Probabilistic heuristic estimates

Though they constitute the major knowledge source in problem-solving systems, no unified theory of heuristics has emerged. Pearl [15] defines heuristics as criteria, methods, or principles for deciding which among several alternative courses of action promises to be the most effective in order to achieve some goal. The absence of a more precise definition has impeded our efforts to understand, utilize, and discover heuristics. Another consequence is that problem-solving techniques which rely on heuristic knowledge cannot be relied upon to act rationally — in the sense of the normative theory of rationality.To provide a sound basis for BPS, the Bayesian Problem-Solver, we have developed a simple formal theory of heuristics, which is general enough to subsume traditional heuristic functions as well as other forms of problem-solving knowledge, and to straddle disparate problem domains. Probabilistic heuristic estimates represent a probabilistic association of sensations with prior experience — specifically, a mapping from observations directly to subjective probabilities which enables the use of theoretically principled mechanisms for coherent inference and decision making during problem-solving. This paper discusses some of the implications of this theory, and describes its successful application in BPS.This research was made possible by support from Heuristicrats, the National Aeronautics and Space Administration, and the Rand Corporation.     

融合信任关系与评论文本的矩阵分解推荐算法

针对推荐系统中用户评分数据稀疏所导致推荐结果不精确的问题,本文尝试将用户评分、信任关系和项目评论文本信息融合在概率矩阵分解方法中以缓解评分数据稀疏性问题.首先以共同好友数目及项目流行度改进皮尔逊用户偏好相似程度并将其作为用户间的直接信任值,然后考虑用户间信任传播过程中所有路径的影响构建新的信任网络;其次通过BERT预训练(Pre-training of Deep Bidirectional Transformers for Language Understanding)模型提取项目的评论文本向量,构造项目的评论文本特征矩阵;最后基于概率矩阵分解(Probabilistic Matrix Factorization,PMF)模型融合用户的评分数据、用户的信任关系以及项目的评论文本信息进行推荐.通过不断的理论分析并在真实的Yelp数据集上进行实验验证,均表明本文算法的有效性.     

Integer-multiple-spacing-based scheduling for multimedia applications in IEEE 802.11e HCCA wireless networks

This paper is concerned with improving bandwidth utilization while guaranteeing quality-of-service (QoS) requirements for multimedia applications in IEEE 802.11e HCCA wireless networks. We propose two integer-multiple-spacing-based (IMS-based) designs: the IMS-based-δ and IMS-based-l designs. In the IMS-based designs, the scheduling spacing of any traffic must be an integer multiple of the minimum spacing. The IMS-based designs have more potential to improve the bandwidth utilization because they schedule traffic with longer spacings compared with the prior designs. Besides the improvement of the bandwidth utilization, the IMS-based-δ design can guarantee the packet delay requirements, where a δ factor is introduced to ensure that the bandwidth utilization must benefit from longer spacings, while the IMS-based-l design can guarantee the packet loss requirements. Numerical results show that the improvement of the bandwidth utilization for the IMS-based-δ and -l designs can be up to 7.7% and 56% or more, respectively, compared with the prior designs.     

Dependence tree structure estimation via copula

We propose an approach for dependence tree structure learning via copula. A nonparametric algorithm for copula estimation is presented. Then a Chow-Liu like method based on dependence measure via copula is proposed to estimate maximum spanning bivariate copula associated with bivariate dependence relations. The main advantage of the approach is that learning with empirical copula focuses on dependence relations among random variables, without the need to know the properties of individual variables as well as without the requirement to specify parametric family of entire underlying distribution for individual variables. Experiments on two real-application data sets show the effectiveness of the proposed method.     

人群头发元素分布及某些特征研究

本文介绍用堆中子活化分析法测定人群头发中I、Br、Mg、Mn、Cu、Na、V、Cl、Al、Ca、S等11种元素。研究人发中元素分布特征、相关性特征、性别年令分布特征。方法学中还从法庭科学应用角度介绍同一性识别中差异率和重合几率的双判据方法。     

考虑电动汽车停泊概率的配电网接纳电动汽车能力评估方法

针对规模化电动汽车无序充电易导致配电网电压及潮流越限,需要定量评估配电网接纳电动汽车的能力问题,提出考虑电动汽车停泊概率的配电网接纳能力评估方法。首先在充电负荷建模环节增加考虑电动汽车停泊概率的影响,采用二阶段方法确定充电负荷所在节点;其次对基础负荷的季节特性进行建模,以研究由此导致的配电网接纳能力季节差异;建立了考虑静态安全约束的接纳能力评估模型,采用机会约束消除充电负荷预测偏差对评估准确度的影响。最后通过算例验证了所提评估方法的有效性。     

考虑源荷不确定性的电热系统联合调度

针对风电和电热负荷不确定的问题,提出计及源荷不确定性的旋转备用容量的优化方法,建立考虑电热备用耦合影响的调度模型。在日前阶段,以能源与负荷的预测量制定机组的出力方案,风电由于其预测精度较低,利用Beta概率密度函数来拟合风电出力,从而确定风电的不确定性带来的旋转备用容量,利用机会约束规划来处理不确定问题;负荷有较高的预测精度,但其波动性较强,使用概率场景生成和削减的方法制定不同场景下负荷备用需求的调整量,以日运行成本最低建立目标函数,运用改进的粒子群算法在IEEE30节点系统上验证了所提模型的经济性和鲁棒性。     

一种基于风险传播的信息系统风险评估方法

传统信息系统的风险评估方法未考虑节点的状态变化和风险的传播方向,且评估结果的准确性受专家主观性的影响,对此,提出了一种基于风险传播的信息系统风险评估方法.首先,确定节点的初始状态转移概率矩阵,并根据攻击属性对矩阵进行修正,得到节点状态转移概率;其次,基于系统风险传播网络拓扑图和节点属性值计算节点在各方向的传播概率;然后,利用三参数区间数方法获取节点威胁事件的量化值;最后,根据风险评估方法计算各节点的风险值.实验结果表明,基于风险传播方法的评估流程更客观、合理,可提高信息系统风险评估的整体性和准确性.     

基于概率密度逼近的无监督特征排序*

依据概率密度逼近提出了一种新的无监督特征排序,应用于特征选择降维.实验证明,这种方法与一些现有的方法相比,更为有效.     

具有中介状态和失效相关时 表决工程系统的可靠性分析

传统的模糊可靠性理论由于引入了模糊工作状态,因素处理方法不断细化,使得分析模型越来越复杂,计算方法过于烦琐,难以为工程实际所应用,特别是对于表决工程系统。采用具有“安全-中介-失效”三级工作模式的单元和系统的可靠性分析方法,运用随机事件的S并运算和T交运算规则,给出了具有中介状态的表决工程系统可靠性向量的计算方法和步骤,可靠性分析的结果是求出系统的安全概率（可靠度）PR、中介概率PM和失效概率PF,并构成可靠性向量［PR,PM,PF］。同时考虑了系统各单元间失效相关性问题,合理地给出单元间的失效相关性参数λ∈［0,1］之值,并利用Sλ和Τλ算子计算考虑各结构失效相关性时表决工程系统的可靠性向量。