一种改进的灰度预测模型

灰色预测模型通常是GM模型,但预测精度有时不令人满意。在对模型GM做了进一步研究的基础上,提出了一个预测精度较高的新灰色预测模型,并从理论上证明了这种模型可以有效提高建模数据序列的光滑度。最后把此方法应用于东部某镇GDP的建模中,试验结果表明该方法是可行且有效的,所建模型的精度优于传统GM（1,1）模型的精度。     

全局优化的一类新的F-C函数

针对求解全局优化问题,有很多种求解方法。文中提出了一种快速求解一般无约束最优化问题的辅助函数方法。即F-C函数方法。该方法与填充函数法和跨越函数法相比较,既有相同点又有不同点。F-C函数法最大的优点就是在极小化F-C函数阶段中只需要进行一次局部极小化算法就能得到比当前极小值更低的目标函数局部极小点。文中在无Lipschitz连续的条件下,给出了一类新的求解全局优化问题的F-C函数。文中讨论了该F-C函数的优良性质并对该函数设计了相应的算法。最后,通过数值试验表明该F-C函数方法具有有效性和可行性。     

裂纹对石墨烯拉伸力学性能影响的数值仿真

为研究裂纹对石墨烯力学性能的影响,以锯齿型石墨烯为研究对象,基于分子动力学方法,采用Tersoff势函数分析裂纹长度对石墨烯拉伸力学性能的影响以及含有裂纹的石墨烯在不同应变率下的拉伸变形破坏过程.结果表明,裂纹长度的增加大大减小石墨烯的抗拉强度和抗拉应变,对弹性模量有一定影响;裂纹降低石墨烯的抗拉应变对应变率的敏感性,但对于含有裂纹的石墨烯,仍可以增大加载速率来提高石墨烯的抗拉性能.     

一种基于相关函数法铁磁谐振波形研究

对铁磁谐振波形进行了系统的分类分级,提出了一种基于Matlab的相关函数方法,并且利用大量数据进行对比,已经得到了效果验证,经过桂林市电力电容器责任有限公司认证,具有良好的实际效果。     

基于.NET Remoting口令系统的设计

由于B/S模式下客户机对服务器的验证困难,提出了使用Remoting程序对网站的真伪进行验证。方案实现了客户端和服务器端的相互认证、服务器端敏感信息的安全存储和每次认证产生不同的会话密钥,安全分析表明,所提的方案能有效防范钓鱼网站等的常见攻击,增加了系统的安全性。方案使用.NET进行实现,证明是可行的。     

Probabilistic heuristic estimates

Though they constitute the major knowledge source in problem-solving systems, no unified theory of heuristics has emerged. Pearl [15] defines heuristics as criteria, methods, or principles for deciding which among several alternative courses of action promises to be the most effective in order to achieve some goal. The absence of a more precise definition has impeded our efforts to understand, utilize, and discover heuristics. Another consequence is that problem-solving techniques which rely on heuristic knowledge cannot be relied upon to act rationally — in the sense of the normative theory of rationality.To provide a sound basis for BPS, the Bayesian Problem-Solver, we have developed a simple formal theory of heuristics, which is general enough to subsume traditional heuristic functions as well as other forms of problem-solving knowledge, and to straddle disparate problem domains. Probabilistic heuristic estimates represent a probabilistic association of sensations with prior experience — specifically, a mapping from observations directly to subjective probabilities which enables the use of theoretically principled mechanisms for coherent inference and decision making during problem-solving. This paper discusses some of the implications of this theory, and describes its successful application in BPS.This research was made possible by support from Heuristicrats, the National Aeronautics and Space Administration, and the Rand Corporation.     

空管系统中键盘快捷功能的研究与实现

目前国内空中交通管制系统人机界面的操作越来越趋于人性化,从可用、能用到好用的人机界面发展过程中,软件提供快捷的功能和方便的操作流程起到了很重要的作用,因此研究软件开发对键盘快捷键的支持就显得尤其重要。本文对可以实现的方法进行比较,分析实现方法的优劣,提出了一种实现键盘快捷功能的方法。     

Hybrid function projective synchronization of chaotic systems with uncertain time-varying parameters via Fourier series expansion

In this paper, the hybrid function projective synchronization (HFPS) of different chaotic systems with uncertain periodically time-varying parameters is carried out by Fourier series expansion and adaptive bounding technique. Fourier series expansion is used to deal with uncertain periodically time-varying parameters. Adaptive bounding technique is used to compensate the bound of truncation errors. Using the Lyapunov stability theory, an adaptive control law and six parameter updating laws are constructed to make the states of two different chaotic systems asymptotically synchronized. The control strategy does not need to know the parameters thoroughly if the time-varying parameters are periodical functions. Finally, in order to verify the effectiveness of the proposed scheme, the HFPS between Lorenz system and Chen system is completed successfully by using this scheme.     

An on-line learning neural controller for helicopters performing highly nonlinear maneuvers

This paper presents an on-line learning adaptive neural control scheme for helicopters performing highly nonlinear maneuvers. The online learning adaptive neural controller compensates the nonlinearities in the system and uncertainties in the modeling of the dynamics to provide the desired performance. The control strategy uses a neural controller aiding an existing conventional controller. The neural controller is based on a online learning dynamic radial basis function network, which uses a Lyapunov based on-line parameter update rule integrated with a neuron growth and pruning criteria. The online learning dynamic radial basis function network does not require a priori training and also it develops a compact network for implementation. The proposed adaptive law provides necessary global stability and better tracking performance. Simulation studies have been carried-out using a nonlinear (desktop) simulation model similar to that of a BO105 helicopter. The performances of the proposed adaptive controller clearly shows that it is very effective when the helicopter is performing highly nonlinear maneuvers. Finally, the robustness of the controller has been evaluated using the attitude quickness parameters (handling quality index) at different speed and flight conditions. The results indicate that the proposed online learning neural controller adapts faster and provides the necessary tracking performance for the helicopter executing highly nonlinear maneuvers.     

一种新的修正恒模算法

阐述了恒模算法(CMA)、修正恒模算法(MCMA)和判决引导(DD)算法的基本原理。针对CMA和MCMA收敛速度慢,固定步长条件下收敛速度和剩余误差之间存在矛盾的缺陷,在分析CMA误差特性的基础上,利用DD算法误差函数的模值和判决器输出构造新的误差函数,提出了一种新的变步长MCMA。新算法在加快收敛速度的同时保持小的剩余误差。仿真结果表明,新算法比CMA和MCMA收敛速度快,均衡输出剩余码间干扰(ISI)小而且能克服相位偏移,具有很好的实用性。