BP人工神经网络的应用及其实现技术

简述了BP人工神经网络的算法原理 ,利用Batchnet程序对一个三层BP人工神经网络进行了设计 ,应用Matlab中人工神经网络工具箱设计了一个用于函数逼近的BP人工神经网络 ,最后 ,运用Matlab中可视化工具Simulink对一个BP人工神经网络例子进行了仿真 ,通过例子 ,探讨了BP人工神经网络的应用并介绍目前几种实用的BP人工神经网络实现技术 .     

用于无人机着陆的图像处理算法

随着无人机着陆图像处理算法的不断研究和发展,在分析小波变换对噪声和边缘点的影响规律的基础上,结合多尺度乘积的特性,采用了一种基于小波变换的多尺度积的边缘检测新算法.通过边缘检测实验并和其他算法作比较,该算法能有效抑制噪声,获得清晰丰富的边缘且定位精度高,为进一步的无人机着陆图像处理提供一个很好的工具.     

汇编语言动态分析工具中的程序插装技术

根据8086/8088语言的结构化特点,提出了程序插装的概念及其实现方法,并基于插装研制出一种动态分析工具,从而实现了对程序分支及语句的自动测试功能.     

码资源受限系统中的碎片整理算法及定时机制的研究

在分析传统码资源静态分配算法缺陷的基础上,研究了直接合并碎片整理算法和最小分支搜索不完全码碎片整理算法.同时研究了碎片整理算法中的关键问题:碎片整理的时机,即定时机制问题.提出了一种获取定时参数的方法,并利用计算机仿真工具对定时机制进行了仿真,验证了理论结论.     

浅谈对数据库文件的加密

本文通过分析数据库文件的结构,探讨出一种简便有效的加密算法,并用此算法编制了汇编语言程序.     

软件静态分析工具评析

为了在软件生命周期的编码阶段尽可能多地发现软件缺陷以降低软件成本和开发时间,需要对被测程序源代码实施软件静态分析。软件静态分析最有效的手段是使用软件静态分析工具。针对C程序常见的软件缺陷,通过对几种主流静态分析工具的功能性对比分析,探讨了软件静态分析工具的优缺点及影响软件静态分析工具选择的诸多因素,可为软件测试人员选择合适的软件静态分析工具提供参考。     

软件静态分析工具综述

为了在软件生命周期的编码阶段尽可能多地发现软件缺陷以降低软件成本和开发时间,需要对被测程序源代码实施软件静态分析,软件静态分析最有效的手段是使用软件静态分析工具。针对C程序常见的软件缺陷,通过对几种主流静态分析工具的功能性对比分析,探讨了软件静态分析工具的优缺点及影响软件静态分析工具选择的诸多因素,为软件测试人员选择适合自己的软件静态分析工具提供参考。     

基于多层循环并行化的负载平衡优化

负载平衡是并行处理中的一个重要概念。参与一个程序执行的各处理机所承担的工作量是否均衡直接影响该程序的并行性能。本文对面向MPP系统程序循环级并行化中负载平衡的优化进行了探讨,提出了优化策略及其实施算法。     

求刚性中子动力学方程数值解的新方法

中子动力学方程是刚性方程,数值计算很费机时,为减少计算机时提出了许多算法,常用的有隐式盖分法、多步法和自动变步长法等,著名的方法有吉尔方法和埃米特方法.但这些方法的计算程序复杂且总计算时间减少不明显.消去刚性法是一个全新的算法,稳定步长可达到20 s,计算时间大大下降.     

连接弧与两已知弧公切点坐标的通用算法

本文介绍一种计算机弧相公切点通用程序的算法。这种算法适用于给定半径的圆弧和两已知圆相切的各种情况。该算法全部采用简单的代数运算,避免了三角函数运算,提高了运算速度,并且由于采用符号函数和较合理的分类,使得程序简洁明了。     

遗传算法在装备调拨辅助决策中的应用

利用遗传算法求解装备调拨中的路径优化问题和运输装载问题,并利用MATLAB进行了实例仿真,对装备调拨的辅助决策具有积极的意义。     

A hard knapsack problem

In this article we develop a class of general knapsack problems which are hard for branch and bound algorithms. The number of alternate optimal solutions for these problems grows exponentially with problem parameters. In addition the LP bound is shown to be ineffective. Computational tests indicate that these problems are truly difficult for even very small problems. Implications for the testing of algorithms using randomly generated problems is discussed.     

