求解鞍点问题的广义正定和反Hermitian分裂方法

探讨了如何求解大型稀疏鞍点问题,给出了一种基于正定分裂的广义正定和反Hermitian分裂(GPSS)方法。该方法首先利用矩阵的正定分裂,构造出鞍点矩阵的2种分裂格式;然后利用这2种分裂格式构造出GPSS迭代;接着给出了迭代收敛的充要条件。最后进行了数值对比实验,实验结果表明,GPSS比正定和反Hermitian分裂(PSS)和Hermitian和反Hermitian分裂(HSS)方法更有效。     

粒子群属性聚类的位置隐私保护

针对基于位置服务中连续查询情况下，用户自身属性信息很容易被攻击者获取，并通过关联获得用户位置隐私的情况，提出了一种利用粒子群聚类加速相似属性用户寻找，并由相似属性匿名实现用户位置泛化的隐私保护方法。该方法利用位置隐私保护中常用的可信中心服务器，通过对发送到中心服务器中的查询信息进行粒子群属性聚类，在聚类的过程中加速相似属性用户的寻找过程，由相似属性用户完成位置泛化，以此实现位置隐私保护。实验结果证明，这种基于粒子群属性聚类的隐私保护方法具有高于同类算法的隐私保护能力，以及更快的计算处理速度。     

Improving the prediction of petroleum reservoir characterization with a stacked generalization ensemble model of support vector machines

The ensemble learning paradigm has proved to be relevant to solving most challenging industrial problems. Despite its successful application especially in the Bioinformatics, the petroleum industry has not benefited enough from the promises of this machine learning technology. The petroleum industry, with its persistent quest for high-performance predictive models, is in great need of this new learning methodology. A marginal improvement in the prediction indices of petroleum reservoir properties could have huge positive impact on the success of exploration, drilling and the overall reservoir management portfolio. Support vector machines (SVM) is one of the promising machine learning tools that have performed excellently well in most prediction problems. However, its performance is a function of the prudent choice of its tuning parameters most especially the regularization parameter, C. Reports have shown that this parameter has significant impact on the performance of SVM. Understandably, no specific value has been recommended for it. This paper proposes a stacked generalization ensemble model of SVM that incorporates different expert opinions on the optimal values of this parameter in the prediction of porosity and permeability of petroleum reservoirs using datasets from diverse geological formations. The performance of the proposed SVM ensemble was compared to that of conventional SVM technique, another SVM implemented with the bagging method, and Random Forest technique. The results showed that the proposed ensemble model, in most cases, outperformed the others with the highest correlation coefficient, and the lowest mean and absolute errors. The study indicated that there is a great potential for ensemble learning in petroleum reservoir characterization to improve the accuracy of reservoir properties predictions for more successful explorations and increased production of petroleum resources. The results also confirmed that ensemble models perform better than the conventional SVM implementation.     

计及历史数据熵关联信息挖掘的短期风电功率预测

对风电功率历史数据进行关联信息挖掘,将有助于提高短期风电功率预测的准确度和计算效率。为解决风电功率预测模型的输入、输出变量的相关性冗余问题,尝试采用了一种基于信息熵和互信息的熵相关系数指标,旨在量化评估不同历史日风电样本与待预测日参考样本间的复杂非线性映射关系,并与线性相关系数、秩相关系数、欧氏距离指标进行了对比研究。同时,设计了一种BP神经网络改进模型,通过亲密样本筛选、隐含层结构寻优、网络权重赋初值等环节,克服了传统预测模型的训练数据冗余度大、收敛速度慢问题,提高了预测模型的泛化能力和计算效率。对某风电场实测数据的算例分析表明,所提出的方法在改善短期风电功率预测性能方面具有应用可行性。     

临界布尔网络的函数泛化问题研究

布尔网络是研究基因调控网络的一种非常重要的模型,通过时序数据推理基因之间的调控关系是研究网络动态行为和干预策略的基础.现有的预测研究主要集中在基因之间的调控关系,而对调控基因与目标基因之间的布尔函数的作用方式研究甚少.由于基因调控网络是一种处于有序和无序之间的临界网络,本文研究了众数规则、基于偏斜和基于互信息的三种泛化方法对临界布尔网络的稳态分布距离和灵敏度误差的影响.结果表明合理的泛化能够明显提高预测网络的稳态分布距离和灵敏度误差指标.三种泛化方法中,基于互信息的泛化方法的总体性能最好.     

