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| 1 | Toward Cloud Computing QoS Architecture:Analysis of Cloud Systems and Cloud Services显示文摘Cloud can be defined as a new computing paradigm that provides scalable, on-demand, and virtualized resources for users. In this style of computing, users can access a shared pool of computing resources which are provisioned with minimal management efforts of users. Yet there are some obstacles and concerns about the use of clouds. Guaranteeing quality of service(Qo S) by service providers can be regarded as one of the main concerns for companies tending to use it. Service provisioning in clouds is based on service level agreements representing a contract negotiated between users and providers. According to this contract, if a provider cannot satisfy its agreed application requirements, it should pay penalties as compensation. In this paper, we intend to carry out a comprehensive survey on the models proposed in literature with respect to the implementation principles to address the QoS guarantee issue. | Mohammad Hossein Ghahramani MengChu Zhou Chi Tin Hon | 2017 | IEEE/CAA Journal of Automatica Sinica2017，4，1： | 19 |
| 2 | An Online Fault Detection Model and Strategies Based on SVM-Grid in Clouds显示文摘Online fault detection is one of the key technologies to improve the performance of cloud systems. The current data of cloud systems is to be monitored, collected and used to reflect their state. Its use can potentially help cloud managers take some timely measures before fault occurrence in clouds. Because of the complex structure and dynamic change characteristics of the clouds, existing fault detection methods suffer from the problems of low efficiency and low accuracy. In order to solve them, this work proposes an online detection model based on asystematic parameter-search method called SVM-Grid, whose construction is based on a support vector machine(SVM). SVM-Grid is used to optimize parameters in SVM. Proper attributes of a cloud system's running data are selected by using Pearson correlation and principal component analysis for the model. Strategies of predicting cloud faults and updating fault sample databases are proposed to optimize the model and improve its performance.In comparison with some representative existing methods, the proposed model can achieve more efficient and accurate fault detection for cloud systems. | PeiYun Zhang Sheng Shu MengChu Zhou | 2018 | IEEE/CAA Journal of Automatica Sinica2018，5，2： | 16 |
| 3 | Modified Cuckoo Search Algorithm to Solve Economic Power Dispatch Optimization Problems显示文摘A modified cuckoo search(CS) algorithm is proposed to solve economic dispatch(ED) problems that have nonconvex, non-continuous or non-linear solution spaces considering valve-point effects, prohibited operating zones, transmission losses and ramp rate limits. Comparing with the traditional cuckoo search algorithm, we propose a self-adaptive step size and some neighbor-study strategies to enhance search performance.Moreover, an improved lambda iteration strategy is used to generate new solutions. To show the superiority of the proposed algorithm over several classic algorithms, four systems with different benchmarks are tested. The results show its efficiency to solve economic dispatch problems, especially for large-scale systems. | Jian Zhao Shixin Liu Mengchu Zhou Xiwang Guo Liang Qi | 2018 | IEEE/CAA Journal of Automatica Sinica2018，5，4： | 14 |
| 4 | An Embedded Feature Selection Method for Imbalanced Data Classification显示文摘Imbalanced data is one type of datasets that are frequently found in real-world applications, e.g., fraud detection and cancer diagnosis. For this type of datasets, improving the accuracy to identify their minority class is a critically important issue.Feature selection is one method to address this issue. An effective feature selection method can choose a subset of features that favor in the accurate determination of the minority class. A decision tree is a classifier that can be built up by using different splitting criteria. Its advantage is the ease of detecting which feature is used as a splitting node. Thus, it is possible to use a decision tree splitting criterion as a feature selection method. In this paper, an embedded feature selection method using our proposed weighted Gini index(WGI) is proposed. Its comparison results with Chi2, F-statistic and Gini index feature selection methods show that F-statistic and Chi2 reach the best performance when only a few features are selected. As the number of selected features increases, our proposed method has the highest probability of achieving the best performance. The area under a receiver operating characteristic curve(ROC AUC) and F-measure are used as evaluation criteria. Experimental results with two datasets show that ROC AUC performance can be high, even if only a few features are selected and used, and only changes slightly as more and more features are selected. However, the performance of Fmeasure achieves excellent performance only if 20% or more of features are chosen. The results are helpful for practitioners to select a proper feature selection method when facing a practical problem. | Haoyue Liu MengChu Zhou Qing Liu | 2019 | IEEE/CAA Journal of Automatica Sinica2019，6，3： | 11 |
