一种改进的变焦遗传算法

提出一种新的变焦遗传算法,在保持串长不变的条件下,大幅度缩小搜索区间,明显提高了遗传算法的收敛速度和解的精度.本文提出的方法对大范围、高精度情况尤其适合.仿真结果说明了算法的有效 性.􀁽     

最大权-最大基数分配问题算法

本文对经典的分配问题，根据实际需要提出了一个新的应用模型，给出了其实现算法及相关证明．     

信息安全系统中一种高速随机序列发生器的设计与实现

对原来的真随机序列发生器进行研究和分析，指出存在的主要问题是：序列的输出速度较慢，把小波分析理论用于真随机序列发生器，改变原来的输出方式，设计一种新的高速随机序列发生器，以满足快速发展的信息安全系统的要求．     

On-line free-flight path optimization based on improved genetic algorithms

Free flight (FF) is the ideal strategy of current investigations on air traffic management systems, where an on-line flight path optimization algorithm is of top importance. This paper proposes an innovative algorithm with potential real-time properties for FF path optimization, by using an improved genetic algorithm (GA). Two kinds of mathematical models for the on-line flight path optimization problem are proposed to cover the near and far future applications. Several improvements are introduced to the GA to speed up its convergence as well as to improve performance. Simulation results show that the new algorithm is effective and has potential to solve the on-line FF path optimization problem in real time.     

An effective hybrid genetic algorithm for flow shop scheduling with limited buffers

As a typical manufacturing and scheduling problem with strong industrial background, flow shop scheduling with limited buffers has gained wide attention both in academic and engineering fields. With the objective to minimize the total completion time (or makespan), such an issue is very hard to solve effectively due to the NP-hardness and the constraint on the intermediate buffer. In this paper, an effective hybrid genetic algorithm (HGA) is proposed for permutation flow shop scheduling with limited buffers. In the HGA, not only multiple genetic operators based on evolutionary mechanism are used simultaneously in hybrid sense, but also a neighborhood structure based on graph model is employed to enhance the local search, so that the exploration and exploitation abilities can be well balanced. Moreover, a decision probability is used to control the utilization of genetic mutation operation and local search based on problem-specific information so as to prevent the premature convergence and concentrate computing effort on promising neighbor solutions. Simulation results and comparisons based on benchmarks demonstrate the effectiveness of the HGA. Meanwhile, the effects of buffer size and decision probability on optimization performances are discussed.     

一种改进的PIV互相关算法

本文在对两种传统PIV算法进行深入分析的基础上，融合了它们的优点而发展了一种新的速度提取算法一预估搜索法，并给出了算法的具体实现步骤。人工及真实图像实验均表明该法具有求解速度快、计算精度高的优点。     

遗传算法在水轮发电机模糊神经网络励磁控制器设计中的应用研究

本文在分析了模糊神经网络(FNN)控制器的工作原理及设计方法的基础上,提出了一种采用遗传算法优化设计水轮发电机模糊神经网络励磁控制器的方法。其基本过程是利用遗传算法得到初始模糊控制规则,并对初始规则进行过滤,在此基础上利用遗传算法结合模拟退火对得到的模糊神经网络进行训练。仿真结果表明与根据专家经验获得模糊规则和BP算法进行学习的常规FNN比较,采用遗传算法优化设计的模糊神经网络励磁控制器所构成的励磁系统具有更好的动态性能。     

可对称化不定非线性问题的不精确Newton法

本文讨论了处理可对称化不定问题的不精确Newton方法,并针对问题的特殊结构提出了不精确Newton-PSMINRES算法。理论分析与数值试验表明,Newton-PSMINRES算法优于其它处理可对称化不定问题的不精确Newton-Krylov算法。     

给粉机转速失控原因分析与改进

从分析一起300MW机组给粉机转速失控引起锅炉主燃料跳闸(MFT)事故的原因入手，着重剖析WDPF-ⅡDCS系统特殊算法XMASTER的跟踪原理，并提出相应改进措施。     

井下粉尘多参数检测的自适应方法

为提高井下粉尘计重含量检测精度并同时获得粒度分布参数,根据井下粉尘衍射光的角谱特征,提出了一种适合于在单片机上运行的算法。首先将衍射光角谱归一化,使得不同浓度但粒度分布相同的尘样具有相同的归一化角谱,而该角谱与给定模式的角谱的贴近程度则用差值平方和表征。由几个优选模式求得的计重含量或粒度分布取加权平均即可获得待求参数。考虑到现场环境中噪声抑制能力和对尘样多样性的适应能力至关重要,本文中最后给出了针对这两个方面的仿真实验结果。