资源列表
Myth-speed-browser
- 神话极速浏览器,Myth speed browser -Myth speed browser
Labview_SAPI_TTS_Library
- 语音播报输入的文本内容，可以用于报警提示，朗读信息等方面。-Voice broadcast input text content, can be used for alarm prompts, reading information and so on.
PSO
- In computer science, particle swarm optimization (PSO) is a computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. It solves a problem by having a population of c
ypea104-acor
- continuous ACO. In computer science and operations research, the ant colony optimization algorithm (ACO) is a probabilistic technique for solving computational problems which can be reduced to finding good paths through graphs. This algorithm
sa
- Simulated annealing (SA) is a probabilistic technique for approximating the global optimum of a given function. Specifically, it is a metaheuristic to approximate global optimization in a large search space. It is often used when the search space is
myMatlab-code
- In computer science and operations research, the ant colony optimization algorithm (ACO) is a probabilistic technique for solving computational problems which can be reduced to finding good paths through graphs. This algorithm is a member of the
gaSVMcgForClass
- svm 的参数优化，利用ga(遗传优化算法)选择最优参数c g，最终提高训练集的分类准确率，更好的提高分类器性能,这是ga的功能函数源码-Svm parameter optimization, the use of ga (genetic optimization algorithm) to the optimal parameter c g, and ultimately improve the training set classification accuracy, better imp
chapter15_GA
- svm 的参数优化，利用ga(遗传优化算法)选择最优参数c g，最终提高训练集的分类准确率，更好的提高分类器性能-Svm parameter optimization, the use of ga (genetic optimization algorithm) to the optimal parameter c g, and ultimately improve the accuracy of the training set classification, better improve
chapter15_PSO
- svm 的参数优化，利用pso(粒子群优化算法)选择最优参数c g，最终提高训练集的分类准确率，更好的提高分类器性能-Svm parameter optimization, the use of pso (particle swarm optimization algorithm) to the optimal parameter c g, and ultimately improve the training set classification accuracy, better impr
chapter15_0
- svm 的参数优化，利用交叉验证法选择最优参数c g，最终提高训练集的分类准确率,更好的提高分类器性能-Svm parameter optimization, the use of cross-validation method to the optimal parameter c g, and ultimately improve the training set classification accuracy，better improve the classifier performan
chapter14
- 基于svm的数据分类预测，数据集是意大利葡萄酒种类的数据集，对葡萄酒进行种类识别以及分类。-Based on the svm data classification prediction, the data set is the Italian wine category data set, the wine species identification and classification.
mm
- 共享内存实验代码，该实验要求利用共享内存实现文件的打开和读写操作，基于linux平台。-Shared memory experimental code, the experiment requires the use of shared memory to achieve file opening and reading and writing operations, based on the Linux platform.