Self-learning energy management for plug-in hybrid electric bus considering expert experience and generalization performance

A self-learning energy management is proposed for plug-in hybrid electric bus, by combining Q-Learning (QL) and Pontryagin's minimum principle algorithms. Different from the existing strategies, the expert experience and generalization performance are focused in the proposed strategy. The expert experience is designed as the approximately optimal reference state-of-charge (SOC) trajectories, and the generalization performance is enhanced by a multiply driving cycle training method. In specific, an efficient zone of SOC is firstly designed based on the approximately optimal reference SOC trajectories. Then, the agent of the QL is trained off-line by taking the expert experience as reference SOC trajectories. Finally, an adaptive strategy is proposed based on the well-trained agent. Specially, two different reward functions are defined. That is, the reward function in the off-line training mainly considers the tracking performance between the expert experience and the SOC, while mainly considering the punishment in the adaptive strategy. Simulation results show that the proposed strategy has good generalization performance and can improve the fuel economy by 22.49%, compared to a charge depleting-charge sustaining (CDCS) strategy.     

内蒙古白银沟铅锌矿地质特征及找矿方向

通过对白银沟铅锌矿区域地质概况、地质特征及成矿条件初步探讨和分析,认为该矿床赋存于上侏罗统满克头鄂博组与玛尼吐组地层中,成矿物质来源于上地幔或地壳深部,有利的赋矿构造是与寄生火山相连通的北西向张扭性构造破碎蚀变带,为今后的找矿指明了方向。     

汽车行业冲压厂的装箱料架规划与配置

根据冲压件的装箱方式及各车型零件间的相似性,对装箱料架进行分类,将其系列化、标准化。分析整车销量与冲压单批次产量之间的关系,总结出每年用于冲压周转所需的装箱料架总数的理论公式,对比总装箱料架的理论值和实际值,了解实际装箱料架数量是否已满足生产要求。根据装箱料架总数的变化趋势,调整冲压生产的频次,按此方式执行,消除装箱料架的闲置现象,大大提升了库房的有效利用率。     

Young infants' generalization of emotional expressions: Effects of familiarity.

From birth, infants are exposed to a wealth of emotional information in their interactions. Much research has been done to investigate the development of emotion perception, and factors influencing that development. The current study investigates the role of familiarity on 3.5-month-old infants' generalization of emotional expressions. Infants were assigned to one of two habituation sequences: in one sequence, infants were visually habituated to parental expressions of happy or sad. At test, infants viewed either a continuation of the habituation sequence, their mother depicting a novel expression, an unfamiliar female depicting the habituated expression, or an unfamiliar female depicting a novel expression. In the second sequence, a new sample of infants was matched to the infants in the first sequence. These infants viewed the same habituation and test sequences, but the actors were unfamiliar to them. Only those infants who viewed their own mothers and fathers during the habituation sequence increased looking. They dishabituated looking to maternal novel expressions, the unfamiliar female's novel expression, and the unfamiliar female depicting the habituated expression, especially when sad parental expressions were followed by an expression change to happy or to a change in person. Infants are guided in their recognition of emotional expressions by the familiarity of their parents, before generalizing to others. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Sequence of the most informative joints (SMIJ): A new representation for human skeletal action recognition

Much of the existing work on action recognition combines simple features with complex classifiers or models to represent an action. Parameters of such models usually do not have any physical meaning nor do they provide any qualitative insight relating the action to the actual motion of the body or its parts. In this paper, we propose a new representation of human actions called sequence of the most informative joints (SMIJ), which is extremely easy to interpret. At each time instant, we automatically select a few skeletal joints that are deemed to be the most informative for performing the current action based on highly interpretable measures such as the mean or variance of joint angle trajectories. We then represent the action as a sequence of these most informative joints. Experiments on multiple databases show that the SMIJ representation is discriminative for human action recognition and performs better than several state-of-the-art algorithms.