GSPN的分析方法及其应用

随着计算机和信息技术的发展,广义随机Petri网(G SPN)作为一种图形化的建模工具,不仅可以对系统进行形式化的描述和快速原型开发,而且由于其具有坚实的数学理论基础,可以对系统进行正确性验证和性能评价,因此在系统的设计过程中,得到了广泛的应用。基于结构分析方法、可达图分析和数值分析方法讨论分析了G SPN,并给出了具体的算例,最后讨论了G SPN的应用领域。     

数据整合技术研究

信息技术的快速发展使企业对其数据整合的需求提升到前所未有的高度。整合更是企业由内向外发展意识的体现。本文从数据源系统的整合出发,探讨了数据整合的方法及技术路线。     

使用图像优化方法估计水体调制传递函数

针对水体属性的变化使图像复原困难的问题,提出了一种从退化的水下图像中估计自然水体调制传递函数的方法。该方法首先建立了自然水体的调制传递函数与其固有光学特性参数之间的关系,然后采用图像复原技术对图像进行复原,最后使用粒子群优化算法来优化调制传递函数的相关参数。仿真实验表明:该方法能有效对水下图像进行复原,且不需测量水体的光学参数就能估计出自然水体的调制传递函数。该方法用于水下激光成像系统的图像复原可取得明显效果。     

C~3I 系统多传感器的信息融合——Fuzzy 函数聚类算法

在对多类传感器收集空中目标状态信息描述的基础上,用Ｆｕｚｚｙ目标函数聚类算法建立了对空情数据融合的数学模型。对数据融合过程,参数的初始化问题进行了实际应用的讨论;并对其应用效果和优势作了实际的分析。该方法是Ｃ３Ｉ系统数据融合技术的有效方法之一。     

基于数据仓库的数据挖掘技术在指挥控制系统中的应用

介绍了数据仓库和数据挖掘的概念、数据挖掘的过程和方法,简单分析了现代战争中信息处理的特点和需求,阐述了数据挖掘在军事指挥控制系统中的应用必要性,提出了军事应用中数据挖掘系统的层次体系结构,并针对该层次体系结构进一步提出了指挥控制系统中数据挖掘技术的应用模型.     

【专题】面向精打产品的红外图像数据采集、治理和应用

面对复杂严酷的战场环境,红外成像精打产品的智能化水平和抗干扰能力是产品生存的重要因素,而图像大数据技术是红外成像精打产品提升技术能力的重要保障。本文结合红外成像精打产品智能化能力提升的需求,提出了面向精打产品的图像数据获取、历史数据及新增数据治理、数据挖掘应用的全过程实用方法,实现了特定目标红外图像数据增补及海量图像数据的高效管理与智能应用;并在图像大数据的支持下,研发了智能信息处理算法性能评价平台和目标检测算法,有效提升了精打产品的智能化水平和实际应用能力。开展基于实际应用需求的图像数据采集、治理和应用技术研究是提升精打产品性能的重要途径,也能够为智能信息处理技术在精打产品上的落地应用提供有力支撑。     

Shock initiation performance of NTO-based polymer bonded explosive

3-nitro-1,2,4-tri-azol-5-one (NTO) is a high energy insensitive explosive. To study the shock initiation process of NTO-based polymer bonded explosive JEOL-1 (32%octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX), 32% NTO, 28% Al and 8% binder system), the cylinder test, the gap experiments and numerical simulation were carried out. Firstly, we got the detonation velocity (7746 m/s) and the parameters of Jones-Wilkins-Lee (JWL) equation of state (EOS) for detonation product by cylinder test and numerical simulation. Secondly, the Hugoniot curve of unreacted explosive for JEOL-1 was obtained calculating the data of pressure and time at different Lagrangian positions. Then the JWL EOS of unreacted explosive was obtained by utilizing the Hugoniot curve as the reference curve. Finally, we got the pressure growth history of JEOL-1 under shock wave stimulation and the parameters of the ignition and growth reaction rate equation were obtained by the pressure-time curves measured by the shock-initiation gap experiment and numerical simulation. The determined trinomial ignition and growth model (IG model) parameters can be applied to subsequently simulation analysis and design of insensitive ammunition with NTO-based polymer bonded explosive.     

The graph association problem: Mathematical models and a lagrangian heuristic

Graph association is the problem of merging many graphs that collectively describe a set of possibly repetitive entities and relationships into a single graph that contains unique entities and relationships. As a form of data association, graph association can be used to identify when two sensors are observing the same object so information from both sensors can be combined and analyzed in a meaningful and consistent way. Graph association between two graphs is related to the problem of graph matching, and between multiple graphs it is related to the common labeling of a graph set (also known as multiple graph matching) problem. This article contribution is to formulate graph association as a binary linear program and introduce a heuristic for solving multiple graph association using a Lagrangian relaxation approach to address issues with between‐graph transitivity requirements. The algorithms are tested on a representative dataset. The developed model formulation was found to accurately solve the graph association problem. Furthermore, the Lagrangian heuristic was found to solve the developed model within 3% of optimal on many problem instances, and found better solutions to large problems than is possible by directly using CPLEX. © 2013 Wiley Periodicals, Inc. Naval Research Logistics, 2013     

网络学习模式识别移动代理因素提取方法研究

从分析网络学习因素的角度出发,提出了利用数据融合理论和使用移动代理技术解决网络学习模式识别的问题。详细分析了网络学习模式中的主要因素,针对网络学习模式识别提出了使用移动代理(MA)进行因素提取的方法。同时运用数据融合技术中分布式缠绕判决模型进行描述,从而使有效地获取网络学习者的学习状态变为可能。也对网络学习因素提取MA的执行环境进行了具体阐述。设计了因素提取MA体系结构,分析了因素提取的执行过程,采用ATP层代理传输协议作为移动代理系统的应用层协议,负责学习模式识别的因素提取。     

复杂声场环境下的近场声全息技术

近场声全息对测量环境的严格要求限制了它在工程实际中的应用,特别是利用互谱法求解全惠面声压时,参考信号的获取极为关键.针对有多个噪声源同时存在的复杂声场环境,提出一种工程解决方法,利用振动信号和声源出口处的信号作为近场声全息的参考信号,在传递函数法的基础上推导出全息面上分离的复声压,由此达到复杂声场环境下的近场声全息重建...