高层建筑应急情况下电梯群控算法研究

高层建筑带来城市景观的同时也带来安全问题,高层建筑发生应急情况时可以利用电梯运输效率高的特点进行人员疏散.文章依据高层建筑应急疏散特点,提出群控系统正常工作与应急工作两种工作模式,分析研究了电梯在应急情况下的交通流的特点,结合疏散路线提出电梯的应急疏散交通模式,采用静态分区内以最小侯梯时间为优化目标的应急群控算法.通过MATLAB面向对象编程技术对算法进行仿真分析,仿真结果表明,采用电梯进行应急疏散是可行和有效的.     

基于BP方法的企业核心竞争力关键因素探析

为了有效提升企业核心竞争力,对影响企业核心竞争力的关键因素进行识别和分析.依据人工神经网络理论,基于一较全面的企业核心竞争力评价指标体系,建立企业核心竞争力的人工神经网络专家模型,在此基础上构建一个识别企业核心竞争力关键影响因素的模型,是企业竞争战略的制定与实施的有益工具.对哈药集团进行实证研究表明,该模型能较好地识别哈药集团企业核心竞争力的关键影响因素,这对企业为提高核心竞争力如何进行有针对性的资源投入有较重要的借鉴价值.     

Highly stable novel inorganic hydrides from aqueous electrolysis and plasma electrolysis

After 10⁴ h of continuous aqueous electrolysis with K₂CO₃ as the electrolyte, highly stable novel inorganic hydride compounds such as KH KHCO₃ and KH were isolated and identified by time of flight secondary ion mass spectroscopy (ToF-SIMS). The existence of novel hydride ions was determined using X-ray photoelectron spectroscopy (XPS) and solid state magic-angle spinning proton nuclear magnetic resonance spectroscopy (¹H MAS NMR). A novel hydride ion formed by plasma electrolysis of a K₂CO₃, Rb₂CO₃, or Cs₂CO₃ electrolyte was also observed by high resolution visible spectroscopy at 407.0 nm corresponding to its predicted binding energy of 3.05 eV.     

基于事件触发的离散多智能体二分一致性

针对一阶离散多智能体系统,研究了事件触发控制下的二分一致性问题.首先考虑智能体间通信拓扑结构为无向连通结构平衡图的情形,针对各智能体设计事件触发控制,包括仅依赖于自身及邻居智能体采样状态的控制输入,以及仅依赖自身状态的事件触发条件,实现了对通信资源的节约利用.基于图论、离散系统稳定性理论,证明系统能够实现二分一致性.同时,合理设置控制输入及事件触发条件中参数,保证系统不存在Zeno现象.之后,进一步分析设计了包含有向生成树的结构平衡图下,多智能体系统的事件触发控制.最后利用仿真实例验证了理论结果的有效性.     

A maximum self-esteem degree based feedback mechanism for group consensus reaching with the distributed linguistic trust propagation in social network

This paper focuses on consensus reaching process (CRP) under social network in which the trust relationship expressed by linguistic information. A new feedback mechanism in social network group decision making (SN-GDM) is proposed, which mainly consists of the following two aspects: (1) The propagation of distributed linguistic trust is investigated to study trust relation among experts; (2) A maximum self-esteem degree based feedback mechanism is developed to produce personalized advice for reaching higher group consensus. To do so, a novel linguistic trust propagation method is proposed to obtain the complete trust relationship among group. The self-esteem degree is used to define the extent that an individual makes concessions. Then, a maximum self-esteem degree based optimal feedback mechanism is built to produce personalized advice to help inconsistent experts make change of their opinion. Its novelty lies in the establishment of an optimization model with the nonlinear group self-esteem degree function as the objective function while group consensus threshold as the restrictions. Therefore, the inconsistent experts will reach a group consensus with the minimum loss of self-esteem degree, and then, it achieves the optimal balance between individual self-esteem and group consensus. Finally, a ranking process is applied to derive the appropriate consensus solution.     

Two-stage stochastic minimum cost consensus models with asymmetric adjustment costs

When dealing with consensus cost problems with asymmetric adjustment costs, the uncertain scenarios with certain probabilities which are becoming a serious problem decision-makers have to face. However, existing optimization-based consensus models have failed to consider uncertain factors that could influence the final consensus and total consensus cost. In order to better deal with these issues, it is necessary to develop practical consensus optimal models. Thus, we establish three two-stage stochastic minimum cost consensus models with asymmetric adjustment costs that may eventually lead the way to better consensus outcomes. The impact of uncertain parameters (such as individual opinions, unit asymmetric adjustment costs, compromise limits, cost-free thresholds) are investigated by modeling three kinds of uncertain consensus models. We solve the proposed two-stage stochastic consensus problem iteratively using the L-shaped algorithm and show the convergence of the algorithm. Furthermore, a case of pollution control negotiations verifies the practicability of the proposed models. Moreover, the comparison of results with the L-shaped algorithm and CPLEX shows that the L-shaped algorithm is more effective in solving time. Some discussions and comparisons on local and global sensitivity analysis of the uncertain parameters are presented to reveal the features of the proposed models. Finally, the relationships between the minimum cost consensus model and minimum cost consensus models with asymmetric adjustment costs and the proposed models are also provided.     

基于备选投票机制的低时延PBFT改进研究

针对实用拜占庭容错算法PBFT共识时延高、视图切换效率低、动态性不足等问题,提出一种基于备选投票机制的低时延共识算法IPBFT。通过增设候补集合,使系统的共识节点能够支持动态增加和减少,同时优化视图切换协议,使算法能够在只有两个阶段的情况下完成共识过程,降低系统的通信开销。在此基础上,将算法的主节点选取方式改进为投票选举机制,在节点进行共识的过程中实现主节点的选举,从而减少视图切换所需的通信次数和时延。实验结果表明,IPBFT算法较原始PBET算法具有更低的共识时延和更高的吞吐量,并且能够较好地支持节点动态的加入或退出。     

网络攻击下双层结构多智能体系统一致性

研究了遭受网络攻击的双层结构多智能体系统的一致性问题。针对包含领导层和跟随者层的双层网络结构的多智能体系统,考虑了如下情况：领导层相邻智能体之间为友好合作关系,跟随者层相邻智能体之间既包含友好合作也包含对抗竞争关系,同时领导层与跟随者层中部分对应智能体之间存在牵制关系。分析了受网络攻击的领导层多智能体系统、跟随者层多智能体系统和双层网络结构多智能体系统的节点之间的一致性关系。基于线性矩阵不等式（LMI）、李雅普诺夫稳定性理论和图论等相关知识给出了领导层多智能体系统节点间实现一致,跟随者层多智能体系统节点间实现二分一致,以及双层结构的多智能体系统之间实现点对点二分一致的充分性判据。最后,给出了具体的数值仿真例子,实现了遭受网络攻击的双层结构多智能体系统的一致性,验证了所给出的判据的有效性。     

犹豫模糊群共识实现算法及其数据系统优选

针对犹豫模糊偏好关系（HFPR）可以在复杂的管理环境下全面描述专家的犹豫评价信息的优势,基于HFPR构建了一种犹豫模糊群共识实现算法,并将其应用于银行数据系统的选购过程中。引入一种新的一致性指数方法来衡量个体HFPR的一致性水平;为了提升群体专家对决策结果的满意度,设计了一种犹豫模糊群共识实现算法,该算法能够在群体HFPR达到共识水平的情况下保证个体HFPR仍然具有满意一致性;通过银行数据系统的选购实例和对比分析实验说明了提出的方法的实用性和有效性。