搜索资源列表
AGeneticAlgorithm-BasedClusteringApproachforatabas
- (程序)用c++编写的一个遗传算法C++类.zip-(Program) written in c++ using a genetic algorithm for C++ classes. Zip
neuralnetwork
- 用VC++ 写的一个BP神经网络算法的类，使用比较简单-VC++ to write with a BP neural network algorithm classes, the use of relatively simple
project3
- 使用BP神经网络来识别彩色图像的类. 自己取采样样本-apply the backpropagation neural network to classify a color image you choose. You need to determine the number of classes and select the training samples by yourself.
Kmeans
- 基于数据挖掘的k-means算法，成功实现簇类更新-Based on Data Mining k-means algorithm, cluster classes successfully updated
fd(1)
- 图像形态学功能应用代码实现，包括基本的膨胀，腐蚀，开运算，关运算，及其组合实现-not only demonstrates the basics of using the Microsoft Foundation classes but is also a starting point for writing your application.
Genetic-Algorithm-CPP-class
- 遗传算法的一个C++类，可以在该类内定义遗传算法个操作算子和数据-A genetic algorithm C++ classes
321
- The objective of this thesis is to investigate the inverse kinematics of the robots which were either built in our laboratory or used in our classes. The problem of inverse kinematics is to find the coordinates of the joint variables correspond
MobileRobots
- pioneer3机器人的编程指导资料，涉及到Aria以及Player库的使用，来龙去脉都讲解得比较详细。-This book is intended as a comprehensive guide to object-oriented C++ programming and control of the Pioneer class of robots made by MobileRobots Inc. It covers both the native API (ARIA, suppl
CLIPS_6.30_Beta.R3
- clips最新版 CLIPS是一种专家系统工具，最初由NASA/Lyndon B. Johnson太空中心软件技术研究室开发出来。自1986年首次发布以来，CLIPS经历了不断的改进和完善。现在它已经被广泛的应用在数以万计的全球用户中。 CLIPS被开发出来以促进集成人类知识和经验的软件发展。 在CLIPS中，知识的表示有三种方式： l 规则，规则表示法是基于启发式经验知识库的首要选择。 l 自定义函数和通用函数，这种方式是程序式知识表示的首选。 l 面向对象设计，也
datamine
- 关于数据挖掘的算法，超市数据挖掘，用于生成决策树和关联规则的程序，附有课设文档-About data mining algorithms, supermarket data mining, decision tree and association rules for building the program, with classes set document
ga2
- 遗传算法，一个简单的库提供基本的算法语言，有很多改进和附加-ga2 is a simple C++ library providing the necessary base classes to implement a genetic algorithm in C++. It is based loosely on Goldberg' s canonical GA, but with many modifications, improvements and additional featu
k-iris
- 模式识别中用于完成数据的分类而用到的一种方法-k近邻。是将已有数据划分到3个类中，本方法中解决数据Iris数据的划分问题。将150个4维数据划分到3类。K近邻法是求最近的K个元素从而将其划分到已有类中。-Pattern recognition for the completion of the classification of the data used in a way-k neighbors. The existing data are divided into three classes
LS_AStarUniversal
- 自己研发的A*算法类，并且利用机器人走迷宫的形式验证了算法的可行性，并且返回了基于像素点的所走路径长度。-A* algorithm developed their own classes, and the use of robots to verify the feasibility of the maze in the form of the algorithm, and returns the pixel-based point of the walking path length.
coevolutionary-algorithm
- 协同进化算法[I5] (Co-Evolutionary Algorithm, CEA)是研究者在协同进化理论基础 上提出的一类新算法。这类算法强调了种群与环境之间、种群与种群之间在不断进化过 程中的协调。与传统进化算法相比较,CEA可以对待求问题解空间进行合理的种群划分, 对较大规模的问题求解能有效跳出局部最优点,寻找到更好的优化解虽然CEA研 究起步较晚,但由于它的优越性,目前己成为当前进化计算的一个研究热点。 -Existing coevoluti
zuoye
- k均值进行聚类分析，把二维模式矢量分成三、四类，用SOFM算法-K-means clustering analysis, the two-dimensional pattern vector is divided into three or four classes, using SOFM algorithm
libORF-master
- 针对各种机器学习，深度学习领域的一个matlab工具包-A machine learning library focused on deep learning.Following algorithms and models are provided along with some static utility classes: - Naive Bayes, Linear Regression, Logistic Regression, Softmax Regression, Linear S
activity-recognition-based-on-DRNN
- 基于多层神经网络的人类活动识别，智能家居领域的一项重大突破。-Activity recognition has received increasing attention from the machine learning community. Of particular interest is the ability to recognize activities in real time streaming data, but this presents a number of
SvmOneVersusOne
- 支持向量机SVM可以使用多分类的问题，本次的代码实现的就是这个功能，里面含有训练和测试数据，分别含有12类标签，也就是都分为12类，另外代码采用了神经网络中的one-versus-one的思想，将数据分类K（K-1）/2个子类，分别调用SVM方法实现-It is about the classification in use of SVM for 12 classes. The algorithm contains training data and test data.
0-svnn
- 这段代码实现了一个新的MLP神经网络训练方法,来自论文A new method for neural network regularization（内附）-This code implements a new training method for MLP neural networks, named Support Vector Neural Network (SVNN), proposed in the work: O. Ludwig “Study on Non-parametric Me
Softmax
- 一个小demo,用softmax实现数据分类，数据有4类，均服从高斯分布-A small demo, a classifier with softmax softmax is implemented to classify 4 classes of datas which are generated by gaussian distribution