复合布尔函数中含某单乘积项的快速判定算法

引入了布尔函数的基本积、单乘积项等概念，通过实例剖析了复合布尔函数中是否含某一单乘积项的一般判定方法，在该基础上提出了一种快速判定途径，并给出了快速判定算法的具体描述，同时对算法进行了实验，结果表明该算法快速有效。     

部件试验模态综合的简便方法

本文将一种基于完备模态基的模态综合技术应用于子结构的试验模态综合,获得成功。这种半试验半理论的模态综合方法是一种较为简便的、要求试验工作量较小的试验模态综合法,因为它只要求测量子结构的振动模态和频率即可。数值仿真结果表明,这种简便的试验模态综合法是行之有效的。     

软土地基水泥搅拌桩室内配合比试验分析

对广州南沙某工程软土地基搅拌桩室内不同配比的水泥土标准试件进行对比试验,研究软土地基搅拌桩施工中水泥、石膏等添加剂的最佳配比方案,对指导搅拌桩的现场施工有着重要的意义。     

Kernel-based least squares policy iteration for reinforcement learning.

In this paper, we present a kernel-based least squares policy iteration (KLSPI) algorithm for reinforcement learning (RL) in large or continuous state spaces, which can be used to realize adaptive feedback control of uncertain dynamic systems. By using KLSPI, near-optimal control policies can be obtained without much a priori knowledge on dynamic models of control plants. In KLSPI, Mercer kernels are used in the policy evaluation of a policy iteration process, where a new kernel-based least squares temporal-difference algorithm called KLSTD-Q is proposed for efficient policy evaluation. To keep the sparsity and improve the generalization ability of KLSTD-Q solutions, a kernel sparsification procedure based on approximate linear dependency (ALD) is performed. Compared to the previous works on approximate RL methods, KLSPI makes two progresses to eliminate the main difficulties of existing results. One is the better convergence and (near) optimality guarantee by using the KLSTD-Q algorithm for policy evaluation with high precision. The other is the automatic feature selection using the ALD-based kernel sparsification. Therefore, the KLSPI algorithm provides a general RL method with generalization performance and convergence guarantee for large-scale Markov decision problems (MDPs). Experimental results on a typical RL task for a stochastic chain problem demonstrate that KLSPI can consistently achieve better learning efficiency and policy quality than the previous least squares policy iteration (LSPI) algorithm. Furthermore, the KLSPI method was also evaluated on two nonlinear feedback control problems, including a ship heading control problem and the swing up control of a double-link underactuated pendulum called acrobot. Simulation results illustrate that the proposed method can optimize controller performance using little a priori information of uncertain dynamic systems. It is also demonstrated that KLSPI can be applied to online learning control by incorporating an initial controller to ensure online performance.     

电梯交通系统(Ⅰ)──电梯交通配置现状及发展

本文对国内外电梯交通配置设计现状及发展趋势作了论述。指出了由统计特性描述进入到采用专家系统和模糊规则的动态特性描述这一总的发展趋势。     

振动沉管挤密碎石桩在闸基处理中的应用

振动沉管挤密碎石桩是近十几年来在挤密砂桩和振冲桩的基础上发展起来的地基处理新技术,具有设备简单、操作方便、成本低、施工快、无污染等特点，被工程界广泛使用，积累了一定的工程经验。其在共产主义闸地基处理中的应用即为一例。     

关于移动平均过程两系数的推导

对经济预测方法中两公式给出了证明，两公式的系数被显式推导出来，这两个公式是时间序列模型公式，广泛用于经济预测之中，但文献上很难找到推导过程，本文的证明是基本的，无需高深数学知识即可理解．     

遥感数据时空融合技术在农作物监测中的适应性研究

受卫星回访周期及云的影响,大范围研究区同一时期的Landsat卫星数据很难获取,因而国内外学者提出了遥感影像时空融合技术。以石河子为实验区,利用STARFM(Spatial and Temporal Adaptive Reflectance Fusion Model)模型融合生成了高时空分辨率TM影像,对不同作物类型真实反射率与融合影像反射率作相关性分析,分析了遥感数据时空融合技术在新疆农作物监测中的适用性。结果表明:利用STARFM模型模拟得到的融合影像与真实影像间的相关性较高,但当地物类型发生变化时,融合影像与真实影像间将存在明显的差异。地物类型变化作物融合影像反射率与真实影像反射率间的相关性较小。     

Action recognition by hidden temporal models

We focus on the recognition of human actions in uncontrolled videos that may contain complex temporal structures. It is a difficult problem because of the large intra-class variations in viewpoint, video length, motion pattern, etc. To address these difficulties, we propose a novel system in this paper that represents each action class by hidden temporal models. In this system, we represent the crucial action event per category by a video segment that covers a fixed number of frames and can move temporally within the sequences. To capture the temporal structures, the video segment is described by a temporal pyramid model. To capture large intra-class variations, multiple models are combined using Or operation to represent alternative structures. The index of model and the start frame of segment are both treated as hidden variables. We implement a learning procedure based on the latent SVM method. The proposed approach is tested on two difficult benchmarks: the Olympic Sports and HMDB51 data sets. The experimental results reveal that our system is comparable to the state-of-the-art methods in the literature.     

Visualizing and understanding graph convolutional network

Multimedia Tools and Applications - The graph convolutional network (GCN), which can handle graph-structured data, is enjoying great interest in recent years. However, while GCN achieved remarkable...