基于K近邻互信息估计的原油管道电耗预测

为使用最少的特征实现管道电耗的精准预测,建立基于K近邻互信息估计的BPNN模型来预测管道电耗.利用管道输送理论公式扩充原始数据集,利用K近邻互信息估计提取强相关性特征,将提取出的特征喂入BPNN来建立原油管道电耗预测模型,最后对比利用不同输入特征建立的模型的预测精度.研究结果表明:利用K近邻互信息估计能够选出多个与电耗相关的重要特征;利用相关性最强的前5个特征建立的BPNN预测模型时,模型的平均绝对百分比误差比利用单个特征建模时降低了39.28％,达到5.79％;该模型平均训练时间也比利用全部特征建模时缩短22.49％.证明K近邻互信息估计能够提取管道电耗的相关特征,与BPNN结合后能够实现管道电耗的准确预测.     

Collection efficiency of liquid‐based samplers for fungi in indoor air

This study assessed the collection efficiency (CE) of two popularly used sampling devices (BioSampler and Coriolis sampler) for fungal aerosols. Phosphate‐buffered saline (PBS) supplemented with or without surfactant (Tween‐20, Tween‐80, or Triton X‐100) and antifoam agent was prepared and used as collection liquids. The agar impactor (BioStage) was simultaneously operated with liquid‐based samplers to collect fungi from seven sites located at a university building, public library, and animal farming. Fungal concentrations determined by liquid samplers were divided by those by BioStage, and the ratio values represented CE. Results indicate that the CE of BioSampler was superior to that of Coriolis (P = 0.0001) and the PBS containing surfactant collected fungi better than that without surfactant (P < 0.0001), whereas antifoam agent showed no influence (P = 0.8). Moreover, fungal concentrations determined by BioSampler with surfactant‐added PBS were statistically indifferent from those by BioStage (P > 0.05) with a Spearman correlation coefficient of 0.81‐0.83 (P < 0.01). In addition to sampler and collection liquid, sampling location was also identified as a significant CE factor (P = 0.006), implying potential influences by fungal genera in the studied fields. Overall, BioSampler with surfactant‐supplemented PBS (eg, Triton X‐100) is recommended considering the great CE and compatibility with a variety of analytical assays.     

Synergetic improvement strategy on thermoelectric performance of CuAlO2 compacts

We fabricated Sr and Ca-doped CuAlO₂ compacts from the mixed powder of CuO, Cu₂O, Al₂O₃, and SrO or CaO by multi-pass hot pressing followed by spark plasma sintering (SPS). The XRD results showed the reaction of CuO, Cu₂O and Al₂O₃ was rather complete and only CuAlO₂ single phase was formed when the additive amount of SrO or CaO was appropriate. Multi-pass hot pressing increased the relative density and the usage of plate-like Al₂O₃ as reaction raw material enhanced the orientation degree. In spite of performance improvement conflicts through elemental doping, density increase and orientation improvement, the measurement on the thermoelectric performance indicated that the electrical resistivity, Seebeck coefficient, power factor, dimensionless figure of merit (ZT) were improved to varying degrees through the synergetic action of elemental doping, density increase, and orientation control. The highest power factor and ZT of the Ca-doped CuAlO₂ compacts reached 1.54?×?10^?4 W?m^?1 K^?2 and 0.015 at 973?K, respectively. The thermoelectric performance was higher than those of CuAlO₂ at the same temperature in published work before.     

基于注意力机制与文本信息的用户关系抽取

随着社交媒体的发展,用户之间的关系网络对于社交媒体的分析有很大的帮助。因此,该文主要研究用户好友关系检测。以往的关于用户好友关系抽取的研究主要基于社交媒体上的结构化信息,比如其他好友关系,用户的不同属性等。但是,很多时候用户本身并没有大量的好友信息存在,同时也不一定有很多确定的属性。因此,我们希望基于用户发表的文本信息来对用户关系进行预测。不同于以往的潜在好友推荐算法,该文提出了一种基于注意力机制以及长短时记忆网络(long short-term memory,LSTM)的好友关系预测模型,将好友之间的评论分开处理,通过分析用户之间的评论来判断是否具备一定的好友关系。该模型将好友双方信息拼接后的结果作为输入,并将注意力机制应用于LSTM的输出。实验表明,用户之间的评论对于好友关系预测确实有较大的实际意义,该文提出的模型较之于多个基准系统的效果,取得了明显的提升。在不加入任何其它非文本特征的情况下,实验结果的准确率达到了77%。     

