组合隔板式鱼道水力特性数值模拟研究

鱼道是为鱼类提供洄游通道的一种重要的工程措施。基于Flow-3D采用标准RNG k-ε紊流模型和Tru-VOF追踪自由液面方法,对鱼道池室内流场进行三维紊流数值模拟,研究池室内水流流速、流态空间分布,分析鱼道的水力特性对目标鱼类洄游上溯的影响。结果表明:溢流堰与竖缝组合隔板式鱼道在设计流速v=0.75 m/s条件下,竖缝处平均流速为0.83 m/s,竖缝处流速分布范围为0.76~0.89 m/s;堰上流速为0.90~1.12 m/s,回流区流速分布范围为0.09~0.25 m/s,流速大小在鱼类的克流能力范围之内,但靠竖缝隔板处存在明显的主流贴壁现象。为此开展了池室优化方案设计,使鱼道池室流态满足鱼类上溯要求。     

基于多尺度自回归模型体系的混凝土坝位移预报及工程应用

针对混凝土坝位移监测数据的时频非线性特征严重影响到数值模型预报精度的难题,通过小波技术解析原型数据中多重交叉环境驱动的效应实况,有机结合非线性自回归模型(Nonlinear Autoregressive Model with Exogenous Input, NARX)和差分整合移动平均自回归模型(Autoregressive Integrated Moving Average Model, ARIMA),建立了多尺度组合机制下的自回归模型体系,解决了内蕴复杂混沌特性的监测序列的信息挖掘难点。工程实例分析表明,所建模型的拟合精度及预测能力均得以提升,相比于传统模型具有较好的抗噪性和鲁棒性。此外,所建立的计算模型经一定的优化和拓展,亦可推广应用于其它水工建筑物的效应预报分析。     

洪水预报智能模型在中国半干旱半湿润区的应用对比

为探究不同洪水预报智能模型在我国半干旱半湿润区的应用效果,选用决策树、多层感知器、随机森林和支持向量机4种模型在陕西省3个典型流域进行逐时洪水预报;选择相关系数、纳什效率系数、均方根误差、平均绝对误差和相对误差等评价指标,比较不同预见期下4种模型在半干旱半湿润典型流域洪水预报的适用性。结果表明:在短预见期预报中,4种模型在半湿润区典型流域均可获得较高的预报结果,在半干旱典型流域模拟精度相对偏低,仅支持向量机模型满足预报要求;随着预见期延长,不同模型性能变化差异大,支持向量机模型整体稳定,在小流域实时洪水预报中具有明显优势;随机森林模型与决策树模型精度随预见期延长而缓慢下降,前者适应性更好;多层感知器模型精度随预见期延长而骤减,模型稳定性较差。     

基于级差最大化组合赋权法的地下水功能评价

针对地下水功能评价中单独采用主观赋权法或客观赋权法存在的问题,结合二者的优点,采用基于主观赋权的层次分析法与客观赋权的熵权法相结合的级差最大化组合赋权法评价地下水功能,并通过计算不同赋权方法权重结果与平均值的相对偏差来衡量级差最大化组合赋权法的准确性。将该方法应用于伊犁河谷西北部平原区浅层地下水功能评价,评价结果基本符合评价区实际情况,验证了该评价方法在地下水功能评价中的可行性。     

Selection of optimized features for fusion of palm print and finger knuckle‐based person authentication

