一种基于改进的ROUSTIDA算法的数据补齐方法

针对ROUSTIDA数据补齐方法存在的问题,提出了一种改进的ROUSTIDA数据补齐方法.该方法首先将条件属性与决策属性区分对待,优先填补决策属性值,避免了不一致决策表的产生;然后,在决策属性相同的前提下填补条件属性缺失值,扩展了原算法的使用范围;最后,通过一个实例说明改进算法补齐后的决策表的确能够获得更集中的决策规则...     

导弹贮存寿命预估的组合模型

在分析比较了几种寿命预估方法优缺点的基础上,针对单一预估方法在解决实际问题中所暴露的局限性,优选了GM-BPNN组合预估模型。该组合模型既利用了灰色预估理论具有所需要的样本数据少、原理简单、运算方便、短期预估精度高、可检验等优点,也发挥了神经网络并行计算、容错能力强、自适应能力强等优点。最后利用该组合模型对弹上某设备寿命进行了预估,取得了较好的预测效果。     

数据挖掘故障诊断专家系统

为了及时准确地对防空导弹飞行试验故障进行诊断,克服传统专家系统获取专家知识的瓶颈,立足于防空导弹飞行试验历史数据,利用数据挖掘的方法获得飞行试验故障模式判定决策树,进而得出导弹故障判定规则,形成故障诊断专家知识库,构建防空导弹故障诊断专家系统.这使数据挖掘和专家系统两者的优点得到充分发挥.     

弹性基上圆柱管弯曲行为的高阶剪切梁理论解

以弹性基上圆柱管为研究对象,基于高阶剪切变形梁理论推导了Winkler弹性基圆柱管弯曲变形的高阶剪切梁理论控制方程,给出四种典型工况弯曲问题的精确解.研究表明,无须假设剪切修正系数,只需引入适当横截面翘曲形状函数,高阶梁理论在圆柱管内外表面满足剪应力τxr为零的边界条件,且对于不同长径比和厚径比的圆柱管弯曲问题均能提供...     

A Fuzzy Cluster and Retinex Theory-based Variation Model for Inhomogenous Image Segmentation

A variational inhomogeneous image segmentation model based on fuzzy membership functions and Retinex theory is proposed by introducing the fuzzy membership function.The existence of the solution of the proposed model is proved theoretically.A valid algorithm is designed to make numerical solution of the model under the framework of alternating minimization.The last experimental results show that the model can make segmentation of the real image with intensity inhomogeneity effectively.     

Buckling analysis of embedded graphene oxide powder-reinforced nanocomposite shells

In this study, the buckling analysis of a Graphene oxide powder reinforced (GOPR) nanocomposite shell is investigated. The effective material properties of the nanocomposite are estimated through Halpin-Tsai micromechanical scheme. Three distribution types of GOPs are considered, namely uniform, X and O. Also, a first-order shear deformation shell theory is incorporated with the principle of virtual work to derive the governing differential equations of the problem. The governing equations are solved via Galerkin's method, which is a powerful analytical method for static and dynamic problems. Comparison study is performed to verify the present formulation with those of previous data. New results for the buckling load of GOPR nanocomposite shells are presented regarding for different values of circumfer-ential wave number. Besides, the influences of weight fraction of nanofillers, length and radius to thickness ratios and elastic foundation on the critical buckling loads of GOP-reinforced nanocomposite shells are explored.     

Real-time prediction of projectile penetration to laminates by training machine learning models withfinite element solver as the trainer

Studies on ballistic penetration to laminates is complicated, but important for design effective protection of structures. Experimental means of study is expensive and can often be dangerous. Numerical simu-lation has been an excellent supplement, but the computation is time-consuming. Main aim of this thesis was to develop and test an effective tool for real-time prediction of projectile penetrations to laminates by training a neural network and a decision tree regression model. A large number of finite element models were developed;the residual velocities of projectiles fromfinite element simulations were used as the target data and processed to produce sufficient number of training samples. Study focused on steel 4340tpolyurea laminates with various configurations. Four different 3D shapes of the projectiles were modeled and used in the training. The trained neural network and decision tree model was tested using independently generated test samples using finite element models. The predicted projectile velocity values using the trained machine learning models are then compared with thefinite element simulation to verify the effectiveness of the models. Additionally, both models were trained using a published experimental data of projectile impacts to predict residual velocity of projectiles for the unseen samples. Performance of both the models was evaluated and compared. Models trained with Finite element simulation data samples were found capable to give more accurate predication, compared to the models trained with experimental data, becausefinite element modeling can generate much larger training set, and thus finite element solvers can serve as an excellent teacher. This study also showed that neural network model performs better with small experimental dataset compared to decision tree regression model.     

Size dependent free vibration analysis of functionally graded piezoelectric micro/nano shell based on modified couple stress theory with considering thickness stretching effect

Higher-order shear and normal deformation theory is used in this paper to account thickness stretching effect for free vibration analysis of the cylindrical micro/nano shell subjected to an applied voltage and uniform temperature rising. Size dependency is included in governing equations based on the modified couple stress theory. Hamilton's principle is used to derive governing equations of the cylindrical micro/nano shell. Solution procedure is developed using Navier technique for simply-supported boundary conditions. The numerical results are presented to investigate the effect of significant parameters such as some dimensionless geometric parameters, material properties, applied voltages and temperature rising on the free vibration responses.     

现代机载探测系统多源信息融合算法

针对机载探测系统的特性,应用Dempster-Shafer(D-S)证据理论和主观Bayes的组合算法,对来自机载SAR雷达、机载前视红外搜索跟踪系统(IRS)、电子支援系统(ESM)等探测系统多次观测所获得的数据,以及来自地面的电子情报(ELINT)的不同信息进行实时融合、识别,进而确定攻击对象.通过实例进行仿真证明,这种组合算法适用于不同类传感器和不同格式信息间的融合,适合于复杂信号环境.     

新型驱护舰编队舰空导弹防御体系射击效能研究

针对新型驱护舰编队舰空导弹防御体系射击效能评估这一难题,对其射击效能准则进行了确立,提出了基于排队论的射击效能评估模型,对体系射击效能进行仿真计算,总结出能对系统射击效能做出准确评估的方法,并利用实例对模型进行了验证。