| 5 | Randomized Latent Factor Model for High-dimensional and Sparse Matrices from Industrial Applications显示文摘Latent factor(LF) models are highly effective in extracting useful knowledge from High-Dimensional and Sparse(HiDS) matrices which are commonly seen in various industrial applications. An LF model usually adopts iterative optimizers,which may consume many iterations to achieve a local optima,resulting in considerable time cost. Hence, determining how to accelerate the training process for LF models has become a significant issue. To address this, this work proposes a randomized latent factor(RLF) model. It incorporates the principle of randomized learning techniques from neural networks into the LF analysis of HiDS matrices, thereby greatly alleviating computational burden. It also extends a standard learning process for randomized neural networks in context of LF analysis to make the resulting model represent an HiDS matrix correctly.Experimental results on three HiDS matrices from industrial applications demonstrate that compared with state-of-the-art LF models, RLF is able to achieve significantly higher computational efficiency and comparable prediction accuracy for missing data.I provides an important alternative approach to LF analysis of HiDS matrices, which is especially desired for industrial applications demanding highly efficient models. | Mingsheng Shang Xin Luo Zhigang Liu Jia Chen Ye Yuan MengChu Zhou | 2019 | IEEE/CAA Journal of Automatica Sinica2019，6，1： | 11 |
| 6 | A Survey of Multi-robot Regular and Adversarial Patrolling显示文摘Multi-robot systems can be applied to patrol a concerned environment for security purposes.According to different goals,this work reviews the existing researches in a multi-robot patrolling field from the perspectives of regular and adversarial patrolling.Regular patrolling requires robots to visit important locations as frequently as possible and a series of deterministic strategies are proposed,while adversarial one focuses on unpredictable robots’moving patterns to maximize adversary detection probability.Under each category,a systematic survey is done including problem statements and modeling,patrolling objectives and evaluation criteria,and representative patrolling strategies and approaches.Existing problems and open questions are presented accordingly. | Li Huang MengChu Zhou Kuangrong Hao Edwin Hou | 2019 | IEEE/CAA Journal of Automatica Sinica2019，6，4： | 10 |
| 7 | A Survey of Cyber Attacks on Cyber Physical Systems:Recent Advances and Challenges显示文摘A cyber physical system(CPS)is a complex system that integrates sensing,computation,control and networking into physical processes and objects over Internet.It plays a key role in modern industry since it connects physical and cyber worlds.In order to meet ever-changing industrial requirements,its structures and functions are constantly improved.Meanwhile,new security issues have arisen.A ubiquitous problem is the fact that cyber attacks can cause significant damage to industrial systems,and thus has gained increasing attention from researchers and practitioners.This paper presents a survey of state-of-the-art results of cyber attacks on cyber physical systems.First,as typical system models are employed to study these systems,time-driven and event-driven systems are reviewed.Then,recent advances on three types of attacks,i.e.,those on availability,integrity,and confidentiality are discussed.In particular,the detailed studies on availability and integrity attacks are introduced from the perspective of attackers and defenders.Namely,both attack and defense strategies are discussed based on different system models.Some challenges and open issues are indicated to guide future research and inspire the further exploration of this increasingly important area. | Wenli Duo MengChu Zhou Abdullah Abusorrah | 2022 | IEEE/CAA Journal of Automatica Sinica2022，9，5： | 6 |
