Computational intelligence interception guidance law using online off-policy integral reinforcement learning

Missile interception problem can be regarded as a two-person zero-sum differential games problem,which depends on the solution of Hamilton-Jacobi-Isaacs(HJI)equa-tion.It has been proved impossible to obtain a closed-form solu-tion due to the nonlinearity of HJI equation,and many iterative algorithms are proposed to solve the HJI equation.Simultane-ous policy updating algorithm(SPUA)is an effective algorithm for solving HJI equation,but it is an on-policy integral reinforce-ment learning(IRL).For online implementation of SPUA,the dis-turbance signals need to be adjustable,which is unrealistic.In this paper,an off-policy IRL algorithm based on SPUA is pro-posed without making use of any knowledge of the systems dynamics.Then,a neural-network based online adaptive critic implementation scheme of the off-policy IRL algorithm is pre-sented.Based on the online off-policy IRL method,a computa-tional intelligence interception guidance(CIIG)law is developed for intercepting high-maneuvering target.As a model-free method,intercepting targets can be achieved through measur-ing system data online.The effectiveness of the CIIG is verified through two missile and target engagement scenarios.

Restoring force correction based on online discrete tangent stiffness estimation method for real-time hybrid simulation

In real-time hybrid simulation（RTHS）, it is difficult if not impossible to completely erase the error in restoring force due to actuator response delay using existing displacement-based compensation methods. This paper proposes a new force correction method based on online discrete tangent stiffness estimation（online DTSE） to provide accurate online estimation of the instantaneous stiffness of the physical substructure. Following the discrete curve parameter recognition theory, the online DTSE method estimates the instantaneous stiffness mainly through adaptively building a fuzzy segment with the latest measurements, constructing several strict bounding lines of the segment and calculating the slope of the strict bounding lines, which significantly improves the calculation efficiency and accuracy for the instantaneous stiffness estimation. The results of both computational simulation and real-time hybrid simulation show that：（1） the online DTSE method has high calculation efficiency, of which the relatively short computation time will not interrupt RTHS; and（2） the online DTSE method provides better estimation for the instantaneous stiffness, compared with other existing estimation methods. Due to the quick and accurate estimation of instantaneous stiffness, the online DTSE method therefore provides a promising technique to correct restoring forces in RTHS.

Direct immune-SCIR public-opinion propagation model based on real-time online users

Current public-opinion propagation research usually focused on closed network topologies without considering the fluctuation of the number of network users or the impact of social factors on propagation. Thus, it remains difficult to accurately describe the public-opinion propagation rules of social networks. In order to study the rules of public opinion spread on dynamic social networks, by analyzing the activity of social-network users and the regulatory role of relevant departments in the spread of public opinion, concepts of additional user and offline rates are introduced, and the direct immune-susceptible, contacted, infected, and refractory (DI-SCIR) public-opinion propagation model based on real-time online users is established. The interventional force of relevant departments, credibility of real information, and time of intervention are considered, and a public-opinion propagation control strategy based on direct immunity is proposed. The equilibrium point and the basic reproduction number of the model are theoretically analyzed to obtain boundary conditions for public-opinion propagation. Simulation results show that the new model can accurately reflect the propagation rules of public opinion. When the basic reproduction number is less than 1, public opinion will eventually disappear in the network. Social factors can significantly influence the time and scope of public opinion spread on social networks. By controlling social factors, relevant departments can analyze the rules of public opinion spread on social networks to suppress the propagate of negative public opinion and provide a powerful tool to ensure security and stability of society.

A Non-Contact Original-State Online Real-Time Monitoring Method for Complex Liquids in Industrial Processes

Failures are very common during the online real-time monitoring of large quantities of complex liquids in industrial processes, and can result in excessive resource consumption and pollution. In this study, we introduce a monitoring method capable of non-contact original-state online real-time monitoring for strongly coated, high-salinity, and multi-component liquids. The principle of the method is to establish the relationship among the concentration of the target substance in the liquid （C）, the color space coor- dinates of the target substance at different concentrations （L＊, a＊, b＊）, and the maximum absorption wave- length （λmax）; subsequently, the optimum wavelength λT of the liquid is determined by a high-precision scanning-type monitoring system that is used to detect the instantaneous concentration of the target substance in the flowing liquid. Unlike traditional monitoring methods and existing online monitoring methods, the proposed method does not require any pretreatment of the samples （i.e., filtration, dilution, oxidation/reduction, addition of chromogenic agent, constant volume, etc.）, and it is capable of original- state online real-time monitoring. This method is employed at a large electrolytic manganese plant to monitor the Fe3. concentration in the colloidal process of the plant＇s aging liquid （where the concentra- tions of Fe3＋, Mn2＋, and （NH4）2SO4 are 0.5-18 mg.L 1, 35-39 g.L 1, and 90-110 g.L 1, respectively）. The relative error of this monitoring method compared with an off-line laboratory monitoring is less than 2%.

