共查询到19条相似文献,搜索用时 500 毫秒
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化工过程变量通常具有较强的相关性,从多变量的角度研究过程参数报警阈值的优化具有实际意义。论文针对实际生产过程中存在着大量无效报警问题,结合多变量报警相关性分析,提出了一类多变量报警阈值优化设计的新方法。首先基于过程参数的历史数据,应用基于皮尔逊相关系数法的凝聚层次聚类方法对报警进行聚类分组,然后采用基于差异驱动原理的赋权方法对报警进行优先级排序,最后遵循报警优先级高优先处理的原则,结合漏报警及误报警概率建立过程报警阈值优化的目标函数,并采用数值优化的方法进行求解,得到最优的报警阈值。对于TE过程进行了实验,结果验证了所提方法的优势。 相似文献
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针对已有的多业务流多通道并行传输不支持业务流之间优先级的问题,将业务的优先级映射到多个通道,建立了具有优先级保证的多业务流多通道数据传输模型。基于排队论知识将模型抽象成多维Markov链,并使用两阶段的PH分布将多维Markov链近似成一维Markov链,采用矩阵分析方法对模型进行定量分析,推导出系统的平均队长和平均等待时间。通过数值分析与简单多业务流单通道、多优先级业务流单通道、简单多业务流多通道这三种传输模型进行了比较。结果表明,不管业务流达到率如何变化,多优先级业务流多通道并行传输模型中的高优先级数据包均能够获得较高的处理能力,说明了该模型能够支持多通道并行传输中业务流之间的优先控制。 相似文献
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针对多约束条件下的高超声速飞行器再入轨迹的优化问题,考虑多个具有不同重要性等级的优化指标,提出基于模糊多目标的轨迹设计方法.首先,利用直接配点法,将最优控制问题转化为带优先级的非线性多目标规划问题;然后,基于模糊满意优化的思想,根据更重要目标具有更高满意度的原则,将优先级表示为满意度序,并设计两步式优化模型.通过调节参数,能获得同时满足优化和重要性等级要求的最优轨迹.仿真结果表明了所提出方法的有效性. 相似文献
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针对任务具有特征参数多和特征参数不确定性的特点,提出了一种基于模糊理论的任务调度算法。利用模糊集合来描述任务的不确定性特征;使用多层模糊综合评判和最大隶属度原理来综合考虑任务的多个特征参数并确定任务的优先级;采用动态构建多层评判模型的调度策略来减小任务优先级评判的失效率。仿真表明,该算法提高了任务调度的成功率,降低了任务截止期的错失率和任务优先级评判的失效率。该方法可应用于优先等级有限的实时系统任务动态调度中。 相似文献
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本文分别提出多总线多处理机系统采用轮流优先级和循环优先级仲裁的分析模型。轮流优先级仲裁方案采用概率分析,循环优先级仲裁方案采用变更状态和参数分析。分析模型被用来对这二种不同仲裁方案进行性能分析和比较。某些结果表明循环优先级仲裁的总线访问延迟最小。 相似文献
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针对现有无线传感器网络多信道MAC协议没有区分数据业务优先级的问题,提出了一种基于区分服务的多信道协议(DP-McMAC)。该协议采用优先级调度策略和区分服务机制,对不同数据业务设置不同的退避参数和竞争窗口,并对提出的协议进行数学建模及延迟分析。仿真结果表明,该协议在高优先级数据的传输时延和吞吐量等性能方面比现有的协议均有所提高,并且保证了高优先级数据传输的实时性要求。 相似文献
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生产过程中,操作人员的操作经验影响生产效益和安全,为此本文结合双层预测控制中稳态目标计算思想,提出了一种具有优先级的实时在线决策支持系统.针对实际生产过程无法确定准确的代价系数的问题,引入操作优先级的思想,结合稳态目标计算层被控变量的优先级优化方法,计算最优操作目标(被控变量和操作变量),解决了模块多变量操作指导中每层模块无法区分变量重要性的问题,并说明了二者在结构上的相似性.最后给出应用本文提及的方法进行决策支持的一个例子,验证该方法的有效性. 相似文献
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基于多优先级的网络通信量的价控问题 总被引:1,自引:1,他引:0
在多优先级网络中,为了满足各个用户的发送要求,解决网络拥塞并且使用户和网络整体获益,讨论了多优先级网络中通信量的价控问题。使用Nasll平衡和Stackelberg策略,以价格控制为桥梁,调节用户在各优先级的发送量。在假设流量是不同优先级发送信息量函数的情况下,讨论了用户的盈余情况。不仅保证得到较满意的盈余值,而且能使网络更加平衡稳定地运行。改进了对已有的价控问题的研究,从而也可以更加合理、有效地利用网络。仿真结果说明了此方法的适用性。 相似文献
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User participation is one of the most important elements in participatory sensing application for providing adequate level of service quality. However, incentive mechanism and its economic model for user participation have been less addressed so far in this research domain. This paper studies the economic model of user participation incentive in participatory sensing applications. To stimulate user participation, we design and evaluate a novel reverse auction based dynamic pricing incentive mechanism where users can sell their sensing data to a service provider with users’ claimed bid prices. The proposed incentive mechanism focuses on minimizing and stabilizing the incentive cost while maintaining adequate level of participants by preventing users from dropping out of participatory sensing applications. Compared with random selection based fixed pricing incentive mechanism, the proposed mechanism not only reduces the incentive cost for retaining the same number of participants but also improves the fairness of incentive distribution and social welfare. It also helps us to achieve the geographically balanced sensing measurements and, more importantly, can remove the burden of accurate price decision for user data that is the most difficult step in designing incentive mechanism. 相似文献
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针对用户创新社区中未考虑企业激励机制对领先用户知识共享行为影响的问题,提出一种基于演化博弈的领先用户知识共享行为激励机制。首先,将企业和领先用户作为博弈主体,分别构建企业未采取激励措施和企业采取激励措施条件下的演化博弈模型;其次,分别对两个模型进行局部稳定性分析,以探讨系统的动态演化过程与演化稳定策略;最后,通过计算机模拟仿真,对比两种条件下领先用户知识共享行为的演化结果,分析领先用户知识共享行为的影响因素及最佳激励策略。实验结果表明,企业采取激励措施可以有效促进领先用户的知识共享行为,并且将激励分配系数控制在一定范围内时系统将达到最佳的稳定状态;最佳激励分配系数大小由知识共享成本、知识搜索成本及额外成本共同决定;知识共享成本、知识搜索成本以及激励分配系数会显著影响领先用户知识共享行为的水平。 相似文献
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提出一种基于用户偏好的激励机制,鼓励用户通过提供共享文件和转发操作为系统做出贡献。IMBPC结合了虚拟价格机制和预期文件传输延时,基于用户对价格和延时的偏好度来选择最合适的节点进行文件下载。通过设置模拟实同仅通过虚拟价格机制来激励用户做出贡献的策略进行比较,显示应用IMBPC策略的系统,节点的贡献积极性明显增加。 相似文献
