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2011 International Conference on Fluid Power and Mechatronics, FPM 2011

作者： Yao, Chengyu Dang, Zhen Chen, Dongning Lv, Shijun Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao China

ISBN: (纸本)9781424484522

In order to overcome the characteristics of uncertainty and incomplete information of fault attribute in searching for fault, a new fault search method based on the fault tree and grey fuzzy multi-attribute decision-making is proposed in this paper. Firstly, utilizing fault tree analysis (FTA) method to determine the initial fault alternative, fault probability and search cost of the fault alternative are considered as fault attributes simultaneously, the attribute value of fault alternative is described as grey fuzzy numbers, calculating the attribute weight by the information entropy method. Then, the grey relational grade between the fault alternative and the ideal alternative is calculated base on grey relational analysis method, and relative closeness of fault alternative is achieved. Finally, according to the relative closeness determine the search order of all fault alternatives. An engineering example of the hydraulic suspension system of a certain type truck is adopted to demonstrate the feasibility and accuracy of the proposed method. © 2011 IEEE.

关键词： Fault tree analysis

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T-S model based fault tree analysis on the hoisting system of rubber-tyred girder hoister

T-S model based fault tree analysis on the hoisting system o...

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2010 WASE International Conference on Information engineering, ICIE 2010

作者： Yao, Chengyu Zhang, Yingyi Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao China

ISBN: (纸本)9780769540801

Hoisting system is the key part of the girder hoister, and its reliability determines the stability and security of the girder hoister directly. Hoisting system consists of mechanical, electrical and hydraulic components. Owing to the multiple and complex failure modes and mechanisms of the components, the hoisting system's reliability evaluation is accomplished by Fault Tree Analysis (FTA) based on T-S model. Failure probabilities can be described as fuzzy possibilities and fault degrees are expressed in terms of fuzzy numbers, while events' relationships are described by T-S gates instead of conventional logic gates. A method to acquire knowledge about the premise and consequent events is given, in terms of fuzzy rules of T-S gates made up of fuzzy possibilities and fault degrees of components. Fuzzy possibilities of the intermediate events and the top event are computed by MATlab, in terms of information about field experiences and expert data. Considering the influence of fault degrees to the system at the same time, it offers reference to find and improve relevant weaknesses of the system, thus the dependability of the whole hoisting system is improved. © 2010 IEEE.

关键词： Fault tree analysis

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An Improved Seagull Optimization Algorithm for Flexible Job-shop Scheduling Problem 13

An Improved Seagull Optimization Algorithm for Flexible Job-...

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13th IEEE International Conference on CYBER Technology in Automation, control, and Intelligent Systems, CYBER 2023

作者： Ma, Kai Yao, Shijie Guo, Shiliang Yang, Bin Li, Shuai Yanshan University Key Lab of Industrial Computer Control Engineering of Hebei Province Qinhuangdao China

ISBN: (纸本)9798350315196

Job-shop scheduling problem is the core link and key technology to realize smart factory and develop smart manufacturing technology. Among them, the flexible job-shop scheduling problem (FJSP) which is more consistent with the actual production and processing mode has been focused. This paper proposes an improved seagull optimization algorithm(ISOA) for solving the FJSP. The ISOA uses chaos initialization and reverse learning to optimize initial population, and introduces Q-learning to change the fitting parameters to balance global search and local search. In addition, we propose a local search model that is adaptive iterative process to enhance the algorithm's optimization search capability. The results of the experiment proved that the algorithm is superior in terms of optimization speed and scheduling results. © 2023 IEEE.

关键词： Iterative methods

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A Stackelberg Game for Spectrum Leasing in Cooperative Cognitive Radio Networks

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International Journal of Automation and computing 2013年第2期10卷 125-133页

作者： Xiao-Cheng Wang Xin-Ping Guan Qiao-Ni Han Zhi-Xin Liu Kai Ma Institute of Electrical Engineering Key Laboratory of Industrial Computer Control Engineering of Hebei Province Yanshan University School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University

According to the property-rights model of cognitive radio, primary users （PUs） who own the spectrum resource have the right to lease part of spectrum to secondary users （SUs） in exchange for appropriate profit. In this paper, we propose a pricing-based spectrum leasing framework between one PU and multiple SUs. In this scenario, the PU attempts to maximize its utility by setting the price of spectrum. Then, the selected SUs have the right to decide their power levels to help PU s transmission, aiming to obtain corresponding access time. The spectrum leasing problem can be cast into a stackelberg game, where the PU plays the seller-level game and the selected SUs play the buyer-level game. Through analysis based on the backward induction, we prove that there exists a unique equilibrium in the stackelberg game with certain constraints. Numerical results show that the proposed pricing-based spectrum leasing framework is effective, and the performance of both PU and SUs is improved, compared to the traditional mechanism without cooperation.