A Cooperative Distributed System for Real-Time Route Guidance

This paper describes a cooperative decentralized architecture for reactive real-time route guidance. The architecture is cooperative in the sense that it allows adjacent local controllers to exchange information regarding the traffic conditions in their territories. A set of local decision rules and associated heuristic functions to support the cooperative architecture are specified. A protocol governing the knowledge exchange among local adjacent controllers is developed. A simulation-assignment modeling framework is used for assessing the effectiveness of this cooperative architecture under various levels of controller knowledge and network traffic congestion. The cooperative decentralized system is tested under various scenarios of knowledge and cooperation and network traffic demand levels. The cooperative system is compared against the shortest path algorithm as a benchmark.

Impact point prediction guidance of ballistic missile in high maneuver penetration condition

An impact point prediction(IPP) guidance based on supervised learning is proposed to address the problem of precise guidance for the ballistic missile in high maneuver penetration condition.An accurate ballistic trajectory model is applied to generate training samples,and ablation experiments are conducted to determine the mapping relationship between the flight state and the impact point.At the same time,the impact point coordinates are decoupled to improve the prediction accuracy,and the sigmoid activation function is improved to ameliorate the prediction efficiency.Therefore,an IPP neural network model,which solves the contradiction between the accuracy and the speed of the IPP,is established.In view of the performance deviation of the divert control system,the mapping relationship between the guidance parameters and the impact deviation is analysed based on the variational principle.In addition,a fast iterative model of guidance parameters is designed for reference to the Newton iteration method,which solves the nonlinear strong coupling problem of the guidance parameter solution.Monte Carlo simulation results show that the prediction accuracy of the impact point is high,with a 3 σ prediction error of 4.5 m,and the guidance method is robust,with a 3 σ error of 7.5 m.On the STM32F407 singlechip microcomputer,a single IPP takes about 2.374 ms,and a single guidance solution takes about9.936 ms,which has a good real-time performance and a certain engineering application value.

Discussion on neighborhood optimal trajectory online correction algorithm and its application range

This paper presents a neighborhood optimal trajectory online correction algorithm considering terminal time variation,and investigates its application range.Firstly,the motion model of midcourse guidance is established,and the online trajectory correction-regenerating strategy is introduced.Secondly,based on the neighborhood optimal control theory,a neighborhood optimal trajectory online correction algorithm considering the terminal time variation is proposed by adding the consideration of terminal time variation to the traditional neighborhood optimal trajectory correction method.Thirdly,the Monte Carlo simulation method is used to analyze the application range of the algorithm,which provides a basis for the division of application domain of the online correction algorithm and the online regeneration algorithm of midcourse guidance trajectory.Finally,the simulation results show that the algorithm has high real-time performance,and the online correction trajectory can meet the requirements of terminal constraint change.The application range of the algorithm is obtained through Monte Carlo simulation.

Online Induction of Probabilistic Real-Time Automata

The probabilistic real-time automaton （PRTA） is a representation of dynamic processes arising in the sciences and industry. Currently, the induction of automata is divided into two steps： the creation of the prefix tree acceptor （PTA） and the merge procedure based on clustering of the states. These two steps can be very time intensive when a PRTA is to be induced for massive or even unbounded datasets. The latter one can be efficiently processed, as there exist scalable online clustering algorithms. However, the creation of the PTA still can be very time consuming. To overcome this problem, we propose a genuine online PRTA induction approach that incorporates new instances by first collapsing them and then using a maximum frequent pattern based clustering. The approach is tested against a predefined synthetic automaton and real world datasets, for which the approach is scalable and stable. Moreover, we present a broad evaluation on a real world disease group dataset that shows the applicability of such a model to the analysis of medical processes.

