The Dynamic Safety Evaluation ModelOf the Safety Control Theory and Its Application

In this paper, on the principle of the modern control theory, the safety state equation of the safety systems was established and the dynamic model of the safety evaluation was put out. And finally, the example of its application in an iron and steel corporation was given.

Increasing the Safety of People Activity in Aggressive Potential Locations, Analyzed through the Probability Theory, Modeling/Simulation and Application in Underground Coal Mining

This paper deals with the increasing safety of working in aggressive potential locations, having SCADA system and WSN sensors, using a “probabilistic strategy” in comparison with a “deterministic” one, modeling/simulation and application in underground coal mining. In general, three conditions can be considered: 1) an unfriendly environment that facilitates the risk of accidents, 2) aggressive equipments that can compete to cause accidents and 3) the work security breaches that can cause accidents. These conditions define the triangle of accidents and are customized for an underground coal mining where the methane gas is released with the exploitation of the massive coal. In this case, the first two conditions create an explosive potential atmosphere. To allow people to work in a safe location it needs: first, a continuing monitoring through SCADA system of the explosive potential atmosphere and second, the use of antiexplosive equipment. This method, named “deterministic strategy”, increases the safety of working, but the explosions have not been completely eliminated. In order to increase the safety of working, the paper continues with the presentation of a new method based on hazard laws, named “probabilistic strategy”. This strategy was validated through modeling/simulation using CupCarbon software platform, and application of WSN networks implemented on Arduino equipments. At the end of the paper the interesting conclusions are emphases which are applicable to both strategies.

Research and application of artificial intelligence service platform for the power field

Conventional analysis methods cannot fully meet the business needs of power grids.At present,several artificial intelligence (AI) projects in a single business field are competing with each other,and the interfaces between the systems lack unified specifications.Therefore,it is imperative to establish a comprehensive service platform.In this paper,an AI platform framework for power fields is proposed;it adopts the deep learning technology to support natural language processing and computer vision services.On one hand,it can provide an algorithm,a model,and service support for power-enterprise applications,and on the other hand,it can provide a large number of heterogeneous data processing,algorithm libraries,intelligent services,model managements,typical application scenarios,and other services for different levels of business personnel.The establishment of the platform framework could break data barrier,improve portability of technology,avoid the investment waste caused by repeated constructions,and lay the foundation for the construction of "platform + application + service" ecological chain.

Performance of beacon safety message dissemination in Vehicular Ad hoc NETworks (VANETs)

Currently, there is a growing belief that putting an IEEE 802.11-like radio into road vehicles can help the drivers to travel more safely. Message dissemination protocols are primordial for safety vehicular applications. There are two types of safety messages which may be exchanged between vehicles: alarm and beacon. In this paper we investigate the feasibility of deploying safety applications based on beacon message dissemination through extensive simulation study and pay special attention to the safety requirements. Vehicles are supposed to issue these messages periodically to announce to other vehicles their current situation and use received messages for preventing possible unsafe situations. We evaluate the performance of a single-hop dissemination protocol while taking into account the quality of service (QoS) metrics like delivery rate and delay. We realize that reliability is the main concern in beacon message dissemination. Thus, a new metric named effective range is defined which gives us more accurate facility for evaluating QoS in safety applications specifically. Then, in order to improve the performance, the effects of three parameters including vehicle's transmission range, message transmission's interval time and message payload size are studied. Due to special characteristics of the safety applications, we model the relationship between communication-level QoS and application-level QoS and evaluate them for different classes of safety applications. As a conclusion, the current technology of IEEE 802.11 MAC layer has still some challenges for automatic safety applications but it can provide acceptable QoS to driver assistance safety applications.

IOT technology application model research of transportation industry in China

The paper studied the connection between internet of things (IOT) technology and transportation industry. Meanwhile,the definition of IOT in transportation was given. Concerning that many problems occurred during the process of traditional intelligent transportation system,the paper proposed a promising model of IOT in transportation. The advantage of the information utilization model from information to function was confirmed through comparative study. Finally,the model presented that a real interconnection of transportation would be achieved based on the unified information collection. It can greatly save cost on technology transfer,exploit potential value of information,and promote the emergence of a sustainable information service market and the industrial upgrade.