关键词： Cognitive radio spectrum leasing power control cooperative transmission pricing stackelberg game

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Relaxed Stability Analysis and Event-Triggered controller Design for Discrete-Time Positive T-S Fuzzy Networked control Systems 49

Relaxed Stability Analysis and Event-Triggered Controller De...

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49th Annual Conference of the IEEE industrial Electronics Society, IECON 2023

作者： Wang, Xiaoxiao Li, Xiaomiao Bao, Zhiyong Liu, Fucai Du, Yuehao Yanshan University Key Lab of Industrial Computer Control Engineering of Hebei Province Qinhuangdao China

ISBN: (纸本)9798350331820

This paper deals with the relaxation stability analysis and event-triggered controller design of discrete-time positive Takagi-Sugeno (T-S) fuzzy networked control systems (FNCSs). The constraints of positive conditions in NCSs bring significant challenges to stability analysis and controller design. A 1-norm event-triggered scheme is proposed for the positive system, which can effectively reduce the frequency of network communication. Since the event-triggered T-S fuzzy controller (ETTSFC) can only observe the latest transmission state after the triggering action, the ETTSFC selects the premise variables different from the T-S fuzzy model, improving design and implementation flexibility. Using the linear copositive Lyapunov function (LCLF), the design criteria of the event-triggered controller to ensure the positivity and stability of the closed-loop system are derived. To relax the sum-of-squares (SOS) based conservative condition, we adopt the Taylor series membership functions (TSMFs) and introduce TSMFs and their approximation error into the stability conditions. Finally, an example is given to illustrate the effectiveness of the design. © 2023 IEEE.

关键词： Lyapunov functions

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An Improved NSGAII Algorithm for Flexible Job-shop Scheduling Problem Based on A New Decoding Mechanism 13

An Improved NSGAII Algorithm for Flexible Job-shop Schedulin...

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13th IEEE International Conference on CYBER Technology in Automation, control, and Intelligent Systems, CYBER 2023

作者： Li, Man Ma, Kai Guo, Shiliang Li, Shuai Yang, Bin Yanshan University Key Lab of Industrial Computer Control Engineering of Hebei Province Qinhuangdao China

ISBN: (纸本)9798350315196

The flexible job-shop scheduling problem (FJSP) is a famous combinatorial optimization problem. FJSP is widely used in process manufacturing industry, so it is of great significance to study FJSP to improve production efficiency. In this paper, a non-dominated sorting genetic algorithm II based on a new decoding mechanism (NSGAII-NDM) is proposed. Firstly, the opposite-based learning strategy is introduced on the basis of NSGAII, and the sufficiency of global search is improved by generating the opposite value. Secondly, an improved adaptive crossover and mutation probability strategy is added, which can dynamically adjust the inherent crossover and mutation probability with the number of iterations and improve the convergence speed of the algorithm. Furthermore, based on fully active scheduling strategy, a new decoding mechanism is proposed, which can get a better scheduling scheme by arranging the machines and starting time of each process more reasonably. Finally, the improved algorithm is tested in a standard test case, which verifies the superiority of NSGAII-NDM in solving the flexible job-shop scheduling problem. © 2023 IEEE.

关键词： Production efficiency

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Design and Analysis of Polynomial Positive Fuzzy System controllers Based on Markov Transitions

Design and Analysis of Polynomial Positive Fuzzy System Cont...