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Participatory smartphone sensing has lately become more and more popular as a new paradigm for performing large-scale sensing, in which each smartphone contributes its sensed data for a collaborative sensing application. Most existing studies consider that smartphone users are strictly strategic and completely rational, which try to maximize their own payoffs. A number of incentive mechanisms are designed to encourage smartphone users to participate, which can achieve only suboptimal system performance. However, few existing studies can maximize a system-wide objective which takes both the platform and smartphone users into account. This paper focuses on the crucial problem of maximizing the system-wide performance or social welfare for a participatory smartphone sensing system. There are two great challenges. First, the social welfare maximization cannot be realized on the platform side because the cost of each user is private and unknown to the platform in reality. Second, the participatory sensing system is a large-scale real-time system due to the huge number of smartphone users who are geo-distributed in the whole world. A price-based decomposition framework is proposed in our previous work (Liu and Zhu, 2013), in which the platform provides a unit price for the sensing time spent by each user and the users return the sensing time via maximizing the monetary reward. This pricing framework is an effective incentive mechanism as users are motivated to participate for monetary rewards from the platform. In this paper, we propose two distributed solutions, which protect users’ privacy and achieve optimal social welfare. The first solution is designed based on the Lagrangian dual decomposition. A poplar iterative gradient algorithm is used to converge to the optimal value. Moreover, this distributed method is interpreted by our pricing framework. In the second solution, we first equivalently convert the original problem to an optimal pricing problem. Then, a distributed solution under the pricing framework via an efficient price-updating algorithm is proposed. Experimental results show that both two distributed solutions can achieve the maximum social welfare of a participatory smartphone system. 相似文献
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《Computer Networks》2007,51(12):3380-3391
The ability to reserve network bandwidth is a critical factor for the success of high-performance grid applications. Reservation of lightpaths in dynamically switched optical networks facilitates guaranteed bandwidth. However, reservation of bandwidth can often lead to bandwidth fragmentation which significantly reduces system utilization and increases the blocking probability of the network. An interesting approach to mitigating this problem is to induce quasi-flexibility in the user requests. A smart scheduling strategy can then exploit this quasi-flexibility and optimize bandwidth utilization. However, there has to be an incentive for flexibility from the user’s perspective as well. In this paper, we explore how the network service provider (NSP) can influence user flexibility by dynamically engineering pricing incentives. Ultimately, user flexibility will lead to efficient network utilization, reduce the price for the users, and increase the revenue for the NSP. 相似文献
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《Expert systems with applications》2014,41(8):3726-3735
Defining appropriate pricing strategy for smart environment is important and complex task at the same time. It holds the primal fraction in Demand Response (DR) program. In our work, we devise an incentive based smart dynamic pricing scheme for consumers facilitating a multi-layered scoring rule. The proposed strategy characterizes both incentive based DR and price based DR programs facilities. This mechanism is applied between consumer agents (CA) to electricity provider agent (EP) and EP to Generation Company (GENCO). Based on the Continuous Ranked Probability Score (CRPS), a hierarchical scoring system is formed among these entities, CA–EP–GENCO. As CA receives the dynamic day-ahead pricing signal from EP, it will schedule the household appliances to lower price period and report the prediction in a form of a probability distribution function to EP. EP, in similar way reports the aggregated demand prediction to GENCO. Finally, GENCO computes the base discount after running a cost-optimization problem. GENCO will reward EP with a fraction of discount based on their prediction accuracy. EP will do the same to CA based on how truthful they were reporting their intentions on device scheduling. The method is tested on real data provided by Ontario Power Company and we show that this scheme is capable to reduce energy consumption and consumers’ payment. 相似文献