Optimization Processes of Tangible and Intangible Networks through the Laplace Problems for Regular Lattices with Multiple Obstacles along the Way

A systematic approach is proposed to the theme of safety,reliability and global quality of complex networks(material and immaterial)by means of special mathematical tools that allow an adequate geometric characterization and study of the operation,even in the presence of multiple obstacles along the path.To that end,applying the theory of graphs to the problem under study and using a special mathematical model based on stochastic geometry,in this article we consider some regular lattices in which it is possible to schematize the elements of the network,with the fundamental cell with six,eight or 2(n+2)obstacles,calculating the probability of Laplace.In this way it is possible to measure the“degree of impedance”exerted by the anomalies along the network by the obstacles examined.The method can be extended to other regular and/or irregular geometric figures,whose union together constitutes the examined network,allowing to optimize the functioning of the complex system considered.

Modeling TCP Incast Issue in Data Center Networks and an Adaptive Application-Layer Solution

In data centers, the transmission control protocol(TCP) incast causes catastrophic goodput degradation to applications with a many-to-one traffic pattern. In this paper, we intend to tame incast at the receiver-side application. Towards this goal, we first develop an analytical model that formulates the incast probability as a function of connection variables and network environment settings. We combine the model with the optimization theory and derive some insights into minimizing the incast probability through tuning connection variables related to applications. Then,enlightened by the analytical results, we propose an adaptive application-layer solution to the TCP incast.The solution equally allocates advertised windows to concurrent connections, and dynamically adapts the number of concurrent connections to the varying conditions. Simulation results show that our solution consistently eludes incast and achieves high goodput in various scenarios including the ones with multiple bottleneck links and background TCP traffic.

Application reliability for communication networks and its analysis method

The network reliability is difficult to be evaluated because of the complex relationship among the network components.It can be quite different for different users running different applications on the same network.This paper proposes a new concept and a model of application reliability.Different from the existing models that ignores the effects of applications,the proposed application reliability model considers the effects of different applications on the network performance and different types of network faults and makes the analysis of network components relationship possible.This paper also provides a method to evaluate the application reliability when the data flow satisfies Markov properties.Finally,a case study is presented to illustrate the proposed network reliability model and the analysis method.

DIMZAL:A Software Tool to Compute Acceptable Safety Distance

The scope of this work is to present a multidisciplinary study in order to propose a tool called DIMZAL. DIMZAL forecasts fuelbreak safety zone sizes. To evaluate a safety zone and to prevent injury, the Acceptable Safety Distance (ASD) between the fire and firefighters is required. This distance is usually set thanks to a general rule-of-thumb: it should be at least 4 times the maximum flame length. A common assumption considers an empirical relationship between fireline intensity and flame length. In the current work which follows on from an oral presentation held at the VII International Conference on Forest Fire Research in Coimbra in 2014, an alternative way is proposed: a closed physical model is applied in order to quantize the ASD. This model is integrated in a software tool, which uses a simulation framework based on Discrete EVent system Specification formalism (DEVS), a 3D physical real-time model of surface fires developed at the University of Corsica and a mobile application based on a Google SDK to display the

煤矿安全事故的综合致因模型

为了系统研究导致煤矿安全事故的人机环因素,结合煤矿实际,将设备因素、环境因素与人因分析和分类系统(Human Factors Analysis and Classification System,HFACS)相结合,构建了煤矿安全事故的“弓弦箭”致因模型。其中,弓弦由设备因素11项、人因因素17项和环境因素11项的致因因素构成,箭表示发生不同人员伤亡数量、不同经济损失的安全事故,利用该模型可以综合描述煤矿安全事故发生的原因以及事故的后果。以“弓弦箭”致因模型为基础,借助蚁群聚类及Ucinet-netdraw方法,分别对100起典型煤矿安全事故进行分析研究。结果显示:(1)在统计的100起事故中,致因因素总频数为803,其中人因因素最高为644,占比80.2%,设备因素次之为92,占比11.5%,环境因素最少为67,占比8.3%;(2)以聚类数为4,最大迭代次数为1000,蚂蚁个数为100,阈值为0.9,蒸发率为0.1进行蚁群聚类分析,得到4类煤矿安全事故致因因素,表明煤矿安全事故是由设备因素、环境因素和人因因素交织作用产生,其中人因因素是最重要的致因因素,且操作者的不安全行为技能差错、决策差错、知觉差错和违反规章制度表现出一定的独立性;(3)Ucinet-netdraw分析显示煤矿安全事故的关键致因路径为:“管理过程漏洞”→“监督不充分”→“个人准备状态”→“违反规章制度”。

