神经网络敏感性分析的高光谱遥感影像降维与分类方法

高光谱遥感影像由于其巨大的波段数直接导致信息的高冗余和数据处理的复杂,这不仅带来庞大的计算量,而且会损害分类精度。因此,在对高光谱影像进行处理、分析之前进行降维变得非常必要。神经网络敏感性分析可以用于对模型的简化降维,该文将该方法运用于高光谱遥感影像降维中,通过子空间划分弱化波段之间的相关性,利用差分进化算法(DE)优化神经网络结构,采用Ruck敏感性分析方法剔除掉对分类贡献较小的波段,从而实现降维。最后,采用AVIRIS影像进行实验,所提算法相比其他相近的降维与分类方法能获得更高的分类精度,达到85.83%,比其他相近方法中最优方法高出0.31%。

基于Madaline网络敏感性的主动学习算法研究

提出一种基于Madaline网络敏感性的主动学习算法。首先用部分样本训练Madaline网络,然后以Madaline网络输出对其输入在给定样本点附近变化的敏感性为尺度,主动从未参与训练的样本中挑选敏感性相对大的样本继续进行训练,循环反复这个过程直到满足训练要求为止。实验验证了该主动学习算法处理离散分类问题的有效性和可行性。

安全知识模态改善网络钓鱼敏感性认知机理研究

网络钓鱼敏感性的缺乏导致人因成为网络钓鱼中最薄弱的环节。网络安全管理部门给网民灌输安全知识对提高其敏感性以主动防御网络钓鱼具有重要意义。本文基于双重编码理论,借助功能性近红外光谱技术,采用2(前测、后测)×2(言语知识、视觉知识)×2(难识别、易识别)的混合实验设计,探究两种安全知识模态改善网络钓鱼敏感性认知机理的差异。研究结果表明,两种模态安全知识干预均显著提高网络钓鱼敏感性,相比言语知识,视觉知识对网络钓鱼敏感性的影响更积极;两种模态安全知识干预对执行功能的增强效果存在差异,执行功能增强越高时网络钓鱼敏感性效果提升越好;执行功能在安全知识模态改善网络钓鱼敏感性过程中起中介作用;网络钓鱼识别难度存在调节作用,识别高难度的网络钓鱼时,视觉知识干预效果更显著。研究结论揭示了安全知识模态改善网络钓鱼敏感性的认知神经机理,对从模态着手进行安全知识灌输以提高网民的网络钓鱼敏感性具有一定的实践指导作用。

武器装备体系能力矩阵评估方法

针对武器装备体系能力难以客观、定量评估的问题,引入复杂网络理论,提出了基于矩阵运算的武器装备体系能力评估方法。分析了武器装备体系能力的概念,建立了武器装备体系的复杂层次网络模型,描述了装备网络的组成、运行过程,定义了装备网络的矩阵描述方法和矩阵运算规则,提出了装备网络作战能力描述参数,给出了装备网络能力的矩阵计算方法,进行了影响因素分析,最后通过实例验证了方法可行性、有效性和灵活性。

Simulation of phytoplankton biomass in Quanzhou Bay using a back propagation network model and sensitivity analysis for environmental variables

Prediction and sensitivity models,to elucidate the response of phytoplankton biomass to environmental factors in Quanzhou Bay,Fujian,China,were developed using a back propagation(BP) network.The environmental indicators of coastal phytoplankton biomass were determined and monitoring data for the bay from 2008 was used to train,test and build a three-layer BP artificial neural network with multi-input and single-output.Ten water quality parameters were used to forecast phytoplankton biomass(measured as chlorophyll-a concentration).Correlation coefficient between biomass values predicted by the model and those observed was 0.964,whilst the average relative error of the network was-3.46% and average absolute error was 10.53%.The model thus has high level of accuracy and is suitable for analysis of the influence of aquatic environmental factors on phytoplankton biomass.A global sensitivity analysis was performed to determine the influence of different environmental indicators on phytoplankton biomass.Indicators were classified according to the sensitivity of response and its risk degree.The results indicate that the parameters most relevant to phytoplankton biomass are estuary-related and include pH,sea surface temperature,sea surface salinity,chemical oxygen demand and ammonium.

A fault diagnosis method of reciprocating compressor based on sensitive feature evaluation and artificial neural network

A method combining information entropy and radial basis function network is proposed for fault automatic diagnosis of reciprocating compressors.Aiming at the current situation that the accuracy rate of reciprocating compressor fault diagnosis which depends on manual work in engineering is very low,we apply information entropy evaluation to select the sensitive features and make clear the corresponding relationship of characteristic parameters and failures.This method could reduce the feature dimension.Then,a complete fault diagnosis architecture has been built combining with radial basis function network which has the fast and efficient characteristics.According to the test results using experimental and engineering data,it is observed that the proposed fault diagnosis method improves the accuracy of fault automatic diagnosis effectively and it could improve the practicability of the monitoring system.

飞机网络战斗生存力(ACCS)解析

飞机网络战斗生存力(ACCS)是飞机生存力的重要组成部分,为了进一步提高飞机生存力设计水平,必须重视飞机网络战斗生存力设计。遵循飞机战斗生存力(ACS)设计原理和框架,类比解析了飞机网络战斗生存力的基本概念和原理框架,给出了优化飞机网络战斗生存力的设计实例,说明了在实际飞机设计时,过分强调网络武器或忽视网络武器都是片面的。给出了6个敏感性减缩措施和6个易损性减缩措施,飞机设计时需要对各种提高飞机生存力的措施进行权衡,力争设计并制造出能力强大、成本效益更好的军用飞机。