基于进化算法的常减压装置模拟

提出了基于优选优生进化算法（Select—best and prepotency evolution algorithm，SPEA）的常减压装置模拟方法。以各塔的温度分布为目标，基于生产过程和分析数据，采用SPEA确定各塔板Murphree效率，从而精确描述各塔板平衡偏离程度。在实际应用中，获得具有良好精度的常减压装置模型。系统分析了SPEA算法的关键参数——优选领域大小与计算复杂性及寻优性能之间的关系，结果显示其取值为群体规模的10％最为合适。     

基于遗传算法的服装工序编排规划

本文讨论了建立服装工序编排系统的必要性，在进行服装工序拆分、合并的基础上，应用遗传算法建立了以流水线平衡为目标的服装工序编排模型．     

Note on ‘Construction of Double Sampling s‐Control Charts for Agile Manufacturing’

He and Grigoryan (Quality and Reliability Engineering International 2002; 18 :343–355) formulated the design of a double‐sampling (DS) s control chart as an optimization problem and solved it with a genetic algorithm. They concluded that the DS s control charts can be a more economically preferable alternative in detecting small shifts than traditional s control charts. We explain that, since they only considered the average sample size when the process is in control, their conclusion is questionable. Copyright © 2006 John Wiley & Sons, Ltd.     

基于遗传算法的门限自回归模型在浅层地下水位预测中的应用

提出了建立门限自回归模型的一种简便通用的方法，用遗传算法可同时优化门限值和自回归系数．实例计算的结果说明了其可行性和有效性．该方法在各种工程时序预测中具有广泛的应用价值     

A Search for Hidden Relationships: Data Mining with Genetic Algorithms

This paper presents an algorithm that permits the search for dependencies among sets of data (univariate or multivariate time-series, or cross-sectional observations). The procedure is modeled after genetic theories and Darwinian concepts, such as natural selection and survival of the fittest. It permits the discovery of equations of the data-generating process in symbolic form. The genetic algorithm that is described here uses parts of equations as building blocks to breed ever better formulas. Apart from furnishing a deeper understanding of the dynamics of a process, the method also permits global predictions and forecasts. The algorithm is successfully tested with artificial and with economic time-series and also with cross-sectional data on the performance and salaries of NBA players during the 94–95 season.     

连铸温度场数值模拟及冷却水参数优化

由于用实验方法来研究工艺参数对铸坯温度场的影响较困难,故而提出了一种在冶金冷却条件指导下的启发式GA(遗传算法)数值模拟优化方法,为优化工艺参数提供了理论依据,并在优化基础上采用MIMO(多输入多输出)系统PID(比例积分微分)控制器实现了二冷段配水的优化控制,改善了铸坯的质量.     

激光切割工艺参数优化数据库系统

用Visual Basic 6.0和用SQL server 7.0设计了激光切割工艺参数数据查询系统.能实现对常用材料的激光切割工艺参数进行查询.同时,提供了方便的数据库维护方法,提出用户基于Web技术的数据库更新方法.     

一种改进的共同进化遗传算法及其应用

将共同进化遗传算法应用于临床营养决策优化中,虽然取得了一定成果,但算法中仍存在早熟现象、局部搜索能量弱等问题,为此提出一种改进的共同进化模型。算法使用新的子群体划分方法和交叉算子,引入精英保留策略、信息交换原则和小生境技术。通过对糖尿病营养治疗的仿真表明,改进后的算法在保证群体多样性和避免早熟现象的前提下,提高了算法的局部和全局寻优能力,且膳食配方中营养素达标率符合要求,满足专家建议的糖尿病饮食需求。     

A genetic‐based neuro‐fuzzy controller for blind equalization of time‐varying channels

This paper presents a neuro‐fuzzy network (NFN) where all its parameters can be tuned simultaneously using genetic algorithms (GAs). The approach combines the merits of fuzzy logic theory, neural networks and GAs. The proposed NFN does not require a priori knowledge about the system and eliminates the need for complicated design steps such as manual tuning of input–output membership functions, and selection of fuzzy rule base. Although, only conventional GAs have been used, convergence results are very encouraging. A well‐known numerical example derived from literature is used to evaluate and compare the performance of the network with other equalizing approaches. Simulation results show that the proposed neuro‐fuzzy controller, all parameters of which have been tuned simultaneously using GAs, offers advantages over existing equalizers and has improved performance. From the perspective of application and implementation, this paper is very interesting as it provides a new method for performing blind equalization. The main contribution of this paper is the use of learning algorithms to train a feed‐forward neural network for M‐ary QAM and PSK signals. This paper also provides a platform for researchers of the area for further development. Copyright © 2008 John Wiley & Sons, Ltd.