This paper investigates a multiplayer Pareto game for affine nonlinear stochastic systems disturbed by both external and the internal multiplicative noises.The Pareto cooperative optimal strategies with the H_(∞) con...This paper investigates a multiplayer Pareto game for affine nonlinear stochastic systems disturbed by both external and the internal multiplicative noises.The Pareto cooperative optimal strategies with the H_(∞) constraint are resolved by integrating H_(2)/H_(∞) theory with Pareto game theory.First,a nonlinear stochastic bounded real lemma(SBRL)is derived,explicitly accounting for non-zero initial conditions.Through the analysis of four cross-coupled Hamilton-Jacobi equations(HJEs),we establish necessary and sufficient conditions for the existence of Pareto optimal strategies with the H_(∞) constraint.Secondly,to address the complexity of solving these nonlinear partial differential HJEs,we propose a neural network(NN)framework with synchronous tuning rules for the actor,critic,and disturbance components,based on a reinforcement learning(RL)approach.The designed tuning rules ensure convergence of the actor-critic-disturbance components to the desired values,enabling the realization of robust Pareto control strategies.The convergence of the proposed algorithm is rigorously analyzed using a constructed Lyapunov function for the NN weight errors.Finally,a numerical simulation example is provided to demonstrate the effectiveness of the proposed methods and main results.展开更多
The Pareto distribution plays an important role in various areas of research. In this paper, the average run length （ARL） unbiased control charts, which monitor the shape and threshold parameters of the Pareto distr...The Pareto distribution plays an important role in various areas of research. In this paper, the average run length （ARL） unbiased control charts, which monitor the shape and threshold parameters of the Pareto distribution respectively, are proposed when the incontrol parameters are known. The effects of parameter estimation on the performance of the proposed control charts are also studied. Results show that the control charts with the estimated parameters are not suitable to be used in the known parameter case, thus the ARL-unbiased control charts for the shape and threshold parameters with the desired ARLo, which consider the variability of the parameter estimates, are further developed. The performance of the proposed control charts is investigated in terms of the ARL. Finally, an example is given to illustrate the proposed control charts.展开更多
该研究通过系统检索2014—2024年中国知网、PubMed、Web of Science等数据库,获取关于高血压控制影响因素的研究文献137篇,采用文献分析法提取影响因素,利用帕累托法则筛选关键因素,并基于健康社会决定因素进行分类,为优化我国高血压防...该研究通过系统检索2014—2024年中国知网、PubMed、Web of Science等数据库,获取关于高血压控制影响因素的研究文献137篇,采用文献分析法提取影响因素,利用帕累托法则筛选关键因素,并基于健康社会决定因素进行分类,为优化我国高血压防控策略提供循证依据。结果显示,共提取64项影响因素,其中前20项累计占比为79.69%,将其归为关键因素,构建的模型涵盖生物遗传因素(35.97%)、个体生活方式(43.87%)及社会因素(20.16%)三个层面。研究表明,应基于健康社会决定因素,采取分层干预策略,即聚焦个体生活方式干预(行为层面)、管理生物遗传相关风险(生理层面)、改善社会支持环境(结构层面),以系统性提升高血压防治效能。展开更多
In this paper, we study an asymmetric game that characterizes the intentions of players to adopt a vaccine. The game describes a decision-making process of two players differentiated by income level and perceived trea...In this paper, we study an asymmetric game that characterizes the intentions of players to adopt a vaccine. The game describes a decision-making process of two players differentiated by income level and perceived treatment cost, who consider a vaccination against an infectious disease. The process is a noncooperative game since their vaccination decision has a direct impact on vaccine coverage in the population. We introduce a replicator dynamics (RD) to investigate the players’ optimal strategy selections over time. The dynamics reveal the long-term stability of the unique Nash-Pareto equilibrium strategy of this game, which is an extension of the notion of an evolutionarily stable strategy pair for asymmetric games. This Nash-Pareto pair is dependent on perceived costs to each player type, on perceived loss upon getting infected, and on the probability of getting infected from an infected person. Last but not least, we introduce a payoff parameter that plays the role of cost-incentive towards vaccination. We use an optimal control problem associated with the RD system to show that the Nash-Pareto pair can be controlled to evolve towards vaccination strategies that lead to a higher overall expected vaccine coverage.展开更多
