-in behaviors,and three feature matrices are extracted to characterize the time distribution,category distribution and POI correlation,***,each user's preference to a POI at a specific time can be estimated by using *** order to further improve the recommendation accuracy,PCTF(Partitionbased CTF) is proposed to fill the missing entries of a tensor after clustering its every *** on a real checkin database show that the proposed method can provide more accurate location recommendation.

关键词： Clustering context feature extraction point of interest(POI) recommendation tensor factorization