| 8 | A Multi-Layered Gravitational Search Algorithm for Function Optimization and Real-World Problems显示文摘A gravitational search algorithm(GSA)uses gravitational force among individuals to evolve population.Though GSA is an effective population-based algorithm,it exhibits low search performance and premature convergence.To ameliorate these issues,this work proposes a multi-layered GSA called MLGSA.Inspired by the two-layered structure of GSA,four layers consisting of population,iteration-best,personal-best and global-best layers are constructed.Hierarchical interactions among four layers are dynamically implemented in different search stages to greatly improve both exploration and exploitation abilities of population.Performance comparison between MLGSA and nine existing GSA variants on twenty-nine CEC2017 test functions with low,medium and high dimensions demonstrates that MLGSA is the most competitive one.It is also compared with four particle swarm optimization variants to verify its excellent performance.Moreover,the analysis of hierarchical interactions is discussed to illustrate the influence of a complete hierarchy on its performance.The relationship between its population diversity and fitness diversity is analyzed to clarify its search performance.Its computational complexity is given to show its efficiency.Finally,it is applied to twenty-two CEC2011 real-world optimization problems to show its practicality. | Yirui Wang Shangce Gao Mengchu Zhou Yang Yu | 2021 | IEEE/CAA Journal of Automatica Sinica2021，8，1： | 5 |
| 9 | A Dynamic Road Incident Information Delivery Strategy to Reduce Urban Traffic Congestion显示文摘Advanced information and communication technologies can be used to facilitate traffic incident management. If an incident is detected and blocks a road link, in order to reduce the incident-induced traffic congestion, a dynamic strategy to deliver incident information to selected drivers and help them make detours in urban areas is proposed by this work. Time-dependent shortest path algorithms are used to generate a subnetwork where vehicles should receive such information. A simulation approach based on an extended cell transmission model is used to describe traffic flow in urban networks where path information and traffic flow at downstream road links are well modeled.Simulation results reveal the influences of some major parameters of an incident-induced congestion dissipation process such as the ratio of route-changing vehicles to the total vehicles, operation time interval of the proposed strategy, traffic density in the traffic network, and the scope of the area where traffic incident information is delivered. The results can be used to improve the state of the art in preventing urban road traffic congestion caused by incidents. | liang qi mengchu zhou wenjing luan | 2018 | IEEE/CAA Journal of Automatica Sinica2018，5，5： | 4 |
| 10 | From Mind to Products:Towards Social Manufacturing and Service显示文摘After reviewing the development of industrial manufacturing, a novel concept called social manufacturing(SM) and service are proposed as an innovative manufacturing solution for the coming personalized customization era. SM can realize a customer's requirements of 'from mind to products', and fulfill tangible and intangible needs of a prosumer, i.e., producer and consumer at the same time. It represents a manufacturing trend,and is expected to become popular in more and more industries.First, a comparison between mass customization and SM is given out, and the basis and motivation from social network to SM is analyzed. Then, its basic theories and supporting technologies,like Internet of Things(Io T), social networks, cloud computing,3 D printing, and intelligent systems, are introduced and analyzed,and an SM platform prototype is developed. Finally, three transformation modes towards SM and 3 D printing are suggested for different user cases. | Gang Xiong Fei-Yue Wang Timo R. Nyberg Xiuqin Shang Mengchu Zhou Zhen Shen Shuangshuang Li Chao Guo | 2018 | IEEE/CAA Journal of Automatica Sinica2018，5，1： | 3 |
| 11 | A Workflow Decomposition Algorithm Based on Invariants显示文摘 | PANG Shanchen LIN Chuang ZHOU Mengchu LI Yin | 2011 | Chinese Journal of Electronics2011，20，1： | 3 |
| 12 | Residual-driven Fuzzy C-Means Clustering for Image Segmentation显示文摘In this paper,we elaborate on residual-driven Fuzzy C-Means(FCM)for image segmentation,which is the first approach that realizes accurate residual(noise/outliers)estimation and enables noise-free image to participate in clustering.We propose a residual-driven FCM framework by integrating into FCM a residual-related regularization term derived from the distribution characteristic of different types of noise.Built on this framework,a weighted?2-norm regularization term is presented by weighting mixed noise distribution,thus resulting in a universal residual-driven FCM algorithm in presence of mixed or unknown noise.Besides,with the constraint of spatial information,the residual estimation becomes more reliable than that only considering an observed image itself.Supporting experiments on synthetic,medical,and real-world images are conducted.The results demonstrate the superior effectiveness and efficiency of the proposed algorithm over its peers. | Cong Wang Witold Pedrycz ZhiWu Li MengChu Zhou | 2021 | IEEE/CAA Journal of Automatica Sinica2021，8，4： | 3 |