This work proposes a novel approach for multi-type optimal placement of flexible AC transmission system(FACTS) devices so as to optimize multi-objective voltage stability problem. The current study discusses a way for...This work proposes a novel approach for multi-type optimal placement of flexible AC transmission system(FACTS) devices so as to optimize multi-objective voltage stability problem. The current study discusses a way for locating and setting of thyristor controlled series capacitor(TCSC) and static var compensator(SVC) using the multi-objective optimization approach named strength pareto multi-objective evolutionary algorithm(SPMOEA). Maximization of the static voltage stability margin(SVSM) and minimizations of real power losses(RPL) and load voltage deviation(LVD) are taken as the goals or three objective functions, when optimally locating multi-type FACTS devices. The performance and effectiveness of the proposed approach has been validated by the simulation results of the IEEE 30-bus and IEEE 118-bus test systems. The proposed approach is compared with non-dominated sorting particle swarm optimization(NSPSO) algorithm. This comparison confirms the usefulness of the multi-objective proposed technique that makes it promising for determination of combinatorial problems of FACTS devices location and setting in large scale power systems.展开更多
基金supported by the National Natural Science Foundation of China(12426609,62203220,62373229)the Taishan Scholar Project Foundation of Shandong Province(tsqnz20230619,tsqn202408110)+2 种基金the Fundamental Research Foundation of the Central Universities(23Cx06024A)the Natural Science Foundation of Shandong Province(ZR2024QF096)the Outstanding Youth Innovation Team in Shandong Higher Education Institutions(2023KJ061).
文摘This paper investigates a multiplayer Pareto game for affine nonlinear stochastic systems disturbed by both external and the internal multiplicative noises.The Pareto cooperative optimal strategies with the H_(∞) constraint are resolved by integrating H_(2)/H_(∞) theory with Pareto game theory.First,a nonlinear stochastic bounded real lemma(SBRL)is derived,explicitly accounting for non-zero initial conditions.Through the analysis of four cross-coupled Hamilton-Jacobi equations(HJEs),we establish necessary and sufficient conditions for the existence of Pareto optimal strategies with the H_(∞) constraint.Secondly,to address the complexity of solving these nonlinear partial differential HJEs,we propose a neural network(NN)framework with synchronous tuning rules for the actor,critic,and disturbance components,based on a reinforcement learning(RL)approach.The designed tuning rules ensure convergence of the actor-critic-disturbance components to the desired values,enabling the realization of robust Pareto control strategies.The convergence of the proposed algorithm is rigorously analyzed using a constructed Lyapunov function for the NN weight errors.Finally,a numerical simulation example is provided to demonstrate the effectiveness of the proposed methods and main results.
基金Supported by Foundation of Ministry of Education of China(13YJC910005,13YJC910010,12YJA910005)Zhejiang Provincial Natural Science Foundation of China(LY16G020003)+2 种基金the Philosophy and Social Science Research Project in Zhejiang Province of China(13NDJC055YB)the National Natural Science Foundation of China(11371322)the Zhejiang Provincial Key Research Base for Humanities and Social Science Research(Statistics)
文摘The Pareto distribution plays an important role in various areas of research. In this paper, the average run length （ARL） unbiased control charts, which monitor the shape and threshold parameters of the Pareto distribution respectively, are proposed when the incontrol parameters are known. The effects of parameter estimation on the performance of the proposed control charts are also studied. Results show that the control charts with the estimated parameters are not suitable to be used in the known parameter case, thus the ARL-unbiased control charts for the shape and threshold parameters with the desired ARLo, which consider the variability of the parameter estimates, are further developed. The performance of the proposed control charts is investigated in terms of the ARL. Finally, an example is given to illustrate the proposed control charts.
