装备技术人才军民融合定制化培训模式

本文依托军民融合国家战略基础,对比国内外发展现状,分析现行培训形式的不足之处,梳理军民融合式培训需求,将军民融合理念贯穿人才培训全过程。针对军事体制调整后的专业技师和工程师等专业技术骨干,形成一套培训要求“专业化”对接、培训师资“军学研”共建、培训内容“菜单式”定制、培训样式“多手段”并举以及培训效果“递进式”发挥的装备技术人才军民融合定制化培训模式,并且有针对性地提出军民融合基地化培训的建设框架,从培训管理、培训实施等方面提出方法,为部队拓宽专业技术人才培训通道,实现被动式培训向主动式培训转变,提高装备实战化保障能力提供借鉴和指导。     

高频地波雷达目标高度估计的AR模型方法

高度估计对于高频地波雷获取三维信息、提高预警能力很有意义。然而目标RCS的随机起伏对高度估计产生严重影响,通过对RCS随机起伏的AR模型建模和模型参数的自适应估计,提出了在RCS变化的条件下高度估计的扩展卡尔曼滤波算法。通过Monte Carlo仿真和外场试验数据的处理,验证了该方法对抑制RCS随机起伏、提高高度估计精度的有效性。     

谈国人视野中的中国崛起

随着中国的快速发展,中国正在崛起已成为国内外有目共睹的事实。一些西方学者把中国崛起看成是对世界和平与发展的"威胁",中国人民则根据中国崛起所带来的巨大变化,把中国崛起看成是对人类文明的重大贡献。对中华民族而言,中国崛起造福13亿中国人,使中国人民基本过上了幸福的小康生活;对全人类来说,中国崛起惠及全世界,推动了世界经济的发展乃至人类文明的进步。     

用物理模型求一类积分问题

微积分是大学物理学中解决许多物理问题所采用的普遍方法,它和许多物理问题密切相关。对某类积分类型,从数学角度来求解,难度校大,如果对于这些复杂的数学积分问题,建立起相关的物理模型,就会使数学问题变得简单。     

3D laser scanning strategy based on cascaded deep neural network

A 3D laser scanning strategy based on cascaded deep neural network is proposed for the scanning system converted from 2D Lidar with a pitching motion device. The strategy is aimed at moving target detection and monitoring. Combining the device characteristics, the strategy first proposes a cascaded deep neural network, which inputs 2D point cloud, color image and pitching angle. The outputs are target distance and speed classification. And the cross-entropy loss function of network is modified by using focal loss and uniform distribution to improve the recognition accuracy. Then a pitching range and speed model are proposed to determine pitching motion parameters. Finally, the adaptive scanning is realized by integral separate speed PID. The experimental results show that the accuracies of the improved network target detection box, distance and speed classification are 90.17%, 96.87% and 96.97%, respectively. The average speed error of the improved PID is 0.4239°/s, and the average strategy execution time is 0.1521 s. The range and speed model can effectively reduce the collection of useless information and the deformation of the target point cloud. Conclusively, the experimental of overall scanning strategy show that it can improve target point cloud integrity and density while ensuring the capture of target.     

An approach for predicting digital material consumption in electronic warfare

Electronic warfare is a modern combat mode, in which predicting digital material consumption is a key for material requirements planning (MRP). In this paper, we introduce an insensitive loss function (ε) and propose a ε-SVR-based prediction approach. First, we quantify values of influencing factors of digital equipments in electronic warfare and a small-sample data on real consumption to form a real combat data set, and preprocess it to construct the sample space. Subsequently, we establish the ε-SVR-based prediction model based on “wartime influencing factors - material consumption” and perform model training. In case study, we give 8 historical battle events with battle damage data and predict 3 representative kinds of digital materials by using the proposed approach. The results illustrate its higher accuracy and more convenience compared with other current approaches. Taking data acquisition controller prediction as an example, our model has better prediction performance (RMSE = 0.575 7, MAPE (%) = 12.037 6 and R² = 0.996 0) compared with BP neural network model (RMSE = 1.272 9, MAPE (%) = 23.577 5 and R² = 0.980 3) and GM (1, 1) model (RMSE = 2.095 0, MAPE (%) = 24.188 0 and R² = 0.946 6). The fact shows that the approach can be used to support decision-making for MRP in electronic warfare.     

A fast-running method for blast load prediction shielding by a protective barrier

This study presents a simplified blast load prediction method on structures behind a protective barrier. The proposed method is basically an empirical approach based on Kingery-Bulamsh (K-B) chart and finite element (FE) analysis results. To this end, this study divides the structure into three regions by three critical points. Blast loads at each critical point can be calculated based on K-B chart and an approximation according to FE analysis results. Finally, peak reflected overpressure and impulse distributed on the structure can be approximately estimated by linearly connecting blast loads at each critical point. In order to confirm a feasibility of the proposed method, a series of numerical simulations were carried out. The simulation results were compared with FE analysis results which are presented in the open literature. From such comparisons, it was found that the proposed method is applicable to predict blast loads on structures behind a protective barrier.     

Assortment optimization with position effects under the nested logit model

We study the assortment optimization problem with position effects under the nested logit model, whose goal is to find the revenue-maximizing subset of products as well as their corresponding display positions. In this joint assortment-position optimization problem, the choices of products are affected by not only their qualities and prices but also the positions where they are displayed. Despite determining the assortment and their corresponding display positions sequentially, we propose to solve this problem in an integrated way to obtain the optimal solution. We formulate this problem as a nonlinear binary integer programming model and develop a dynamic programming based solution approach to obtain the optimal assortment-position assignments. We carry out extensive numerical experiments to evaluate the benefit of our integrated approach. The most important insight we discover is that it is not necessarily better to put the most attractive products in the best position. Moreover, we show that compared to the sequential approaches, our approach can improve revenue by 10.38% on average, which suggests that firms should take into consideration position effects when making assortment decisions. Finally, we discuss results related to two extensions of this problem, that is, the special case when positions are preassigned to nests, and the joint assortment-position-price optimization problem.     

战情生成软件(STAGE)中的若干问题

首先简要介绍了战情生成软件(STAGE)的功能和组成,然后描述了在使用STAGE中所遇到的电子地图的转入、军标的本土化、用户模型的嵌入、远程节点的控制、运行前初始战情的获取、数据库问数据交换和战情运行的实时性等问题,最后给出了解决这些问题的方法.     

基于细分小波的图像压缩算法研究

层次细节模型LOD(Level of detail)和感兴趣区域模型ROI(Region of Interesting)是静止图像压缩及网络传输技术中两个重要模型.通过将灰度图像网格化,并在图像网格上进行B样条细分小波变换,实现了图像的LOD压缩算法.并通过Gouraud明暗处理技术将网格还原成压缩过的灰度图像;同时,该算法还可方便地通过ROI区域选择,使ROI区域比背景区域获得更好的图像质量.