| 13 | Dual-Objective Mixed Integer Linear Program and Memetic Algorithm for an Industrial Group Scheduling Problem显示文摘Group scheduling problems have attracted much attention owing to their many practical applications.This work proposes a new bi-objective serial-batch group scheduling problem considering the constraints of sequence-dependent setup time,release time,and due time.It is originated from an important industrial process,i.e.,wire rod and bar rolling process in steel production systems.Two objective functions,i.e.,the number of late jobs and total setup time,are minimized.A mixed integer linear program is established to describe the problem.To obtain its Pareto solutions,we present a memetic algorithm that integrates a population-based nondominated sorting genetic algorithm II and two single-solution-based improvement methods,i.e.,an insertion-based local search and an iterated greedy algorithm.The computational results on extensive industrial data with the scale of a one-week schedule show that the proposed algorithm has great performance in solving the concerned problem and outperforms its peers.Its high accuracy and efficiency imply its great potential to be applied to solve industrial-size group scheduling problems. | Ziyan Zhao Shixin Liu MengChu Zhou Abdullah Abusorrah | 2021 | IEEE/CAA Journal of Automatica Sinica2021，8，6： | 3 |
| 14 | Deadlock-free Supervisor Design for Robotic Manufacturing Cells With Uncontrollable and Unobservable Events显示文摘In this paper,a deadlock prevention policy for robotic manufacturing cells with uncontrollable and unobservable events is proposed based on a Petri net formalism.First,a Petri net for the deadlock control of such systems is defined.Its admissible markings and first-met inadmissible markings(FIMs)are introduced.Next,place invariants are designed via an integer linear program(ILP)to survive all admissible markings and prohibit all FIMs,keeping the underlying system from reaching deadlocks,livelocks,bad markings,and the markings that may evolve into them by firing uncontrollable transitions.ILP also ensures that the obtained deadlock-free supervisor does not observe any unobservable transition.In addition,the supervisor is guaranteed to be admissible and structurally minimal in terms of both control places and added arcs.The condition under which the supervisor is maximally permissive in behavior is given.Finally,experimental results with the proposed method and existing ones are given to show its effectiveness. | Bo Huang MengChu Zhou Cong Wang Abdullah Abusorrah Yusuf Al-Turki | 2021 | IEEE/CAA Journal of Automatica Sinica2021，8，3： | 3 |
| 15 | Computation of an Emptiable Minimal Siphon in a Subclass of Petri Nets Using Mixed-Integer Programming显示文摘Deadlock resolution strategies based on siphon control are widely investigated.Their computational efficiency largely depends on siphon computation.Mixed-integer programming(MIP)can be utilized for the computation of an emptiable siphon in a Petri net(PN).Based on it,deadlock resolution strategies can be designed without requiring complete siphon enumeration that has exponential complexity.Due to this reason,various MIP methods are proposed for various subclasses of PNs.This work proposes an innovative MIP method to compute an emptiable minimal siphon(EMS)for a subclass of PNs named S^(4)PR.In particular,many particular structural characteristics of EMS in S4 PR are formalized as constraints,which greatly reduces the solution space.Experimental results show that the proposed MIP method has higher computational efficiency.Furthermore,the proposed method allows one to determine the liveness of an ordinary S^(4)PR. | Shouguang Wang Wenli Duo Xin Guo Xiaoning Jiang Dan You Kamel Barkaoui MengChu Zhou | 2021 | IEEE/CAA Journal of Automatica Sinica2021，8，1： | 2 |
| 16 | Analysis of Evolutionary Social Media Activities: Pre-Vaccine and Post-Vaccine Emergency Use显示文摘Dear Editor,In this letter,we analyze the public discourse sentiments over time and seek to understand the salient patterns around COVID-19 vaccines and vaccination from social media data.Globally,more than 373 million people have been diagnosed with COVID-19 and 5.66 million have died from this disease by 2022.It continues to have a negative impact on human daily life and the global economic development till now,due to the lack of effective treatment of COVID-19 induced issues and prevention of transmission methods. | Haoyue Liu MengChu Zhou Xiaoyu Lu Abdullah Abusorrah Yusuf Al-Turki | 2023 | IEEE/CAA Journal of Automatica Sinica2023，10，4： | 2 |