The impact of digital technology in biometrics is much more efficient at interpreting data than humans, which results in completely replacement of manual identification procedures in forensic science. Because the single modality‐based biometric frameworks limit performance in terms of accuracy and anti‐spoofing capabilities due to the presence of low quality data, therefore, information fusion of more than one biometric characteristic in pursuit of high recognition results can be beneficial. In this article, we present a multimodal biometric system based on information fusion of palm print and finger knuckle traits, which are least associated to any criminal investigation as evidence yet. The proposed multimodal biometric system might be useful to identify the suspects in case of physical beating or kidnapping and establish supportive scientific evidences, when no fingerprint or face information is present in photographs. The first step in our work is data preprocessing, in which region of interest of palm and finger knuckle images have been extracted. To minimize nonuniform illumination effects, we first normalize the detected circular palm or finger knuckle and then apply line ordinal pattern (LOP)‐based encoding scheme for texture enrichment. The nondecimated quaternion wavelet provides denser feature representation at multiple scales and orientations when extracted over proposed LOP encoding and increases the discrimination power of line and ridge features. To best of our knowledge, this first attempt is a combination of backtracking search algorithm and 2D²LDA has been employed to select the dominant palm and knuckle features for classification. The classifiers output for two modalities are combined at unsupervised rank level fusion rule through Borda count method, which shows an increase in performance in terms of recognition and verification, that is, 100% (correct recognition rate), 0.26% (equal error rate), 3.52 (discriminative index), and 1,262 m (speed).     

一种鲁棒性的少样本学习方法

少样本学习是目前机器学习研究领域的一个热点,它能在少量的标记样本中学习到较好的分类模型.但是,在噪声的不确定环境中,传统的少样本学习模型泛化能力弱.针对这一问题,提出一种鲁棒性的少样本学习方法RFSL(Robust Few-Shot Learning).首先,使用核密度估计(Kernel Density Estimation,KDE)和图像滤波(Image Filtering)方法在训练集中加入不同的随机噪声,形成多个不同噪声下的训练集,并分别生成支持集和查询集.其次,利用关系网络的关系模块通过训练集端到端地学习多个基分类器.最后,采用投票的方式对各基分类器的最末Sigmoid层非线性分类结果进行融合.实验结果表明,RFSL模型可促进小样本学习快速收敛,同时,与R-Net以及其他主流少样本学习方法相比,RFSL具有更高的分类准确率,更强的鲁棒性.     

多重不确定的密码体制研究

针对现有密码体制中只有密钥不确定的特点,文章提出了多重不确定密码体制的概念,指出了可能实现的一些途径。文章分析了其优势,指出这类密码体制在大大增强安全性的同时,其可能带来的运算量的增加是可以忽略的。     

Parallel heap: An optimal parallel priority queue

We describe a new parallel data structure, namely parallel heap, for exclusive-read exclusive-write parallel random access machines. To our knowledge, it is the first such data structure to efficiently implement a truly parallel priority queue based on a heap structure. Employing p processors, the parallel heap allows deletions of (p) highest priority items and insertions of (p) new items, each in O(log n) time, where n is the size of the parallel heap. Furthermore, it can efficiently utilize processors in the range 1 through n.This work was supported by U.S. Army's PM-TRADE contract N61339-88-g-0002, Florida High Technology and Industry grant 11-28-716, and Georgia State University's internal research support during spring and summer quarters, 1991.     

一种简化的三维模糊制器

针对三维模糊控制器规则多,结构复杂,难以实现的问题,提出了一种简化的三维模糊控制器。该方法是把三个输入量分别为偏差、偏差变化、偏差的偏差变化的一维模糊控制器加权融合实现简化的三维模糊控制器。并提出了根据不同类型的被控对象设置三个加权系数。加权系数具有粗调、细调和微调的作用,类似于传统PID调节器的比例、积分和微分,实现对系统静差的消除。     

基于图像内容层次表征的遥感图像 分割方法

提出基于图像内容层次表征的高分辨率遥感图像快速多精度分割方法。首先根据初始分割结果建立区域邻接图(RAG),并将其定义为马尔可夫随机场(MRF);然后引入光谱、形状和边缘等图像特征进行层次合并,通过记录层次合并过程获得图像内容的层次表征;最后根据层次表征中不同层级对象之间的关系快速生成任意不同精度的分割结果,以满足不同应用的需求。利用QuickBird卫星图像进行实验和评价的结果表明,本文方法具有较高的精度和效率。