某办公建筑热舒适及能耗的正交法优化

以重庆某采用地板送风加辐射供冷空调系统办公房间为研究对象,考虑送风速度、送风温度、辐射顶板温度、辐射顶板安装高度等影响因素,以房间热舒适度和能量利用系数的综合评分为优化目标,运用正交法建立4因素3水平正交方案,通过数值计算和极差、方差分析得到各因素对综合评分影响次序,从而得到最优方案,并为此类型空调系统设计提供了参考.     

智能混合动力汽车经济性自适应巡航控制策略研究

针对智能混合动力汽车自适应巡航过程中的能量控制策略问题,结合模型预测控制在处理多目标、多约束优化问题方面的优势和粒子群算法运算量小、收敛快的特点,将粒子群算法作为模型预测控制的滚动优化方法,构造基于模型预测控制的粒子群算法.仿真结果表明,文中算法能够使绝大部分工况点落在较低燃油消耗率区域,只有少部分工况点落在非经济区域,虽然多消耗了1.06%的燃油,但在运算速度上却获得了60.3%的提升.     

基于泛函网络的组合推荐算法

在研究组合算法的基础上，提出一种基于泛函网络实现前融合推荐算法. 探讨Vague集条件下推荐算法的前融合问题，给出了基于泛函网络构架实现前融合组合推荐算法的一般过程. 通过推荐系统泛函拓朴结构的建立，利用泛函神经元的自学习、自组织和自适应能力，进一步优化推荐结果，较大地提高了系统的推荐准确度. 最后，将算法应用于Movielens推荐系统中，计算机仿真实验结果表明，本文提出的基于泛函网络实现前融合推荐算法是有效的、可靠的.     

游泳馆钢-木混合结构的体系选型和关键设计问题

崇明游泳馆采用钢?胶合木混合网壳结构。通过对胶合木力学特性和游泳馆结构静力的分析，计算屋面网壳结构钢和胶合木的合理应用范围。讨论了钢夹板木结构连接节点刚度对结构整体刚度的影响，并通过节点试验得到了节点的实际刚度。参考《空间网格结构技术规程》中关于网壳结构的稳定性分析和极限承载力的计算方法，考虑木材的材质缺陷和无塑性发展能力，钢?木混合网壳结构的弹塑性极限承载力安全系数建议取4.2。     

Driving Mechanism of Cotton Comber's Detaching Roller Based on Time-Sharing Unidirectional Drive

The high-speed reciprocating motion of a detaching roller limits the velocity of a cotton comber and affects the quality of comber slivers. The article has proposed a controllable time-sharing unidirectional hybrid drive mechanism after analyzing detaching roller＇s current numerical control drive method. The analysis focuses on the detaching roller motion required according to cotton comber＇s velocity and process. The double-servo motors of the mechanism consists of differential gear trains. The mechanism addresses the problem of increased servo motor power,and failure of promptly responded to the positive inversion process of mechanism driven by servo motors. A velocity calculation model of the detaching roller controllable drive mechanism will be generated by using superposition method and design of differential gear trains. The accuracy of the model will be verified using the test platform. This study has presented a reliable and practical high-speed drive mechanism and can be a reference to future studies on high-speed reciprocating motion drive.     

一种任意起始位姿的连续曲率泊车路径在线规划方法

针对目前泊车路径规划算法对起始位姿要求严格，且难以兼顾最终位姿精度、路径质量及计算效率等问题，提出了一种任意起始位姿的连续曲率路径在线规划方法。该方法将整个泊车路径规划分为库位内调整与入库过程两部分。库位内调整采用以最终位姿高精度与调整次数最少为目标函数的最优化方法进行逐段规划；入库过程采用连续曲率曲线组用于混合A*算法的状态节点扩展以直接生成无需后处理的可执行路径。设计考虑路径的曲率变化与方向改变次数的估价函数；采用由路径几何形状特征点构建特征多边形的碰撞检测方法以提高计算效率。离线仿真与实车试验结果验证了该方法的有效性。     