| 17 | Hybrid Petri Nets for Modeling and Analysis of Microgrid Systems显示文摘Hybrid Petri nets(HPNs) are widely used to describe and analyze various industrial hybrid systems that have both discrete-event and continuous discrete-time behaviors. Recently,many researchers attempt to utilize them to characterize power and energy systems. This work proposes to adopt an HPN to model and analyze a microgrid that consists of green energy sources. A reachability graph for such a model is generated and used to analyze the system properties. | Xiaoyu Lu MengChu Zhou Ahmed Chiheb Ammari Jingchu Ji | 2016 | IEEE/CAA Journal of Automatica Sinica2016，3，4： | 2 |
| 18 | A Novel Multiobjective Fireworks Algorithm and Its Applications to Imbalanced Distance Minimization Problems显示文摘Recently,multimodal multiobjective optimization problems(MMOPs)have received increasing attention.Their goal is to find a Pareto front and as many equivalent Pareto optimal solutions as possible.Although some evolutionary algorithms for them have been proposed,they mainly focus on the convergence rate in the decision space while ignoring solutions diversity.In this paper,we propose a new multiobjective fireworks algorithm for them,which is able to balance exploitation and exploration in the decision space.We first extend a latest single-objective fireworks algorithm to handle MMOPs.Then we make improvements by incorporating an adaptive strategy and special archive guidance into it,where special archives are established for each firework,and two strategies(i.e.,explosion and random strategies)are adaptively selected to update the positions of sparks generated by fireworks with the guidance of special archives.Finally,we compare the proposed algorithm with eight state-of-the-art multimodal multiobjective algorithms on all 22 MMOPs from CEC2019 and several imbalanced distance minimization problems.Experimental results show that the proposed algorithm is superior to compared algorithms in solving them.Also,its runtime is less than its peers'. | Shoufei Han Kun Zhu MengChu Zhou Xiaojing Liu Haoyue Liu Yusuf Al-Turki Abdullah Abusorrah | 2022 | IEEE/CAA Journal of Automatica Sinica2022，9，8： | 2 |
| 19 | Editorial: Evolution from AI, IoT and Big Data Analytics to Metaverse显示文摘Time flies.Since I took over the Editor-in-Chief position from this journal’s founding Editor-in-Chief,Professor Fei-Yue Wang in 2018,five years has past just like a second.Looking back from today,as a team,we,including editorial board members,editorial staff members,our early career advisory board members,all contributing authors and all reviewers,should be proud of what this journal has achieved.This journal is the first of its kind of journals,resulting from IEEE’s collaboration with Chinese Association of Automation-an outside-USA professional organization/institution.We have overcome many barriers and difficulties,and well proven that we,united and working together,can accomplish a challenging mission.We indeed set a great example for IEEE and its many societies to pursue more and more collaboration with other publishers,organizations and institutions from not only China but also such countries as India,Brazil,and Japan. | MengChu Zhou | 2022 | IEEE/CAA Journal of Automatica Sinica2022，9，12： | 2 |
| 20 | Urban Sensing Based on Mobile Phone Data:Approaches,Applications,and Challenges显示文摘Data volume grows explosively with the proliferation of powerful smartphones and innovative mobile applications.The ability to accurately and extensively monitor and analyze these data is necessary.Much concern in cellular data analysis is related to human beings and their behaviours.Due to the potential value that lies behind these massive data,there have been different proposed approaches for understanding corresponding patterns.To that end,analyzing people's activities,e.g.,counting them at fixed locations and tracking them by generating origindestination matrices is crucial.The former can be used to determine the utilization of assets like roads and city attractions.The latter is valuable when planning transport infrastructure.Such insights allow a government to predict the adoption of new roads,new public transport routes,modification of existing infrastructure,and detection of congestion zones,resulting in more efficient designs and improvement.Smartphone data exploration can help research in various fields,e.g.,urban planning,transportation,health care,and business marketing.It can also help organizations in decision making,policy implementation,monitoring,and evaluation at all levels.This work aims to review the methods and techniques that have been implemented to discover knowledge from mobile phone data.We classify these existing methods and present a taxonomy of the related work by discussing their pros and cons. | Mohammadhossein Ghahramani MengChu Zhou Gang Wang | 2020 | IEEE/CAA Journal of Automatica Sinica2020，7，3： | 2 |
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