郑州“7·20”地铁水淹事件STAMP致因分析

为探讨河南郑州“7·20”地铁5号线伤亡事件致因,综合运用系统理论事件模型与过程(STAMP)模型,分析5号线伤亡事件安全控制结构,据此逐级辨识事件致因;基于复杂网络理论将事件致因及其联系抽象为网络的节点和边,建立地铁水灾事件网络;计算聚类系数、度数等拓扑参数定量分析事件致因性质,确定关键致因。结果表明:地方党委政府面对汛情的应对部署不紧不实,缺少有效的组织动员和有关部门对工程建设存在失管失察是事件的深层根源;建设单位、设计单位等五方主体单位及运维单位的主体责任失职是事件的主观关键致因;应从政府及有关部门、五方主体单位和运维单位方面采取多元协同的风险防控措施。

基于组合赋权云模型的塔台管制系统运行安全评估

随着我国民航业的迅猛发展,空中交通流量不断攀升,机场塔台管制系统的运行安全面临严峻考验,因此,正确识别和评估风险成为有效提高塔台管制系统运行安全水平的重要前提。为精准且有效地完成对塔台管制系统运行的安全评估,构建了基于模糊决策实验室分析法(Decision-Making Trial and Evaluation Laboratory,DEMATEL)网络层次分析法(Analytic Network Process,ANP)熵权法云模型的塔台管制系统运行安全评估模型。首先,通过流程图法并结合人机环管的思想建立塔台管制系统运行安全评估指标体系,并采用模糊DEMATEL法确定评估指标间的相互影响关系,绘制评估指标之间的网络结构图;然后,通过ANP法确定各评估指标的主观权重,采用熵权法确定各评估指标的客观权重,并通过博弈论方法计算评估指标的综合权重;最后,将权重结果与评语层云模型结合使用对各级安全评估指标进行安全评估,通过MATLAB软件完成算例的仿真分析。结果表明:该塔台管制系统运行安全等级在一般和良好之间,仍需采取有效措施对某些风险因素进行控制;同时验证了该模型在塔台管制系统运行安全评估中具有可行性和准确性,对塔台管制系统安全评估具有指导意义。

苏里格气田采气集气工艺及管网模拟研究现状

苏里格气田作为我国内陆最大的整装气田,随着天然气不断开采,地层压力逐渐降低,采气工艺技术的革新与集气管网布局的优化成为延续气田生产寿命的核心问题。该气田通过井下节流工艺有效利用地温热能解决了水合物堵塞问题;新型锁芯式井下节流器一次打捞成功率在90%以上;布井方案采用单井串接工艺,缩短了采气管线长度;减少运行管理费用投入,使建设投资额降低约48.8%。梳理了近年来管网模型研究的发展动态,指出不同方法的优缺点,并以苏里格气田采气量增加30%的背景下,展示了骨架管网水力计算模型的建立过程和模拟软件算法流程,利用TGNET软件模拟管网压降幅度,从而有效抑制水合物生成并避免经济损失。针对集输管网适用性评价进行讨论,指出了生产工况变化对管网运行效率的影响,以及建立水力计算模型对于预测和避免潜在风险的必要性。

城市燃气管网生产安全事故风险协同治理模式研究

保障城市燃气管网安全生产,遏制重特大事故发生,对于维护社会公共安全意义重大。该文在厘清中国城市燃气管网风险治理现状和剖析2021年湖北十堰“6·13”重大事故的基础上,从协同视角切入,通过SFIC模型梳理当前风险治理工作起始条件模糊、催化领导乏力、制度设计缺欠、协同过程混乱等现实问题,进而界定政府、企业、社会三大治理主体及其逻辑关系。研究指出,应遵循SFIC协同治理实践路径,采取理念转变、平台构建、政策完善等手段夯实协同治理基础,落实协同治理保障,并由六大机制创新迸发协同治理过程内在活力,提升治理水平。