面向同源蛋白质探测的一种新型混合深度学习模型

根据蛋白质氨基酸链探测其同源蛋白质,进而预测蛋白质的功能,是生物信息学研究领域的一个重要挑战,也是众多生物医学研究领域的基础研究内容,有着重要的科研价值和广泛的应用需求。其研究难点在于:(1)如何学习对同源蛋白质预测有效、有用的蛋白质特征信息;(2)如何更好地运用蛋白质特征信息,实现同源蛋白质的探测与识别。为了解决同源蛋白质探测与识别研究中的关键难点,本文提出一种基于混合深度学习架构的同源蛋白质探测与识别模型(HDLM-PHP)。通过采用统一的"管道式"深度学习架构,将蛋白质特征学习和探测识别统一为一个整体,提高同源蛋白质探测与识别的效能。采用多组并行的深度卷积神经网络,学习蛋白质的各种属性信息,以期获得丰富的待检测蛋白质和靶蛋白质的高级相关性特征,并通过全连接方式使用多层RBM结构融合和精炼这些相关性特征为全局相关性特征。通过统一的深度网络连接方式,以探测和识别任务为导向,学习到对于同源蛋白质预测最有效、最全面的蛋白质特征信息。在标准数据集SCOPe上,对所提模型进行性能与效率评测,结果表明:本文提出的模型能有效地学习到符合任务导向的蛋白质特征数据,提升同源蛋白质探测与识别的准确度和召回率,优于现有的模型和算法。     

Hybrid Forecasting with Estimated Temporally Aggregated Linear Processes

We introduce a new strategy for the prediction of linear temporal aggregates; we call it ‘hybrid’ and study its performance using asymptotic theory. This scheme consists of carrying out model parameter estimation with data sampled at the highest available frequency and the subsequent prediction with data and models aggregated according to the forecasting horizon of interest. We develop explicit expressions that approximately quantify the mean square forecasting errors associated with the different prediction schemes and that take into account the estimation error component. These approximate estimates indicate that the hybrid forecasting scheme tends to outperform the so‐called ‘all‐aggregated’ approach and, in some instances, the ‘all‐disaggregated’ strategy that is known to be optimal when model selection and estimation errors are neglected. Unlike other related approximate formulas existing in the literature, those proposed in this paper are totally explicit and require neither assumptions on the second‐order stationarity of the sample nor Monte Carlo simulations for their evaluation. Copyright © 2014 John Wiley & Sons, Ltd.     

CoPt-Co hybrid supported on amino modified SiO_2 nanospheres as a high performance catalyst for hydrogen generation from ammonia borane

CoPt-Co hybrids were successfully supported on amino modified SiO_2 nanospheres by a chemical reduction method at a temperature of 278 K.The solid carrier i.e.amino modified SiO_2,provides numerous anchoring sites for the metal nanoparticles(NPs)to improve the dispersion while reducing the size of metal NPs.The supported NPs displayed a narrow particle size distribution on the SiO_2 surface with an average diameter of 12 nm.The XRD results alongside with the binary alloy phase diagram suggest that the resulted NPs are bimetallic,composed of CoPt and amorphous Co.Among the prepared materials,the solid with the specific composition of SiO_2@Pt_(0.1)Co_(0.9)was proved to be effective catalyst for ammonia borane(AB)hydrolysis in aqueous solution.The turnover frequency(TOF)value of the supported nanocatalyst was 25.59mol_(H_2)min~(-1)·mol_M~(-1),almost twice as that of unsupported Pt_(0.1)Co_(0.9)NPs while the activation energy was 37.05 kJ mol~(-1).Furthermore,the SiO_2@Pt_(0.1)Co_(0.9)composite manifested high catalytic activity even after five cycles of reuse.     

Banach空间中寻求(α,β)-适度混合集值映像吸引点的一般迭代格式

引入（α，β）-适度混合集值映像与条件I^*的概念，提出了用于寻求（α，β）-适度混合集值映像吸引点的一般迭代法.在一致凸Banach空间中，利用条件I^*与半紧性质，建立了所提（α，β）-适度混合集值映像的迭代格式的强收敛性.结论改进与修正了之前文献中已发布的相应结果.