“电力电子技术”课程思政的思考与实践

针对传统“电力电子技术”课程只重视知识传授,缺乏全方位、有目标的价值观引领等问题,以立德树人为中心,通过加强教师学习和常态化交流互动,建立思想政治理论课程组,通过专业内部教师纵向互动以及专业教师与思想政治理论课教师横向互动的模式进行课程建设。建设了课程网站,采用学习通等信息化教学手段,在教学中以教师为主导、学生为主体,通过课堂内外互补、线上资源和线下课堂互补、专业知识和价值引领相结合的方式实现全员、全程、全方位育人。

融入思政元素的飞机工程课程群混合式教学实践

在立德树人背景下,开展课程思政教学是必然趋势。针对专业课程价值塑造弱化的问题,飞机性能工程课程群根据国产民机和签派员岗位能力,依托超星在线教学平台,明确育人目标,将“课程思政”融入线上线下混合式教学,实现思政教学与“双线教学”双向贯通,课程群组成了课堂学习共同体,形成协同效应,打造有温度、有深度的立体课堂,丰富学生的学习方式,建立家国情怀和情感认同,达到“知识——技能——价值”一体化育人目标。

一体两步三引导应用于针灸临床在线课程教学改革研究

中医针灸临床课程是针灸推拿专业必修的主干课程,其教学效果影响学生实习甚至是毕业后的临床工作。在近几年新型冠状病毒肺炎疫情防控的大背景下,各高校均无法正常开展线下教学,线上教学已成为必然趋势。如何提高中医临床课程学生的临床能力,已经成为全国高校线上教育教学综合改革的重要内容之一。文章针对传统线上教学存在的问题进行分析,根据针灸推拿学专业特点、针灸临床能力培养的重要性,探讨“一体两步三引导”在针灸临床在线教学改革中的应用,制定相应的改革方案,旨在为相关人员提供参考和借鉴。

论网络舆论反转及其引导

互联网为传统舆论场带来近乎颠覆式的改变,网络舆论的不稳定性和不确定性因素明显增加,网络舆论反转已成为一种常态化现象。网络舆论反转实质上是网络舆论受众在对网络舆论事件真假甄别基础上价值判断和情绪表达的转变,不同的价值判断和情绪表达相互交织、相互作用,推动网络舆论出现不同类型的反转。个人情感先于事实、众声喧哗消解事实、利益至上解构事实、片面认知曲解事实、复杂流程延误事实均导致事实真相不能及时登场、完整亮相,网络舆论必定再三跌宕变更。网络舆论反转乱象严重损害网络舆论场稳定、网络生态和谐和网络舆论影响力,亟须对其进行及时正确有效的引导,这已成为新时代思想政治教育的重大课题。

网络社交圈层化背景下大学生思想政治教育的挑战与对策

网络社交圈层化对大学生思想政治教育提出新挑战。社交圈层化虽有助于大学生形成稳定的社交关系,但也可能导致信息茧房和观点极化,限制了大学生的信息来源和视野,影响其思维方式和价值观念。因此,高校需加强价值观教育,打破圈层壁垒,促进文化交流与融合,引导大学生全面、客观地认识世界。同时,建立有效的价值观引导机制,加强社会实践与体验,提升大学生的独立思考能力和创新能力,促进其全面发展和健康成长。

社交媒体时代青年“偶像文化”透视与教育引导

文章首先明确“偶像文化”相关概念内涵,从理论上解析网络青年亚文化、“偶像文化”。其次,对“偶像文化”进行深层透析,从现实呈现上说明“偶像文化”“是何”的问题。再次,运用多学科综合分析,从教育学、心理学、社会学、新闻传播学等学科探讨“粉丝”群体的行为表现与心理机制,说明“何以”的问题。从次,探究“偶像文化”的影响,说明“有何”影响的问题。最后,针对粉丝行为的“失范”,提出有效的应对措施,回答“如何”应对“偶像文化”影响的问题,切实回应引导“偶像文化”有序发展及青年价值观培塑的时代要求和现实诉求。

煤矿井下钻探远程支持技术及其应用前瞻

为提升钻探工艺技术信息化程度,进一步提高业务水平、服务效率和企业管理水平,提出以煤矿井下钻探技术为理论支撑,基于网络有线、无线传输等建构煤矿井下钻探技术远程支持服务体系,开发出基于该远程支持服务体系的煤矿井下钻探技术远程服务平台系统。平台的功能实现由5个模块组成,包括慕课视频点播模块、远程故障维修模块、远程技术支持模块、消息推送模块、信息安全模块。通过基于“端对端”的钻探技术标准化培训平台和基于浏览器/B/S架构的钻探技术装备远程指导系统,为施工现场提供了故障诊断、技术查询、可视化维修等技术支持,使煤矿井下钻探技术服务更高效、更及时,有力提高了服务效率,降低了人工成本,更有效地提升了钻探工艺服务信息化程度,为钻探设备的智能化发展赋能。