基于分布式光纤的地铁隧道安全风险监测技术及其应用

全站机器人监测系统是地铁隧道安全风险监测的重要技术手段之一,但监测点相对有限。本文基于分布式光纤测量数据,提出了一种基于分布式光纤的地铁隧道安全风险监测技术。首先,将分布式光纤监测系统获取的应变数据映射为更加直观的变形位移数据;然后,通过确定3个输入参数、2个隐含层、1个输出参数,构建基于BP神经网络的应变-位移转换模型,验证结果表明,预测值和真实值的误差在0.2 mm以内,说明所建模型能较好地拟合数据的变化规律;最后,将其应用于青岛地铁1号线某区间,确定401.66~699.45με作为各测点预警值的安全区间,202.49~899.98με作为控制值的安全区间,计算结果与现场实测结果相吻合,误差满足工程需要。

融合随机森林与SHAP的恶意加密流量预测模型

加密流量保护用户隐私信息的同时也会隐藏恶意行为,尽早发现恶意加密流量是抵御不同网络攻击(如分布拒绝式攻击、窃听、注入攻击等)和保护网络免受入侵的关键手段.传统基于端口、深度包检测等恶意流量检测方法难以对抗代码混淆、重新包装等复杂攻击,而基于机器学习的方法也存在误报率高和决策过程难以理解的问题.为此,提出一种恶意加密流量检测高可解释性模型EPMRS,以弥补现有研究在性能与可解释性上存在的局限性.在数据去重,重编码及特征筛选等数据预处理的基础上,基于随机森林构建恶意加密流量检测模型,并与逻辑回归、KNN、LGBM等10种主流机器学习模型进行5折交叉验证的实验对比;基于SHAP框架从整体模型、核心风险特征交互效应及样本决策过程三个不同的层面,全面增强恶意加密流量检测模型的可解释性.EPMRS在MCCCU数据集的实证结果表明,EPMRS对未知加密恶意流量的检测准确率达到99.996%、误识别率为0.0003%,与已有工作相比,性能指标平均提升了0.287175%~7.513175%;同时,通过可解释性分析识别出了session(会话)、flow_duration(流持续时间)、Goodput(有效吞吐量)等为影响恶意加密流量检测的核心风险因素.

槐树关水库大坝渗流安全评价与预测

为评价槐树关水库大坝的渗流稳定性,收集大坝近年来面板周边缝与坝基监测点处渗压计数据,库水位、气温、降雨量、坝后渗流的监测数据及大坝工程建设与地质资料,先将监测点处渗压计值和坝前水位进行Pearson相关性分析,再根据大坝工程建设及地质资料绘制大坝断面模型并导入Autobank7.7软件计算坝后渗流量,最后将气温、库水位、降雨量等影响因子代入PCA BP神经网络与随机森林、BP神经网络模型对坝后渗流量进行预测。结果表明:除P_(3)、P_(6)、P_(9)外的监测点渗压计值、坝后量水堰监测渗流量值与库水位相关性较强,符合大坝渗流场的一般规律,初步判定大坝较稳定;实际监测的坝后渗流量是Autobank软件模型理论计算值的8倍,判定大坝有出现渗流破坏的可能,后续应采取相应措施除险加固加强监测以保证大坝的稳定性;PCA BP神经网络与随机森林、BP神经网络3种模型最佳预测准确度分别为83.20%、79.35%、69.41%,其中PCA BP神经网络的预测效果最佳,通过模型预知渗流量防止渗流破坏对保证大坝的安全运行具有重要意义。

国家间冲突风险监测预警模型构建及应用研究

[研究目的]科学分析复杂国际环境中的国家间冲突风险,有利于提高国家安全风险监测预警能力,帮助各国在复杂的国际格局中寻求维持自身发展的道路。[研究方法]基于国家安全系统视角,提出了集国家间冲突情景感知、数据收集与预处理、风险预测为一体的国家间冲突风险监测预警模型;基于专家知识和案例数据分别构建了两种国家间冲突贝叶斯网络(BN)模型:BN ISM和BN TAN。[研究结论]模型耦合机器学习技术和贝叶斯网络方法,实现了国家间冲突风险的实时监测和预警,为国家安全决策提供支持;BN TAN模型在整体预测和低冲突风险预测方面表现出色,而BN ISM模型在高风险预测方面具有比较明显的优势。未来国家间冲突风险监测预警模型应当考虑多领域知识与案例数据的融合,为推动国家安全治理体系建设贡献力量。