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adaboost_for_matlab
- AdaBoost, Adaptive Boosting, is a well-known meta machine learning algorithm that was proposed by Yoav Freund and Robert Schapire. In this project there two main files 1. ADABOOST_tr.m 2. ADABOOST_te.m to traing and test a user-coded learnin
DICOMDIR
- DICOMDIR Reader Matlab实现DICOMDIR读取 Matlab, Image Processing Toolbox 程序读取DICOMDIR文件，读取meta数据，生成三维矩阵。 相关知识 Reading DICOMDIR folder using the directory browser GUI: dcmSeries = loaddcmdir Generating 3D array by selecting a dico
Ada_Boost
- AdaBoost, short for Adaptive Boosting, is a machine learning algorithm, formulated by Yoav Freund and Robert Schapire. It is a meta-algorithm, and can be used in conjunction with many other learning algorithms to improve their performance.
adaboost1
- adaboost代码，比较简单。但方便了解Adaboost算法的基本原理-The aim of the project is to provide a source of the meta-learning algorithm known as AdaBoost to improve the performance of the user-defined classifiers.
GODLIKE
- GODLIKE is an abbreviation of Global Optimum Determination by Linking and Interchanging Kindred Evaluators. This algorithm is an attempt to gen- eralize and improve the robustness of the four meta-heuristic optimization al- gorithms GA, PSO, DE
RECONFG
- This paper presents a new method to solve the network reconfiguration problem in the presence of distributed generation (DG) with an objective of minimizing real power loss and improving voltage profile in distribution system. A meta heuristic
adaboost
- adaboost算法的训练和测试代码，简单的实例(The aim of the project is to provide a source of the meta-learning algorithm known as AdaBoost to improve the performance of the user-defined classifiers.)
2222
- 进化算法（如纯遗传算法）是元启发式算法。 这意味着，它们是一个通用框架和一组概念准则，可用于创建特定的算法以解决特定的问题。 因此，本文中介绍的示例可以看作是实验和创建进化优化代码的起点，而不是固定的静态代码库。(Evolutionary algorithms (such as pure genetic algorithms) are meta heuristic algorithms. This means that they are a generic framework and a set
109201289dg-placement
- This paper presents a new method to solve the network reconfiguration problem in the presence of distributed generation (DG) with an objective of minimizing real power loss and improving voltage profile in distribution system. A meta heuristic Harmon
系统建模
- 1.批量最小二乘法算法（也称最小二乘的一次性完成辨识算法） 2.递推最小二乘法算法，应用递推算法对参数估计值进行不断修正,以取得更为准确的参数估计值。 3.粒子群算法(PSO)。粒子群优化算法的基本思想：是通过群体中个体之间的协作和信息共享来寻找最优解．PSO的优点在于简单容易实现并且没有许多参数的调节。 4.BP神经网络，各个神经元仅接收来自前一级的输出，经神经元处理后的信息将输出至下一级，网络中没有反馈，即前一级神经元不会接受后一级神经元的输出。 water tank是原始数据（双容