多禁飞区在线遭遇的自主规避再入制导方法

针对高超声速滑翔飞行器再入过程中遭遇多个未知威胁的规避突防需求,提出了一种多禁飞区在线遭遇的自主规避再入制导方法。将多个在线遭遇的禁飞区连续规避问题抽象为序贯决策问题,设计了一种基于强化学习的解决方案以提高飞行器的自主规避能力。充分考虑强化学习智能体的泛化能力和训练效率,建立了禁飞区规避问题的马尔科夫决策过程。在此基础上,设计基于模糊控制策略的多智能体协调决策方法,为每一个在线遭遇的禁飞区分配航向决策智能体进行独立航向决策,根据实时环境评估各禁飞区的威胁程度并协调生成航向指令。理论分析和数值仿真表明,此方法能够使飞行器在满足终端约束和过程约束条件下,在多个在线遭遇的禁飞区场景中实现有效规避,具有良好的鲁棒性和泛化能力。

火箭弹中制导凸优化方法

为提高火箭弹制导过程中的可靠性和环境适应性,提出一种基于凸优化的在线求解规划弹道的方法,使其尽可能的达到其原有的毁伤效能。以制导火箭弹滑翔弹道模型为仿真实例,以控制能量最优轨迹规划模型为研究对象,利用伪谱法离散连续变量,线性凸化非线性动态方程,建立标准凸优化模型,基于凸优化方法求解并进行循环仿真计算得到仿真弹道,并与原理想弹道进行了比对。仿真结果表明,该方法能在偏离预设的初始弹道时,快速求解得到可行的优化弹道,证明了该方法在存在偏差时求解弹道规划问题有一定效果。

网络舆情中基于心理暗示的温和舆论引导策略研究

为应对网络舆论环境中信息茧房效应的消极影响,考虑在舆论引导过程中将个体对引导观点的接受程度,提出基于心理暗示的温和观点引导策略,并构建了基于心理暗示的温和引导策略模型。通过实验分析了引导强度与引导比例的影响,研究了引导策略对舆论演化过程的影响,并在多个网络下验证了引导策略的稳定性,最后与传统度引导策略进行了对比。结果表明温和引导在引导效果具有优越性,尤其是能在中长期对群体舆论进行持续影响。

基于移动医疗的新生儿护理线上咨询门诊的建立与实施

目的建立并实施新生儿护理线上咨询门诊,让群众得到“指尖上的医疗便利”,及时解决家长的育儿问题,识别疾病的风险。方法在医院微信公众号设立互联网医院之新生儿护理线上咨询门诊;选拔出诊护士、建立互联网专科护理服务制度、工作流程;监测互联网护理门诊工作量、接诊反应时长、服务时长和满意度。结果共选拔16名护士出诊,2020年2月—2023年8月新生儿护理线上咨询门诊共接诊9212例次,咨询条目145598次,足月儿8489人次(92.2%),早产儿723人次(7.8%),新生儿喂养咨询最多,为62799条(43.14%),新生儿黄疸咨询44778条(30.75%),皮肤问题咨询26297例次(18.06%),其他11724条(8.05%),判断需要转诊至线下护理或者医疗门诊者337人次(3.66%)。患者挂号到护士接诊的反应时长中位数为33(0,162)分钟。护士服务时长中位数为46(17,1440)min。进行了满意度评价的为6427人次(69.77%),其中服务质量、服务态度、系统使用3个维度均获得5星好评的为6362人次(98.99%)。结论开设新生儿护理线上咨询门诊可有效帮助家长足不出户解决育儿问题,满足新生儿延续性护理的需求,节约了家长就医时间,提升了家长就医体验感,也体现了新生儿专科护士的专业价值。

基于SDAE-SVM算法的雷达干扰方案在线决策方法

面向主动雷达型末制导干扰场景,提出了一种基于SDAE-SVM算法的雷达干扰方案在线决策方法。基于认知电子战机理构建在线干扰方案决策原理模型,包括雷达状态在线评估模块和干扰效果在线评估模块;区分有源压制干扰和有源欺骗干扰,分别构建雷达状态在线评估指标和干扰效果在线评估指标;建立雷达状态和干扰效果自适应评估流程,融合SDAE算法和SVM算法构建SDAE-SVM算法,用于干扰方案在线决策模型求解。通过仿真案例分析得出以下结论:本研究提出的雷达干扰方案在线决策方法准确率达到96.02%,同时与单独使用SDAE算法和SVM算法进行求解相比,采用SDAE-SVM算法求取的决策方案准确率最高,证明本研究方案可行。