基于网络交换机安全措施的研究和实现

介绍了电力行业信息网络交换机的安全现状,详细阐述了加强硬件安全以及安全策略加固方法及注意事项。     

宿南矿区徐桥塌陷治理工程优选方案

因受祁南煤矿采煤影响而使徐桥塌陷成危桥,为保此桥安全正常使用,必须对桥进行加固处理或重建一座新桥。方案一是进行加固处理,方案二是重建一座新桥。经过对二方案进行优化比较,确定采用重建一座新桥的方案。     

Study on destructions and reinforcement measures of mined constructions

Ground movement and deformation caused by underground mining would destroy the constructions located within subsidence area. Constructions would suffer different destructions with different location. The effect of ground deformation caused by underground mining to constructions was analyzed. Analyzed the destructive types of constructions in different ground movement and deformation. Taking a two-storey building for example, the walls were reinforced by computation before mining. To protect the construction the reinforcement measures to the construction before mining were studied.     

考虑无线充电的无人机路径在线规划

近年来, 无人机在物流、通信、军事任务、灾害救援等领域中展现出了巨大的应用潜力, 然而无人机的续航 能力是制约其使用的重大因素, 在无线充电技术不断突破和发展的背景下, 本文基于深度强化学习方法, 提出了一 种考虑无线充电的无人机路径在线优化方法, 通过无线充电技术提高无人机的任务能力. 首先, 对无人机功耗模型 和无线充电模型进行了构建, 根据无人机的荷电状态约束, 设计了一种基于动态上下文向量的深度神经网络模型, 通过编码器和解码器的模型架构, 实现无人机路径的直接构造, 通过深度强化学习方法对模型进行离线训练, 从而 应用于考虑无线充电的无人机任务路径在线优化. 文本通过与传统优化方法和深度强化学习方法进行实验对比, 所提方法在CPU算力和GPU算力下分别实现了4倍以及100倍以上求解速度的提升.     

一种基于强化学习的指挥智能体控制方法

针对无人水下航行器(unmanned underwater vehicle,UUV)如何进行任务分配、航路规划、指挥控制问题, 提出一种新的控制实现方法。搭建UUV 指挥智能体训练平台,设计学习训练所需的想定,进行状态设计、数据适配、 决策解析和规则库建立,选定近端策略优化(proximal policy optimization,PPO)强化学习算法进行训练,并进行应用 验证。结果表明：指挥智能体能有效对UUV 进行任务分配、航路规划、指挥控制;通过不断优化算法,可提高战胜 基于规则的传统控制方法的胜率。     

粮油中转储备库的加固改造设计

介绍了加固方案的选择、相关构件强度的计算、接点构造的处理等主要加固步骤。实践证明,此方案较经济、合理,且能最大程度地减少施工工作量。     

复合锚杆桩在基础加固中的应用

根据某桥墩基础承载力下降的具体情况,采用单孔复合锚杆桩技术,对桥墩基础进行了加固,并对单孔复合锚杆桩的加固机理进行了初步研究.利用数值模拟方法,对加固后桥墩基础的承载能力以及加固结构的承载性能进行了比较系统地分析.结果表明:利用单孔复合锚杆桩技术加固后的桥墩基础,其承载力有较大幅度地提高,在600kN/m的桥墩载荷作用下,加固结构和周围的岩体在垂直方向上的位移变形值不足2mm,而且基本上保持着同步变形同步稳定的理想状态,达到了设计目的.     

