智能蚂蚁算法及其在电信网动态路由优化中的应用

本文介绍一种新的、启发式的、具有自组织能力的智能蚂蚁算法;并针对我国电信网的具体情况,提出借助这种智能蚂蚁算法,用分散控制的方式实现电信网动态路由优化的一种方案,目的是提高网络资源的利用率、网络运行的效率和可靠性。     

C程序设计课程的教学探索与实践

针对C程序设计课程的特点及其在软件专业课程体系中的地位和作用,提出了建立内存观点、以算法为中心、树立面向工程的思想、发挥其前导作用等教学思路。     

RLS算法在DPSK解调实验中的应用

在DPSK解调实验中,文章通过使用MC1496相乘器的同步解调电路进行分析和测试,同时对采用RLS自适应算法的解调电路进行分析和计算机模拟仿真,结果表明采用RLS自适应算法的解调电路性能优越、波形清晰。希望此方法对以后DPSK解调实验的改进具有参考作用。     

RLS channel estimation with adaptive forgetting factor in space-time coded MIMO-OFDM systems

INTRODUCTION The very dramatic increase in demand for high-rate data transmission stimulated greater re- search efforts in developing wideband wireless communication systems which could support high- rate transmission over wireless channels. But we have to face the challenges from the multi-path effects because multi-path propagation of wire wave is usu- ally seen as a harmful factor which leads to one of the most troublesome radio channel problems. However, the multi-path effects can beco…     

谈程序设计及算法优化

文章就如何学习计算机语言、处理语言中基本知识和程序设计方法、技法的关系,以及通过实例阐明如何进行算法的优化进行了论述.     

一种改进实数编码遗传算法及其应用

将混沌现象和邻域细化搜索策略应用于实数编码遗传算法(RCGA)中,提出了一种改进的RCGA。并将该算法应用于连续函数优化求解。与其他方法相比,表明该算法可靠且算法效率更高。     

Prediction of malignancy selective neural networks degree in brain glioma using ensemble

A clustering algorithm based selective neural networks ensemble （CLUSEN） is proposed to predict the degree of malignancy in brain glioma. Since the degree prediction of malignancy is critical before brain surgery, many learning methods are used like rule induction algorithm, single neural networks, support vector machines, etc. Ensemble learning methods can improve the generalization of single learning machine, and are becoming popular in the machine learning and medical data processing communities. The procedure of CLUSEN can efficiently remove redundancy learning individuals and help improve the diversity of ensemble methods. CLUSEN is used to predict the degree of malignancy in brain glioma. Experimental results on a set of brain glioma data show that, compared to support vector machines, rule induction and single neural networks, the classification accuracy of CLUSEN is higher.     

Optimization of a Reduced Chemical Kinetic Model for HCCI Engine Simulations by Micro-Genetic Algorithm

A reduced chemical kinetic model （44 species and 72 reactions） for the homogeneous charge compression ignition （HCCI） combustion of n-heptane was optimized to improve its autoignition predictions under different engine operating conditions. The seven kinetic parameters of the optimized model were determined by using the combination of a micro-genetic algorithm optimization methodology and the SENKIN program of CHEMKIN chemical kinetics software package. The optimization was performed within the range of equivalence ratios 0.2-1.2, initial temperature 310- 375 K and initial pressure 0, 1-0.3 MPa, The engine simulations show that the optimized model agrees better with the detailed chemical kinetic model （544 species and 2 446 reactions） than the original model does.     

基于改进遗传算法的优化研究

遗传算法本身固有的并行处理性和开放性,使得它在优化识别方面的效率非常之高,而且受到越来越广泛的研究,然而,遗传算法自身也有一些缺点．遗传算法在寻优过程中易出现“早熟”,设计变量增多时效率较低以及结构分析时间长．论文分析了遗传算法的常见缺陷,并通过采用小生境技术、基于多父体变量级别的杂交以及小生境技术的改进策略,遗传算法的优化性能（优化效率和质量）得到了大大的提高。     

基于模糊算法的电锅炉温度控制器的设计

针对直热式热水电锅炉的温控特点,以PIC16F877A单片机为核心,采用模糊控制算法,设计了一种模糊控制器,并运用MATLAB软件的simulink仿真环境对温度控制系统性能和抗干扰能力进行仿真分析。结果表明,该控制器能达到稳定性好、调节时间短且超调量小的预期指标。