A misclassification cost‐minimizing evolutionary–neural classification approach

Machine learning algorithms that incorporate misclassification costs have recently received considerable attention. In this paper, we use the principles of evolution to develop and test an evolutionary/genetic algorithm (GA)‐based neural approach that incorporates asymmetric Type I and Type II error costs. Using simulated, real‐world medical and financial data sets, we compare the results of the proposed approach with other statistical, mathematical, and machine learning approaches, which include statistical linear discriminant analysis, back‐propagation artificial neural network, integrated cost preference‐based linear mathematical programming‐based minimize squared deviations, linear integrated cost preference‐based GA, decision trees (C 5.0, and CART), and inexpensive classification with expensive tests algorithm. Our results indicate that the proposed approach incorporating asymmetric error costs results in equal or lower holdout sample misclassification cost when compared with the other statistical, mathematical, and machine learning misclassification cost‐minimizing approaches. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006.     

快速傅立叶变换用于Fokker-Planck-Landau方程的数值求解

利用谱方法和FFT技术对Fokker-Planck-Landau方程进行了数值求解,研究了均匀空间条件下粒子在速度空间的分布函数随时间的演化。数值计算表明,所用计算方法能够很好地满足质量、动量和能量守恒要求,计算速度与有限差分方法相比大大加快。     

Cooperative interception with fast multiple model adaptive estimation

For the case that two pursuers intercept an evasive target, the cooperative strategies and state estimation methods taken by pursuers can seriously affect the guidance accuracy for the target, which performs a bang For the case that two pursuers intercept an evasive target, the cooperative strategies and state estimation methods taken by pursuers can seriously affect the guidance accuracy for the target, which performs a bang-bang evasive maneuver with a random switching time. Combined Fast multiple model adaptive estimation (Fast MMAE) algorithm, the cooperative guidance law takes detection configuration affecting the accuracy of interception into consideration. Introduced the detection error model related to the line-of-sight (LOS) separation angle of two interceptors, an optimal cooperative guidance law solving the optimization problem is designed to modulate the LOS separation angle to reduce the estimation error and improve the interception performance. Due to the uncertainty of the target bang-bang maneuver switching time and the effective fitting of its multi-modal motion, Fast MMAE is introduced to identify its maneuver switching time and estimate the acceleration of the target to track and intercept the target accurately. The designed cooperative optimal guidance law with Fast MMAE has better estimation ability and interception performance than the traditional guidance law and estimation method via Monte Carlo simulation.     

基于改进核极限学习机和集成学习理论的目标机动轨迹预测

为了提高目标轨迹预测的精度以及预测模型的泛化能力,提出基于改进蝙蝠算法优化的核极限学习机(Kernel Extreme Learning Machine,KELM)和集成学习理论目标机动轨迹预测模型。构建KELM模型,并采用改进的蝙蝠算法对KELM的参数进行优化;以优化后的KELM神经网络为弱预测器,结合集成学习算法生成强预测器,通过训练不断优化强预测的结构和参数,得到一种基于集成学习理论的目标机动轨迹预测模型;基于不同规模的样本,将所得预测模型与逆传播神经网络、支持向量机和极限学习机等模型进行对比分析。仿真结果表明:所提目标机动轨迹预测模型具有较好的预测精度和泛化能力。     

区间正交小波变换域FLP算法及其在捷联寻北中的应用

针对机抖激光陀螺角随机游走和发动机干扰等影响静态捷联寻北精度的问题,提出了一种新的基于区间正交小波变换的前向线性预测算法。该算法利用前向线性预测技术以及区间正交小波变换抑制边界效应的能力,有效地减小了角随机游走和发动机干扰。车载实验证明该算法的有效性。     

柔性加工设备机电系统的动力学模型与辨识

在剖析柔性加工设备机电系统结构、信息传递链等基础上，建立柔性加工设备机电系统较精确的动力学模型，并研制相应硬件，实现实时在线模型参数辨识，排除变工况与加工过程的时变性对状态监测与故障诊断的影响，为实现柔性加工环境下多变工况加工过程的实时状态监测、故障诊断与故障预警打下基础。     

关于弹药贮存可靠性要求的若干问题

本文根据我国弹药产品的特点,提出了弹药贮存可靠性指标的确定程序、贮存可靠性指标的内容及其对应的贮存条件。从原材料的选择、元器件的控制、结构设计、包装设计,生产工艺、组装时间,贮存管理等方面,论述了贮存可靠性的保证措施,并提出了三种贮存可靠性预计方法。     

弹药可靠贮存寿命预计方法

本文针对现阶段弹药贮存可靠性数据不充分和研制阶段贮存可靠性评定比较困难的现状,提出了弹药可靠贮存寿命的4种预计方法,对每种方法的适用场合、实施步骤,特别是对相似产品法在弹药可靠贮存寿命中的应用做了较为详细的介绍。     

机械失效分析、预测和预防的基本方法及应用

本文对机械失效分析、预测和预防的基本内容、方法以及在舰艇动力装置中的若干应用,进行了较为全面的论述,以期促进这门工程技术在海军装备管理和维修中的应用。     

FFT的8088汇编语言程序实现

本文针对使用8088汇编语言实现基2FFT 的难点,就旋转因子的求取、比例系数的选择、16位乘积的获得以及运算溢出等问题提出了有效的解决方法,并给出了具体程序.从而,可使 FFT 运算速度较单纯运行相应的高级语言程序提高20倍左右.