循环赛竞赛编排的算法实现

根据对抗性体育竞赛赛事编排的需要,结合球类等运动项目的组织规则和相关规定．运用数据库及网络技术,设计循环赛的比赛编排方法,同时赛事成绩信息通过通用运动会管理系统进行管理和发布,实现运动会的完全信息化管理。系统使大量繁琐的人工计算任务通过简单方便的操作便可以实现,大大减轻运动会组织人员的劳动强度,提高工作效率,保证数据的准确性、安全性。     

基于博弈论的社交网络的控制方法

社交网络虽然实现了网络化的人际信息交流和交友．但同时也存在着大量的例如个人隐私信息泄露等问题。面对这种情况,计算机学术界提出一种基于博弈论的能够避免泄露用户隐私信息的新型的社交网络的访问控制方法。就这一基于博弈论的社交网络控制方法进行相关的简述和分析,以便于人们了解和认识这种社交网络的博弈论控制方法。     

改进型时间触发嵌入式系统编程模式

对于成本敏感的嵌入式系统,通常因为资源有限而难以采用抢先式实时多任务操作系统。传统的基于超级循环的前后台编程方法和基于时间触发的合作式多任务编程方法对任务的划分需要较高的技巧。本文通过对基于时间触发合作式调度器的改进,建立了一种适用于小型嵌入式系统的通用编程模式,使这类系统的编程变得清晰、简单。     

A novel adaptive cooperative location algorithm for wireless sensor networks

To overcome the disadvantages of the location algorithm based on received signal strength indication(RSSI) in the existing wireless sensor networks(WSNs),a novel adaptive cooperative location algorithm is proposed.To tolerate some minor errors in the information of node position,a reference anchor node is employed.On the other hand,Dixon method is used to remove the outliers of RSSI,the standard deviation threshold of RSSI and the learning model are put forward to reduce the ranging error of RSSI and improve the positioning precision effectively.Simulations are run to evaluate the performance of the algorithm.The results show that the proposed algorithm offers more precise location and better stability and robustness.     

无线多跳网络中基于博弈论的协作激励机制研究

无线多跳网络中网络传输性能容易受到自私节点的影响。本文首先对目前的节点协作激励机制进行了总结,然后,针对分簇路由中簇间路由场景,运用博弈论中非合作博弈的思想,建立博弈模型以激励簇内节点通过协作通信的方式帮助簇头进行数据包的转发,最后给出了基于非合作博弈的激励机制中纳什均衡解的求解过程。     

模具敏捷制造系统研究

针对模具设计制造过程复杂、条件苛刻和单件或小批量生产的特点 ,论述了模具产业发展敏捷制造技术的必要性。提出了模具敏捷制造系统框架和基于STEP与特征技术实现信息集成与过程集成的运行机制。阐述了基于Internet/Intranet的开放式可视化协同工作平台的模具敏捷制造实施方案。     

In Silico Logical Modelling to Uncover Cooperative Interactions in Cancer

The multistep development of cancer involves the cooperation between multiple molecular lesions, as well as complex interactions between cancer cells and the surrounding tumour microenvironment. The search for these synergistic interactions using experimental models made tremendous contributions to our understanding of oncogenesis. Yet, these approaches remain labour-intensive and challenging. To tackle such a hurdle, an integrative, multidisciplinary effort is required. In this article, we highlight the use of logical computational models, combined with experimental validations, as an effective approach to identify cooperative mechanisms and therapeutic strategies in the context of cancer biology. In silico models overcome limitations of reductionist approaches by capturing tumour complexity and by generating powerful testable hypotheses. We review representative examples of logical models reported in the literature and their validation. We then provide further analyses of our logical model of Epithelium to Mesenchymal Transition (EMT), searching for additional cooperative interactions involving inputs from the tumour microenvironment and gain of function mutations in NOTCH.     

基于博弈论的制造网络联盟合作伙伴的监督及激励机制设置

制造网络联盟企业是一种动态联盟,传统的企业的行政管理方法不适用,需采用新的方法和理论来指导其运行和管理.本文在建立了制造网络联盟企业的监督博弈模型的基础上,用纯策略和混合策略博弈均衡的原理讨论了监督机制的设置原则.此外,利用信息经济学的委托-代理理论,通过引入盟主的监督惩罚函数建立了双方博弈委托-代理模型.求解该模型,得到最佳分配系数以激励合作伙伴的投入;并对该系数进行讨论得到三条监督激励机制,为盟主设置合理的监督激励机制提供了理论基础.     

An intelligent negotiator agent design for bilateral contracts of electrical energy

In this paper, an intelligent agent (using the Fuzzy SARSA learning approach) is proposed to negotiate for bilateral contracts (BC) of electrical energy in Block Forward Markets (BFM or similar market environments). In the BFM energy markets, the buyers (or loads) and the sellers (or generators) submit their bids and offers on a daily basis. The loads and generators could employ intelligent software agents to trade energy in BC markets on their behalves. Since each agent attempts to choose the best bid/offer in the market, conflict of interests might happen. In this work, the trading of energy in BC markets is modeled and solved using Game Theory and Reinforcement Learning (RL) approaches. The Stackelberg equation concept is used for the match making among load and generator agents. Then to overcome the negotiation limited time problems (it is assumed that a limited time is given to each generator–load pairs to negotiate and make an agreement), a Fuzzy SARSA Learning (FSL) method is used. The fuzzy feature of FSL helps the agent cope with continuous characteristics of the environment and also prevents it from the curse of dimensionality. The performance of the FSL (compared to other well-known traditional negotiation techniques, such as time-dependent and imitative techniques) is illustrated through simulation studies. The case study simulation results show that the FSL based agent could achieve more profits compared to the agents using other reviewed techniques in the BC energy market.     

基于MTPM和DPM的多无人机协同广域目标搜索滚动时域决策

传统的协同搜索决策方法在目标引导和机间协同方面存在不足. 研究建立了基于分布概率预测的目标概率图（Target probability map,TPM）初始化方法和基于贝叶斯准则的目标概率图动态更新方法,形成了修正目标概率图（Modified TPM,MTPM）及其运算机理.考虑对任务子区域进行可控回访,定义了数字信息素图（Digital pheromone map,DPM）,建立了数字信息素图使用方法及更新机理.设计了基于MTPM和DPM的寻优指标,建立了基于滚动时域控制的协同搜索决策方法（MTPM-DPM-RHC method,MDR）.仿真表明: 1） MTPM能有效降低对目标的虚警率和漏检率;2） DPM能有效实现对任务区域可控回访;3） MDR方法的遍历能力、重访能力和目标搜索效率均优于已有方法.