镁钛复合处理对不锈钢凝固组织的影响及机制

摘要：TiN是铁素体不锈钢有效的异质形核剂，但钢中大尺寸的TiN颗粒会对不锈钢板材表面质量带来不利影响。为此，提出依靠镁钛复合处理来细化TiN颗粒及控制宏观晶粒的方法。通过良好气氛保护的电阻炉试验，研究了添加Mg和Ti元素对于铁素体不锈钢宏观铸态组织和TiN颗粒细化效果的影响规律，并对其细化机理进行了详细分析。经研究得知，向铁素体不锈钢中添加了微量Mg和Ti元素后试样宏观等轴晶比例由37%提高至50%，TiN颗粒平均尺寸由处理前的5μm细化至2μm。镁钛复合处理后，钢液中形成的MgO和MgAl2O4与TiN之间的晶格错配度很低，分别为1.14和5.29，均属于有效形核范围，可以成为TiN异质形核核心，促进在晶内均匀析出更多的TiN。同时基于TiN与铁素体相之间的良好的晶格匹配关系，其进一步促进了δ-Fe形核，从而有效细化了铁素体宏观组织，这将有利于提高铁素体不锈钢力学性能和表面质量。     

A Forecasting Framework Based on Kalman Filter Integrated Multivariate Local Polynomial Regression: Application to Urban Water Demand

Neural Processing Letters - In this study, a forecasting framework for daily urban water demand has been proposed. It was developed based on the extended Kalman filter (EKF) which consists of state...     

基于改进关联规则算法的警情数据分析

针对传统Apriori算法挖掘警情数据的缺点，提出一种改进的Apriori算法。该算法首先在关联规则发现阶段引入权值参数，设计支持度阈值函数，以挖掘不常发生的重大案情发生规律；然后提出一种压缩矩阵优化算法，将数据压缩存储在只有0或1的矩阵中，并用2个数组来记录矩阵中每一行及每一列1的总数，可多次压缩矩阵，提升挖掘效率；最后将改进的算法用于实际的警情数据挖掘分析，给出关联规则挖掘结果。实验表明，改进算法不仅执行效率较传统算法有所提升，且针对警情数据的挖掘结果准确性也有所提高。     

锚杆锯切设备自动化改造技术应用

通过对锚杆锯切设备的设计、改进情况进行总结，详细介绍了自动化改造前后的设备工作原理、结构组成以及各部分工作过程动作描述等内容，根据改造前后的各项数据统计分析，列出了自动化改造后产品质量、生产效率和企业的利润的变化，同时还有设备故障率、工人劳动强度、设备操作人员数量的减少以及工厂生产环境由污染型转变成节能环保型企业等相关内容，展示所取得的有益效果。     

基于连续介质损伤力学的7075铝合金高温成形极限理论预测与数值仿真

开展7075铝合金高温单向拉伸试验和成形极限试验，获得了不同温度和应变率的应力-应变曲线和成形极限曲线。结果表明，在较高的温度和应变率时7075铝合金的强度减小、成形性提高。为描述7075铝合金高温损伤演化过程，提出一种改进的连续介质损伤模型，并建立了耦合损伤的多轴统一黏塑性本构模型。基于试验结果，运用NSGAII遗传算法标定了模型中的参数，标定后的本构模型可以很好地预测7075铝合金的高温热力行为和极限应变。通过有限元软件Abaqus的用户材料子程序VUMAT，该本构模型被编入到Abaqus软件中进行数值仿真计算。结果表明，仿真获得的成形极限曲线和应变场分布与试验和理论结果吻合度好，进一步证明了所建立的耦合损伤的多轴本构模型的正确性及其在高温成形极限有限元仿真中的适用性。     

正偏心正交车铣精加工切削层几何形状研究

针对未考虑正偏心正交车铣切削层几何形状而导致难以全面反映正交车铣切削层几何形状变化规律的问题，基于正交车铣运动规律，在不考虑动力学影响的情况下，对切削层的形成过程进行了静态分析。建立的正偏心正交车铣切削层几何形状的解析模型涉及铣刀侧刃和底刃的切入/切出角度、切削厚度和切削深度。通过试验验证了该解析模型的正确性，并分析了切削参数对铣刀切削层的影响。研究结果为正偏心正交车铣切削层几何形状的变化提供了定量的分析依据，为切削力和颤振的研究提供了理论指导。