资源列表
5
- 基于名义的机器人滑模控制 采用滑膜控制 可以很好地克服外界干扰 对控制的实时性和稳定性有提高-Based on the name of the robot is controlled by sliding synovial control may well overcome external interference and stability of the real-time control has been improved
pso-bp.tar
- 基于粒子群算法优化BP神经网络参数的matlab程序，极大地提高了预测精度。-Based on particle swarm optimization BP neural network parameters matlab program, which greatly improved the prediction accuracy.
MKSVM
- 模糊支持向量机的代码程序,代码包含了多分类的分类器-The Fuzzy SVM
bp-for-license-recognition
- 利用BP神经网络算法进行车牌图像识别的代码，进行数字、车牌字符的识别，另附相应学习图片素材（二值化）及训练后网络-Using BP neural network algorithm for vehicle license plate image recognition code, the number of characters, license plate recognition, with the corresponding learning picture material and tra
logisticNewton
- logistic回归实现，优化方法为牛顿法，代码中未上传数据，- logistic newton
ZHINENGSHUIDI
- 首次利用智能水滴算法的基本原理，设计了求解VRPTW问题的快速有效算法，-Based on the principles of the intelligent water drops, a fast and efficient intelligent water drops (IWD) algorithm for solving the VRPTW is designed.
Standard-LSA
- 一种新的智能优化算法：闪电算法，用无约束优化测试函数进行验证，效果不错，值得推广，该算法的文献已被SCI检索，百度学术也可搜索到-A new intelligent optimization algorithms: Lightning algorithm, using unconstrained optimization test function to verify, the effect is good, worthy of promotion, the literature of the
GRNN
- 本案例是采用GRNN（径向基）神经网络预测水资源量，GRNN神经网络适合于小样本、高精度预测，本实例附有数据（不全），下载者可以直接将数据更改为自己的数据便可以使用。程序中使用了交叉验证方法，使预测精度大大提高-This case is the use of GRNN (Radial Basis Function) neural network to predict the amount of water, GRNN neural networks suitable for small samp
WindowsFormsApplication1
- 二代证读卡器和指纹识别示例代码，快速运行SDK的Demo演示程序。您必须拥有一个亚略特的指纹采集设备。-Second generation ID card reader and fingerprint sample code, run fast the SDK Demo demo program. You must have a sub Elliott fingerprint capture device.
MLP
- A multilayer perceptron (MLP) is a feedforward artificial neural network model that maps sets of input data onto a set of appropriate outputs. An MLP consists of multiple layers of nodes in a directed graph, with each layer fully connected to the nex
HMM-python-master
- 用python实现了隐马尔科夫模型的概率计算和预测部分，主要是前向后向算法和维特比算法-Realized with python hidden Markov model probability calculation and prediction part is mainly forward-backward algorithm and the Viterbi algorithm
Segmentation_Astar
- 这是一个基于A*算法的路径规划程序，利用栅格法构建了房间地图，然后通过A*算法规划出一条从出发点到目标点的最短路径。-This is based on A* algorithm path planning process, build the room use map grid method, and then through the A* algorithm plan a starting point the shortest path to the target point.