资源列表
assoctiation
- 关联规则挖掘的一个小算法 是平时做的一个小作业 感觉功能比较全 值得参考- a agrithom of datamining
gabijiao
- 该程序通过实例（函数），比较了遗传算法，量子遗传算法和新遗传算法三种算法，表明了算法间的关系和差别以及算法的好坏。-The program by example (function), compared the genetic algorithm, quantum genetic algorithm and the new genetic algorithm for three kinds of algorithm, shows the relationship and differences
QGA
- 该算法明确描述了量子遗传算法的实现流程，通过运行，该程序是正确的。-The algorithm clearly describes the realization of the quantum genetic algorithm process, by running the program is correct.
weka-src
- weka 3.7源代码包 WEKA的全名是怀卡托智能分析环境(Waikato Environment for Knowledge Analysis)-weka 3.7 source code package WEKA full name is the intelligent analysis of the environment Waikato (Waikato Environment for Knowledge Analysis)
libsvm-weights-2.9
- 数据属性的权重分析. 用户可以给每个数据实例权重-Weights for data instances Users can give a weight to each data instance.
OO
- 序优化是解决基于仿真优化的重要工具，由著名学者YuChi Ho提出-Ordinal optimization is to solve an important tool for simulation-based optimization, presented by the famous scholar YuChi Ho
main
- 扫面线z buffer算法，读入obj文件，绘制一帧-Scan line z buffer algorithm for face, read into the obj file, draw a
implementationofCoevolutionaryalgorithm
- 利用帕累托最优和协同进化算法做一个模拟，可以应用在多目标优化上。-a simulation using pareto optimization and co-evolutionay algorithm, it could be used to solve multiple objective optimization.
financialwarningsystem
- 一个综合性模型，含有最大最小博弈模型，基因表达式编程模型，最终产生股票指数模拟结果-a comprehensive model together with minority game, majority game, genatic programing, and finally produce a simulated result of stock index.
minoritygameusedtomodelfinancialcontagion
- 市场博弈模型，用来模拟股票市场运行，最终产生股票指数的模拟结果-an market game model, used to simulated financial market operation, and produce a simulated result of stock index.
AI
- 人工智能导论与算法研究 章节： 1.导论 2.知识表示 3.逻辑推理 4.搜索原理 5.不确定推理-Fundation of Artificial Intelligence Structure: 1.Introduction 2.Knowledge Representation 3.Logic 4.Search 5.Uncertainty
bp
- 基于BP神经网络算法的函数逼近，利用matlab实现BP算法逼近任意非线性函数-BP neural network algorithm based on function approximation, using matlab to achieve BP algorithm approximate any nonlinear function