文摘该研究通过系统检索2014—2024年中国知网、PubMed、Web of Science等数据库,获取关于高血压控制影响因素的研究文献137篇,采用文献分析法提取影响因素,利用帕累托法则筛选关键因素,并基于健康社会决定因素进行分类,为优化我国高血压防控策略提供循证依据。结果显示,共提取64项影响因素,其中前20项累计占比为79.69%,将其归为关键因素,构建的模型涵盖生物遗传因素(35.97%)、个体生活方式(43.87%)及社会因素(20.16%)三个层面。研究表明,应基于健康社会决定因素,采取分层干预策略,即聚焦个体生活方式干预(行为层面)、管理生物遗传相关风险(生理层面)、改善社会支持环境(结构层面),以系统性提升高血压防治效能。
文摘In this paper, we study an asymmetric game that characterizes the intentions of players to adopt a vaccine. The game describes a decision-making process of two players differentiated by income level and perceived treatment cost, who consider a vaccination against an infectious disease. The process is a noncooperative game since their vaccination decision has a direct impact on vaccine coverage in the population. We introduce a replicator dynamics (RD) to investigate the players’ optimal strategy selections over time. The dynamics reveal the long-term stability of the unique Nash-Pareto equilibrium strategy of this game, which is an extension of the notion of an evolutionarily stable strategy pair for asymmetric games. This Nash-Pareto pair is dependent on perceived costs to each player type, on perceived loss upon getting infected, and on the probability of getting infected from an infected person. Last but not least, we introduce a payoff parameter that plays the role of cost-incentive towards vaccination. We use an optimal control problem associated with the RD system to show that the Nash-Pareto pair can be controlled to evolve towards vaccination strategies that lead to a higher overall expected vaccine coverage.
文摘This work proposes a novel approach for multi-type optimal placement of flexible AC transmission system(FACTS) devices so as to optimize multi-objective voltage stability problem. The current study discusses a way for locating and setting of thyristor controlled series capacitor(TCSC) and static var compensator(SVC) using the multi-objective optimization approach named strength pareto multi-objective evolutionary algorithm(SPMOEA). Maximization of the static voltage stability margin(SVSM) and minimizations of real power losses(RPL) and load voltage deviation(LVD) are taken as the goals or three objective functions, when optimally locating multi-type FACTS devices. The performance and effectiveness of the proposed approach has been validated by the simulation results of the IEEE 30-bus and IEEE 118-bus test systems. The proposed approach is compared with non-dominated sorting particle swarm optimization(NSPSO) algorithm. This comparison confirms the usefulness of the multi-objective proposed technique that makes it promising for determination of combinatorial problems of FACTS devices location and setting in large scale power systems.
文摘作为网络传输控制机制的核心,拥塞控制关注如何在异构网络环境中最优化特定传输性能目标。已有拥塞控制机制忽略了不同应用的性能偏好在吞吐量-时延两个维度上的帕累托最优前沿(Pareto optimal frontier,POF)分布,难以满足差异化应用的性能需求。针对上述问题,本文提出了一种面向应用性能偏好的帕累托最优拥塞控制机制pBBR(ParetooptimalBBR),结合离线网络场景学习和在线控制参数优化的思想,最大程度满足应用的差异化性能偏好。实验结果表明,pBBR能够在一个采集-识别周期内判断出网络场景的切换,从而快速选择当前网络场景的最优控制参数。每个网络场景下,pBBR都能够最大化满足不同的应用性能偏好:针对吞吐量敏感业务,pBBR可以达到Cubic(吞吐优先)的97%,且时延只有Cubic的52%;针对时延敏感业务,pBBR的时延可以达到Sprout(时延优先)的95%,同时吞吐量损失只有1%。此外,多参数优化可进一步提升pBBR性能,例如在高铁长期演进技术(long term evolution,LTE)通信场景下,单参数pBBR的吞吐量、时延分别是Cubic的94%和99%,而三参数pBBR则分别提升到Cubic的101%和93%(优于Cubic)。
