资源列表
PSOTool
- 求解非线性方程组方法有经典算法以及近年来流行的遗传算法．牛顿法及其改进形式,但是此类算法的收敛性在很大程度上依赖于初始点的选择，对于某些非线性方程组容易导致求解失败 为了克服经典算法的缺点，设计了求解非线性方程组的混合遗传算法,但依然对方程组和编码方法有很高要求。PSO是受到鸟群或者鱼群社会行为的启发而形成的一种基于种群的随机优化技术。它是一类随机全局优化技术，通过粒子间的相互作用发现复杂搜索空间中的最优区域。该算法是一种基于群体智能的新型演化计算技术，具有简单易实现、设置参数少、全局优化能力强
SVM-MT
- 基于libSVM-v310的完全多线程化libSVM，仅读写文件在框架内无法优化。svm-predict不需要openmp支持，svm-train需要打开openmp支持。VS2008编译。修改MAX_THREAD可以调整svm-predict线程数。-A fully multi-thread optimized libSVM based on libsvm-3.10. svm-predict won t need openmp however svm-train requires. The p
Genetic-Algorithm
- 本例应用遗传算法实现了对于一些非线性、多模型、多目标的函数优化问题，用其它优化方法较难求解，而遗传算法可以方便的得到较好的结果。-In this case the genetic algorithm is applied to implement for some nonlinear, model, multi-objective function optimization problem, with other optimization methods are difficult to sol
BPNN-NIR
- 用于近红外/高光谱光谱分析的BP神经网络分析程序-BP NN for NIR/hyperspectral imaging .
test
- 以c++和opencv为工具，通过摄像头捕捉到肤色区域，并跟踪，实现手势识别-In c++ and opencv as a tool, through the camera to capture color region and tracking, gesture recognition
SHADE_CEC2013.tar
- SHADE implemented by C++ for Special Session & Competition on Real-Parameter Single Objective Optimization at CEC-2013
jieba
- jieba分词软件，是python下的开源分词软件，里面有使用例子，简单易用-jieba segmentation software, is under the open source python segmentation software, there are examples of the use, easy to use
NB
- 自己编写的朴素贝叶斯分类器，经实测效果不错，供文本分类的研究人员相互学习-I have written a naive Bayes classifier, measured results are good for text classification researchers learn from each other
PlantomGo
- 幻影围棋棋源代码，参加计算机博弈比大赛亚军的代码。-Phantom Go chess source code, to participate in a computer game than the runner-up code.
neuronal-network_bp
- 人工神经网络的bp算法，用java语言编程实现，可以做为参考。-Artificial neural network algorithm bp, using java programming language, can be used as reference.
Representation-learning
- 深度学习领域的一个分支，由日本人引领的机器学习潮流-A branch of the deep learning field, conducted by a japanese researcher
13Deep-Learning-Tutorial
- 适合机器视觉的深度学习入门讲义，深度学习是机器学习领域现在最热门的领域之一-The deep learning tutorial is suitable to machine vision, which is the most popular area in the machine learning area