基于Boost消息机制研究与实现

消息通信机制可以有效的简化系统设计,增强系统的可扩展性。Boost Signal/Slot机制,为在进行消息机制开发提供了有力的工具。以Boost为基础,分析了Boost消息机制的实现方式,通过引入一个简单实例,演示了利用Boost构造消息机制的基本方法。     

水库周边违建问题清查整治中的依法行政与权利救济

针对临近水库的别墅等建筑物的清查整治,在实体层面,尤其对于五证齐全的建筑物,如何定性为违建需要慎重把握,对水库管理范围的界定是一个重点问题;在程序层面,应避免执法中因急于求成而催生的程序违法.强拆行为会产生重大损失,涉及多方主体和多重法律关系,应理清其中各方的法律责任,妥善解决纠纷.     

Simple Question Answering over Knowledge Graph Enhanced by Question Pattern Classification

Knowledge and Information Systems - Question answering over knowledge graph (KGQA), which automatically answers natural language questions by querying the facts in knowledge graph (KG), has drawn...     

A two-stage adaptive multi-fidelity surrogate model-assisted multi-objective genetic algorithm for computationally expensive problems

Surrogate model-assisted multi-objective genetic algorithms (MOGA) show great potential in solving engineering design problems since they can save computational cost by reducing the calls of expensive simulations. In this paper, a two-stage adaptive multi-fidelity surrogate (MFS) model-assisted MOGA (AMFS-MOGA) is developed to further relieve their computational burden. In the warm-up stage, a preliminary Pareto frontier is obtained relying only on the data from the low-fidelity (LF) model. In the second stage, an initial MFS model is constructed based on the data from both LF and high-fidelity (HF) models at the samples, which are selected from the preliminary Pareto set according to the crowding distance in the objective space. Then the fitness values of individuals are evaluated using the MFS model, which is adaptively updated according to two developed strategies, an individual-based updating strategy and a generation-based updating strategy. The former considers the prediction uncertainty from the MFS model, while the latter takes the discrete degree of the population into consideration. The effectiveness and merits of the proposed AMFS-MOGA approach are illustrated using three benchmark tests and the design optimization of a stiffened cylindrical shell. The comparisons between the proposed AMFS-MOGA approach and some existing approaches considering the quality of the obtained Pareto frontiers and computational efficiency are made. The results show that the proposed AMFS-MOGA method can obtain Pareto frontiers comparable to that obtained by the MOGA with HF model, while significantly reducing the number of evaluations of the expensive HF model.

     

Compiler-directed scratchpad memory data transfer optimization for multithreaded applications on a heterogeneous many-core architecture

The Journal of Supercomputing - The heterogeneous many-core architecture plays an important role in the fields of high-performance computing and scientific computing. It uses accelerator cores with...     

Incorporating Actor-Critic in Monte Carlo tree search for symbolic regression

Neural Computing and Applications - Most traditional genetic programming methods that handle symbolic regression are random algorithms without memory and direction. They repeatedly search for the...     

航天器用实时操作系统设计

针对航天器在应用实时操作系统时的特殊需要,设计了航天器用实时操作系统的总体设计方案及内核;总体设计中,将操作系统分为板卡级驱动层、系统内核层、接口层三个层次,并确定了满足航天器任务的最简需求与各层的关系;在内核设计中,设计了双向链表管理器、多任务调度管理器、时钟管理器、消息队列管理器、中断管理器,并在其中体现了最简设计的思想;最后,对航天器用实时操作系统的可靠性设计思路进行了描述;此操作系统目前已应用多个航天器中。     

煤矿管道瓦斯流量计量技术研究

阐述了煤矿管道瓦斯流量计量技术的发展现状,分析了孔板流量计、涡街流量计、皮托管流量计、旋进漩涡流量计、V锥流量计的优缺点;针对瓦斯流量测量准确度受气体中的杂质和瓦斯体积分数变化影响的问题,提出了解决办法;建议煤矿瓦斯抽放管网中的主管、干管、支管采用V锥流量计,汇流管以及各评价单元采用多点采样的插入式流量计;指出煤矿管道瓦斯流量计量应根据不同的现场状况、工况条件及测量需求选择相应的流量计。     

基于径向基的瓦斯涌出量灰色预测模型

为了进一步预防煤层瓦斯突出,实现准确、快速预测煤矿瓦斯涌出量的大小,首先采用1-AGO对样本数据进行处理,建立灰色(GM)预测模型,再利用径向基(RBF)神经网络对灰色预测模型结果进行预测,以作为其最终的预测值;采用阜新煤矿某工作面瓦斯涌出量的历史数据进行建模,实验结果表明,GM-RBF组合模型在预测精度及训练误差方面均优于单一的GM模型和RBF神经网络预测模型;算法计算简便,减弱了数据的随机性及模型误差,煤矿瓦斯涌出量的预测平均误差减小到1.57%。     

多液压缸采样臂同步运动控制的设计与实现

针对移动式煤炭采样车上多液压缸采样臂的结构、功能及其技术要求,分析了液压采样臂采样工作时各液压缸的运动规律和控制难点.为解决采样臂的多液压缸联动以实现终端执行件采样头的位置和角度控制问题,通过软件建立采样臂三维模型,对采样臂采样时各液压缸的运动轨迹进行仿真规划,提出并使用一种基于Simotion C240的虚拟主轴同步的方法,实现多液压缸同步控制.所提出的方法成功地应用于某型号煤炭采样车的控制,满足了自动采样过程中螺旋采样头定点定角度采样的动作要求,取得了实际的应用成果.