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2024 China Automation Congress, CAC 2024

作者： Chang, Sen Li, Xiaomiao Liu, Fucai Bao, Zhiyong Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao China

ISBN: (纸本)9798350368604

This study explores polynomial Markov positive fuzzy systems, formulating controllers for these systems by examining the prerequisites for positivity and stochastic stability. Initially, polynomials are incorporated into the Markov positive fuzzy system to represent nonlinear elements better and enhance its capacity to model nonlinear systems. Concurrently, the study discusses the non-convex scenarios encountered in the stability analysis of the closed-loop system once the positive fuzzy system controller is integrated and confirms the stability of the Markov polynomial positive fuzzy system. Ultimately, the effectiveness of the proposed approaches is demonstrated through a numerical simulation example. © 2024 IEEE.

关键词： Fuzzy systems

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Bandwidth Allocation with Minimum Rate Constraints in Cluster-based Femtocell Networks

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International Journal of Automation and computing 2015年第1期12卷 77-82页

作者： Kai Ma Liang Li Jie Yang Zhi-Xin Liu Xin-Bin Li Xin-Ping Guan School of Electrical Engineering Key Laboratory of Industrial Computer Control Engineering of Hebei Province Yanshan University Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information ProcessingMinistry of Education

Inter-femtocell interference becomes serious when femtocells are densely deployed. To mitigate the inter-femtocell interference, this paper proposes a cluster-based bandwidth allocation algorithm. We create femtocell clusters by constructing a weighted interference graph and allocate bandwidth to each cluster based on a Nash bargaining solution(NBS). Simulation results show that the cluster-based bandwidth allocation algorithm can reduce the inter-femtocell interference and meet the minimum rate constraint of each cluster.

关键词： Femtocell cluster inter-femtocell interference bandwidth allocation Nash bargaining solution(NBS)

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Relay Selection and Power control for Mobile Underwater Acoustic Communication Networks: A Dual-Thread Reinforcement Learning Approach

IEEE Transactions on Green Communications and Networking

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IEEE Transactions on Green Communications and Networking 2024年第2期9卷 1-1页

作者： Dai, Jun Li, Xinbin Han, Song Yu, Junzhi Liu, Zhixin Key Lab of Industrial Computer Control Engineering of Hebei Province China Department of Advanced Manufacturing and Robotics College of Engineering State Key Laboratory for Turbulence and Complex Systems Peking University Beijing China

This paper deals with a cooperation communication problem (relay selection and power control) for mobile underwater acoustic communication networks. To achieve satisfactory transmission capacity, we propose a reinforcement-learning-based cooperation communication scheme to efficiently resist the highly dynamic communication links and strongly unknown time-varying channel states caused by the mobility of Autonomous Underwater Vehicles (AUVs). Firstly, a particular Markov decision process is developed to model the dynamic relay selection process of mobile AUV in the unknown scenario. In the developed model, an experimental statistical-based partition mechanism is proposed to cope with the greatly increasing dimension of the state space caused by the mobility of AUV, reducing the search optimization difficulty. Secondly, a dual-thread reinforcement learning structure with actual and virtual learning threads is proposed to efficiently track the superior relay action. In the actual learning thread, the proposed improved probability greedy policy enables the AUV to strengthen the exploration for the reward information of potential superior relays on the current state. Meanwhile, in the virtual learning thread, the proposed upper-confidence-bound-index-based uncertainty estimation method can estimate the action-reward level of historical states. Consequently, the combination of actual and virtual learning threads can efficiently obtain satisfactory Q value information, thereby making superior relay decision-making in a short time. Thirdly, a power control mechanism is proposed to reuse the current observed action-reward information and transform the multiple unknown parameter nonlinear joint power optimization problem into a convex optimization problem, thereby enhancing network transmission capacity. Finally, simulation results verify the effectiveness of the proposed scheme. IEEE

关键词： Convex optimization

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Predicting preeclampsia in early pregnancy using clinical and laboratory data via machine learning model

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BMC Medical Informatics and Decision Making 2025年第1期25卷 1-15页