Multiagent Reinforcement Learning:Rollout and Policy Iteration

We discuss the solution of complex multistage decision problems using methods that are based on the idea of policy iteration(PI),i.e.,start from some base policy and generate an improved policy.Rollout is the simplest method of this type,where just one improved policy is generated.We can view PI as repeated application of rollout,where the rollout policy at each iteration serves as the base policy for the next iteration.In contrast with PI,rollout has a robustness property:it can be applied on-line and is suitable for on-line replanning.Moreover,rollout can use as base policy one of the policies produced by PI,thereby improving on that policy.This is the type of scheme underlying the prominently successful Alpha Zero chess program.In this paper we focus on rollout and PI-like methods for problems where the control consists of multiple components each selected(conceptually)by a separate agent.This is the class of multiagent problems where the agents have a shared objective function,and a shared and perfect state information.Based on a problem reformulation that trades off control space complexity with state space complexity,we develop an approach,whereby at every stage,the agents sequentially(one-at-a-time)execute a local rollout algorithm that uses a base policy,together with some coordinating information from the other agents.The amount of total computation required at every stage grows linearly with the number of agents.By contrast,in the standard rollout algorithm,the amount of total computation grows exponentially with the number of agents.Despite the dramatic reduction in required computation,we show that our multiagent rollout algorithm has the fundamental cost improvement property of standard rollout:it guarantees an improved performance relative to the base policy.We also discuss autonomous multiagent rollout schemes that allow the agents to make decisions autonomously through the use of precomputed signaling information,which is sufficient to maintain the cost improvement property,without any on-line coordination of control selection between the agents.For discounted and other infinite horizon problems,we also consider exact and approximate PI algorithms involving a new type of one-agent-at-a-time policy improvement operation.For one of our PI algorithms,we prove convergence to an agentby-agent optimal policy,thus establishing a connection with the theory of teams.For another PI algorithm,which is executed over a more complex state space,we prove convergence to an optimal policy.Approximate forms of these algorithms are also given,based on the use of policy and value neural networks.These PI algorithms,in both their exact and their approximate form are strictly off-line methods,but they can be used to provide a base policy for use in an on-line multiagent rollout scheme.     

基于回采巷道破碎程度的浆液性能选型研究

工作面回采巷道围岩破碎程度不同,应采用不同性能的注浆材料对围岩进行分区、分类加固。采用BP神经网络算法,建立了回采巷道围岩破碎程度与注浆材料性能的“地质条件—浆液性能”互馈模型。该模型选取顶板岩层强度、煤层强度、底板岩层强度等7个地质条件参数作为输入因子,选取注浆材料7 d抗压强度、初凝时间和初始黏度作为输出因子。利用34组数据对模型进行训练,8组数据作为测试样本开展误差分析。结果表明：训练集拟合系数达到0.999 95,测试集输出因子相对误差低于13%,训练和测试效果较好,能够满足基于围岩破碎程度进行浆液参数选型及预测的要求。     

Sex differences in impulsivity: A meta-analysis.

Men are overrepresented in socially problematic behaviors, such as aggression and criminal behavior, which have been linked to impulsivity. Our review of impulsivity is organized around the tripartite theoretical distinction between reward hypersensitivity, punishment hyposensitivity, and inadequate effortful control. Drawing on evolutionary, criminological, developmental, and personality theories, we predicted that sex differences would be most pronounced in risky activities with men demonstrating greater sensation seeking, greater reward sensitivity, and lower punishment sensitivity. We predicted a small female advantage in effortful control. We analyzed 741 effect sizes from 277 studies, including psychometric and behavioral measures. Women were consistently more punishment sensitive (d = ?0.33), but men did not show greater reward sensitivity (d = 0.01). Men showed significantly higher sensation seeking on questionnaire measures (d = 0.41) and on a behavioral risk-taking task (d = 0.36). Questionnaire measures of deficits in effortful control showed a very modest effect size in the male direction (d = 0.08). Sex differences were not found on delay discounting or executive function tasks. The results indicate a stronger sex difference in motivational rather than effortful or executive forms of behavior control. Specifically, they support evolutionary and biological theories of risk taking predicated on sex differences in punishment sensitivity. A clearer understanding of sex differences in impulsivity depends upon recognizing important distinctions between sensation seeking and impulsivity, between executive and effortful forms of control, and between impulsivity as a deficit and as a trait. (PsycINFO Database Record (c) 2010 APA, all rights reserved)