基于类成员后向切片的面向对象程序回归测试

程序切片是一种重要的程序分析方法,类成员级粒度的切片技术目前仅仅有Tip提出的类层次切片技术.Tip提出的类层次切片技术其分析基础是Rossie-Friedman的类层次框架,但主要用于面向对象程序的优化,并不适用于回归测试.本文基于Rossie-Friedman的类层次框架提出类成员后向切片方法,并提出一个覆盖类的方法一级的回归测试策略.     

Evasion policies for a vessel being chased by pirate skiffs

Piracy attack is a serious safety problem for maritime transport worldwide. Whilst various strategic actions can be taken, such as rerouting vessels and strengthening navy patrols, this still cannot completely eliminate the possibility of a piracy attack. It is therefore important for a commercial vessel to be equipped with operational solutions in case of piracy attacks. In particular, the choice of a direction for rapidly fleeing is a critical decision for the vessel. In this article, we formulate such a problem as a nonlinear optimal control problem. We consider various policies, such as maintaining a straight direction or making turns, develop algorithms to optimize the policies, and derive conditions under which these policies are effective and safe. Our work can be used as a real‐time decision making tool that enables a vessel master to evaluate different scenarios and quickly make decisions.     

指控系统智能反汇编软件开发

针对没有提供软件清单的指控系统,在对其硬件环境十分熟悉的基础上,采用模拟跟踪程序执行路径的方法,开发了某型指控系统的智能反汇编软件。它可将固化在该系统EPROM中的机器码程序自动地反汇编成汇编源程序,形成打印文件存盘,以便列出程序清单供阅读和修改,进而改善指控系统功能。     

浅析军事医学语言的现实意义

军事医学语言是军事语言学的一个分支学科。古今中外的军事医学实践表明,军事医学语言在医学工作中发挥着重要作用,有时对医疗效果起着决定性作用。我国古代十分重视运用军事医学语言保障部队提高医疗效果的作用。但是,军事医学语言学科还不成体系,严重影响着军事医学工作科学效能的发挥。加快军事医学语言学科体系建设,已经成为当前巩固和提高部队战斗力中一个不可忽视的课题。     

汇编语言的单元测试技术研究

汇编语言具有非结构化、非标准化、硬件相关性高、灵活性极大等特性,单元测试难度较大.针对汇编语言的特点,论述了汇编语言单元测试过程中功能测试、结构覆盖率测试和性能测试的方法和步骤.     

Short‐term capacity allocation problem with tool and setup constraints

We consider a short‐term capacity allocation problem with tool and setup constraints that arises in the context of operational planning in a semiconductor wafer fabrication facility. The problem is that of allocating the available capacity of parallel nonidentical machines to available work‐in‐process (WIP) inventory of operations. Each machine can process a subset of the operations and a tool setup is required on a machine to change processing from one operation to another. Both the number of tools available for an operation and the number of setups that can be performed on a machine during a specified time horizon are limited. We formulate this problem as a degree‐constrained network flow problem on a bipartite graph, show that the problem is NP‐hard, and propose constant factor approximation algorithms. We also develop constructive heuristics and a greedy randomized adaptive search procedure for the problem. Our computational experiments demonstrate that our solution procedures solve the problem efficiently, rendering the use of our algorithms in real environment feasible. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005     

Screening multi-dimensional heterogeneous populations for infectious diseases under scarce testing resources,with application to COVID-19

Testing provides essential information for managing infectious disease outbreaks, such as the COVID-19 pandemic. When testing resources are scarce, an important managerial decision is who to test. This decision is compounded by the fact that potential testing subjects are heterogeneous in multiple dimensions that are important to consider, including their likelihood of being disease-positive, and how much potential harm would be averted through testing and the subsequent interventions. To increase testing coverage, pooled testing can be utilized, but this comes at a cost of increased false-negatives when the test is imperfect. Then, the decision problem is to partition the heterogeneous testing population into three mutually exclusive sets: those to be individually tested, those to be pool tested, and those not to be tested. Additionally, the subjects to be pool tested must be further partitioned into testing pools, potentially containing different numbers of subjects. The objectives include the minimization of harm (through detection and mitigation) or maximization of testing coverage. We develop data-driven optimization models and algorithms to design pooled testing strategies, and show, via a COVID-19 contact tracing case study, that the proposed testing strategies can substantially outperform the current practice used for COVID-19 contact tracing (individually testing those contacts with symptoms). Our results demonstrate the substantial benefits of optimizing the testing design, while considering the multiple dimensions of population heterogeneity and the limited testing capacity.