作者： Chen, Songchang Li, Jia Zhang, Xiao Xu, Wenqiu Qiu, Zhixu Yan, Siyao Zhao, Wenrui Zhao, Zhiguang Tian, Peirun Zhao, Qiang Zhang, Qun Chen, Weiping Li, Huahua Ruan, Xiaohong Xiao, Gefei Zhang, Sufen Hu, Liqing Qin, Jie Huang, Wuyan Li, Zhongzhe Wang, Shunyao Zhang, Rui Huang, Shang Wang, Xin Yao, Yao Ran, Jian Cheng, Danling Luo, Qi Pan, Teng Gao, Ruyun Zheng, Jing Wang, Yuxuan Liu, Cong Cao, Xianling Zhou, Xuanyou Xu, Naixin Zhang, Lanlan Han, Xu Wang, Haolin Feng, Suihua Li, Shuyuan Zhang, Jianguo Zhao, Lijian Wei, Fengxiang Obstetrics and Gynecology Hospital Institute of Reproduction and Development Fudan University Shanghai 200011 China Hebei Industrial Technology Research Institute of Genomics in Maternal & Child Health Clin Lab BGI Genomics Hebei Province Shijiazhuang 050011 China BGI Genomics Guangdong Province Shenzhen 518083 China Hebei Medical University Hebei Province Shijiazhuang 050011 China Department of Obstetrics and Gynecology Jiangmen Central Hospital Guangdong Province Jiangmen 529030 China Clinical Transformation and Application Key Lab for Obstetrics and Gynecology Pediatrics and Reproductive Medicine of Jiangmen Guangdong Province Jiangmen 529030 China Department of Medical Genetics and Prenatal Diagnosis Zhuhai Center for Maternal and Child Health Care Guangdong Province Zhuhai 519000 China Department of Prevention and Health Care Zhuhai Center for Maternal and Child Health Care Guangdong Province Zhuhai 519000 China Hunan Provincial Key Laboratory of Regional Hereditary Birth Defects Prevention and Control Changsha Hospital for Maternal & Child Health Care Affiliated to Hunan Normal University Hunan Province Changsha 410007 China Division of Maternal-Fetal Medicine Shenzhen Bao’ an Women’s and Children’s Hospital Guangdong Province Shenzhen 518102 China The Genetics Laboratory Longgang District Maternity and Child Healthcare Hospital of Shenzhen City (Longgang Maternity and Child Institute of Shantou University Medical College) Longgang District Guangdong Province Shenzhen 518712 China Longgang District Maternity and Child Healthcare Hospital of Shenzhen City (Longgang Maternity and Child Institute of Shantou University Medical College) Guangdong Province Shenzhen 518712 China Department of Blood Transfusion The Affiliated Suzhou Hospital of Nanjing Medical University Suzhou Municipal Hospital Gusu School Nanjing Medical University 80 Tianedang Road Suzhou Jiangsu 518712 China School of Basic Medical Sciences Jiamusi University Heilongjiang P

Background: This study was performed to characterize the relationship of various laboratory test indicators with clinical information and Preeclampsia (PE) development. Then, prediction models for early-onset preeclampsia (EOPE), late-onset preeclampsia (LOPE), and preterm preeclampsia (Preterm PE) were developed using maternal characteristics and laboratory data. Methods: Between January 2019 and December 2021, we retrospectively recruited 144 EOPE, 363 LOPE, 231 Preterm PE, and 1458 healthy participants from six hospitals. We utilized all available clinical and laboratory data obtained during routine prenatal visits in early pregnancy. The models for EOPE, LOPE, and Preterm PE were created using ensemble machine learning models with patient clinical and laboratory data. Results: By comparing laboratory variables between PE patients and healthy controls, we identified 7, 18, 8, 15, 7,29 laboratory markers for EOPE, LOPE, and Preterm PE, severe PE, superimposed PE, first-time PE respectively. The ensemble EOPE and LOPE models incorporating clinical and laboratory predictors outperformed the clinical factor models respectively. The ensemble EOPE model demonstrated good sensitivity (72.22%,95% confidence interval [CI]: 57.59%-86.85%) and specificity (85.25%,95% CI: 80.54%-89.97%) in distinguishing EOPE from controls in early pregnancy. Similarly, the ensemble LOPE model showed good accuracy in differentiating LOPE from healthy participants (sensitivity: 69.57%, 95% CI: 56.27%-82.86%;specificity: 85.25%, 95% CI: 80.54%-89.97%). The prediction scores demonstrated notable positive correlations with blood pressure at admission, while they showed inverse correlations with 24-hour urine protein levels and fetal growth restriction among PE patients. In conclusion, our study identified key laboratory indicators for forecasting PE. The developed models exhibited good predictive capability for assessing preeclampsia risk and severity based on clinical and laboratory data. Clini

关键词： laboratory data Machine learning model Preeclampsia

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