基于改进型模糊层次分析法的舰艇生命力评估

由于舰艇系统的复杂性,对全舰进行生命力评估需要将其分解到下一级或几级具体的子系统,通过系统生命力指标得到全舰生命力的描述。传统的模糊层次分析法(FAHP)存在两个缺陷:一方面可能导致计算结果错误;另一方面也可能造成无法计算指标权重,使模糊层次分析法的使用范围受到限制。采用一种改进的模糊层次分析法,建立三角模糊判断矩阵,确定各层次间相关因素的权重,并计算得到各子系统的权重排序。实例证明,该模型的评估结果反映了舰船系统的实际工况。根据该模型计算的评估结果,可以更好地发现舰艇生命力系统的薄弱环节,为损管决策提供科学的理论依据和方法。     

Robust single-track train dispatching model under a dynamic and stochastic environment: A scenario-based rolling horizon solution approach

After a major service disruption on a single-track rail line, dispatchers need to generate a series of train meet-pass plans at different decision times of the rescheduling stage. The task is to recover the impacted train schedule from the current and future disturbances and minimize the expected additional delay under different forecasted operational conditions. Based on a stochastic programming with recourse framework, this paper incorporates different probabilistic scenarios in the rolling horizon decision process to recognize (1) the input data uncertainty associated with predicted segment running times and segment recovery times and (2) the possibilities of rescheduling decisions after receiving status updates. The proposed model periodically optimizes schedules for a relatively long rolling horizon, while selecting and disseminating a robust meet-pass plan for every roll period. A multi-layer branching solution procedure is developed to systematically generate and select meet-pass plans under different stochastic scenarios. Illustrative examples and numerical experiments are used to demonstrate the importance of robust disruption handling under a dynamic and stochastic environment. In terms of expected total train delay time, our experimental results show that the robust solutions are better than the expected value-based solutions by a range of 10-30%.     

基于云模型的装备研制项目中止决策方法

装备研制项目是一项复杂的系统工程,其实施前景不确定,科学及时地中止没有前景的研制项目对于优化国防资源配置有重要意义。针对目前中止决策方法中的定性方法主观性大,而定量方法损失信息较多的问题,引入了云理论,通过云变换把定性评语转化为评价云,建立了云决策模型。     

基于期望效用准则战场目标分配决策研究

文章通过分析影响目标价值的指标,构建火力分配决策模型,研究基于期望效用准则的战场目标分配决策方案模型,提出其分析步骤和方法,科学计算期望效用,较大程度上降低了决策的风险程度,具有一定的科学性和实用性,该方法为战场目标分配决策方案的选择提供理论依据。     

舰载光电对抗系统作战仿真方法研究

该文针对舰载光电对抗系统作战仿真需求出发,首先建立了舰载光电对抗作战双方和虚拟战场环境的模型,然后开展了作战仿真试验,试验结果证明战术应用软件提交的作战方案可行,实现了多种光电对抗手段综合运用的目的,具备指挥光电对抗设备开展光电对抗作战的能力。该文所描述的仿真方法适用于评价舰载光电对抗系统作战决策方案。     

导航系统异步串口通信协议参数智能检测算法研究

针对某些舰船导航装备所采用的异步串口通信协议参数不明确,无法正常和其他设备通信的现象,提出了一套基于单片机采集电平数据,计算机对采样数据进行解析的异步串口通信协议参数自动检测方法。依次阐述了对波特率、数据位长度、校验方式以及数据编码方式的解析算法。经实践结果表明,该方法运行速率快、正确率高,是检测异步串口通信协议参数的可靠方法。     

海洋环境监测是海洋发展和维权的支撑

海洋维权装备必须适应海洋环境,海洋环境又无休止地影响着海洋装备的功能和性能.要想提高装备技术水平,发挥装备的最大效能,在应用和研制装备的同时,要充分了解海洋环境对装备的诸多影响,要研究海洋环境与装备相关性技术.本文根据海洋维权装备发展顶层设计的需求,从功能上定性地探讨分析海洋环境对雷达探测、水声探测、目标识别、精确制导、信号传输、导航定位等方面的影响,提出海洋维权装备对海洋环境的适应性要求和对海洋环境效应技术的支撑性需求,提出把海洋环境监测要素纳入海战场辅助决策体系.海洋环境监测既是人类认知海洋、开发海洋、防灾救灾、海战场建设的需要,又是海洋发展和维权的支撑和先导,军民共建,军民共享,为发展海洋经济,保护海洋权益而励志奋进!     

基于交通预测的多态交通流信号控制

为解决现有信号控制方法对多态交通流交叉口适应性不足的问题,通过在交叉口设置多功能进口车道和车辆检测器、车道控制器等硬件设施,进行了短时交通流预测基础上的多态交通流条件下交叉口信号配时优化研究。根据交通量预测数据,建立信号控制延误估计模型,以交叉口总延误最小为优化目标选取多功能车道流向,根据每相位最大排队长度逐步优化绿灯时长并实施信号控制。短时交通预测以小波分析为基础,采用RBF神经网络及Markov链分别预测交通流的稳态与随机部分。使用VISSIM软件对设置多功能车道的交叉口多态流信号控制方法进行了交通仿真。分析结果表明：该方法可有效降低行车延误,提高交叉口服务水平。     

Predicting arterial breakdown probability: A data mining approach

Predicting the probability of traffic breakdown can be used as an important input for creating advanced traffic management strategies that are specifically implemented to reduce this probability. However, most, if not all, past research on the probability of breakdown has focused on freeways. This study focuses on the prediction of arterial breakdown probability based on archived traffic data for use in real-time transportation system operations. The breakdown of an arterial segment is defined in this study as a segment's operating condition under the level of service F according to the highway capacity manual threshold, although any other level of service could be used. Data from point detection and automatic vehicle identification matching technologies are aggregated in space and time to allow their use as inputs to the prediction model. A decision tree approach, combined with binary logistic regression, is used in this study to predict the breakdown probability based on these inputs. The model is validated using data not used in the development of the model. The research shows that the root mean square error and the mean absolute error of the prediction was 13.6 and 11%, respectively. The analysis also shows that the best set of parameters used in the prediction can be different for different links, due to the various causes of breakdown and characteristics of different links. Predicting the probability of breakdown in ahead of time will allow the agencies to change the signal-timing plan that can delay or eliminate the breakdown.     

基于MDDP系统的智能压机线开发

冲压压力机作为汽车制造行业表面件加工的设备,具有多工况,变载荷、重载荷的特点,在零件加工过程中需要持续往复运行。随着设备的负荷不断增大使用年限地不断增长,一些大型的机械故障也因为磨损、疲劳以及维护保养不及时彻底等因素而开始出现,且出现频次逐渐增高。在既有的正常点巡检和例行检修保养的前提下,一些故障和问题仍无法及时发现或提前预判,从而造成了大量的非计划停机时间、人工成本、备件成本的投入。为此,引入了智能设备的概念,开发MDDP系统,实现设备自主监控、诊断、决策和预测。