遗传算法综述

遗传算法来源于进化论和群体遗传学，是计算智能的重要组成部分，正受到众多学科的高度重视。本文系统综述了遗传算法的发展历程，理论研究和应用研究，并进行了分析和评价。  

一种新型的网络安全实现方法--基因计算机

针对目前对网络安全性能要求的不断提高 ,各种类型的防火墙又都存在一定的缺陷 ,该文基于遗传的概念 ,提出了一种新型的网络安全实现方法——基因计算机 .  

Automatic detection of parsimony for heteroskedastic time series processes

 The paper proposes a new multiple-representation geno-mathematical algorithm for coping with ill-conditioned time series processes through competing nonlinear model formulations. Extensive testing and comparisons to a rigorous statistical time series package indicate that the geno-mathematical search-machine is effective and robust for modelling complicated time series. The new algorithm is used to model a representative set of global asset returns. The diagnostic tests prove that the ARCH-effects of the difficult nonlinear processes are annihilated completely in both full and reduced model variants.  

A Neuro-Genetic Algorithm for Heteroskedastic Time-Series Processes Empirical Tests on Global Asset Returns

 The paper proposes a new neuro-genetic hybrid algorithm (NGHA) for coping with ill-conditioned time-series processes. Extensive testing and comparisons to various heteroskedastic models indicate that the neuro-genetic algorithm may be a useful device for modelling complicated time series. NGHA is used to model a factor price series corresponding to the European factor of a representative set of global asset returns. NGHA provides a platform for adapting evolutionary computation to the search for suitable networks for observed time series.  

基因表达式编程的理论研究综述*

对新兴的基因表达式编程算法在国内外的理论研究现状进行了系统的研究，剖析了GEP的基本原理和特点，并对国内外关于GEP理论和算法的研究现状进行系统的讨论，最后根据笔者的见解探讨了未来研究的重点方向。  

Continuous Levels‐of‐Detail and Visual Abstraction for Seamless Molecular Visualization

Molecular visualization is often challenged with rendering of large molecular structures in real time. We introduce a novel approach that enables us to show even large protein complexes. Our method is based on the level‐of‐detail concept, where we exploit three different abstractions combined in one visualization. Firstly, molecular surface abstraction exploits three different surfaces, solvent‐excluded surface (SES), Gaussian kernels and van der Waals spheres, combined as one surface by linear interpolation. Secondly, we introduce three shading abstraction levels and a method for creating seamless transitions between these representations. The SES representation with full shading and added contours stands in focus while on the other side a sphere representation of a cluster of atoms with constant shading and without contours provide the context. Thirdly, we propose a hierarchical abstraction based on a set of clusters formed on molecular atoms. All three abstraction models are driven by one importance function classifying the scene into the near‐, mid‐ and far‐field. Moreover, we introduce a methodology to render the entire molecule directly using the A‐buffer technique, which further improves the performance. The rendering performance is evaluated on series of molecules of varying atom counts.