资源列表
APyramid
- 基于VC++的图像匹配的金字塔算法。输入原始的512*512灰度图像，同时输入模板图像，分别输出图像和模板图像的三层金字塔图像，用来分层匹配；对输入图像利用小波变换分层，并形成三层金字塔，然后对模板图像做同样的处理，然后从顶至下以此对原始图像和模板图像进行匹配，匹配采用简单的对应像素的绝对误差累计来表示。提供测试模式集及其测试结果。-Based on VC++ pyramid algorithm for image matching. Enter the original 512* 512 gr
flowercloud
- 基于人工智能中的云模型，运用正态云发生器的正向生成和逆向生成，完成花卉信息的提取和重构-Based on artificial intelligence in the cloud model, using normal cloud generator generates the positive and reverse generation, complete flowers information extraction and reconfiguration
improveBPNet
- 改进的BP算法实现程序，以共轭梯度法实现BP神经网络。测试数据以txt格式给出。-Improved BP algorithm procedures in order to conjugate gradient method to achieve BP neural network. Test data given in txt format.
RBFNeuralNetwork
- RBF神经网络优化的粒子群优化的预测文献,可以-RBF Neural Network Optimized by Particle Swarm Optimization for Forecasting
paes
- 一个非常好用的多目标进化算法，可以轻松的达到PARETO前端-MOEA
BP
- 人工神经网络的C语言实现，程序涉及梯度下降法，函数求逆及偏导数的实现-Artificial Neural Networks C-language implementation, the program involves gradient descent method, function inverse and the partial derivative of the realization of
TSP_hopfield
- 通过hopfield神经网络解决TSP商务旅行商问题，找出一条最短路径！-By hopfield neural networks to solve traveling salesman problem TSP business, find a shortest path!
ISODATA
- 本例为等度规映射的C++算法实现，包含了使用方法。-In this case ISOMAP of C++ algorithm includes the use of methods.
PathPlanningforMobileRobotBased0nBPNeuralNetworkAl
- 这是一篇介绍BP神经网络在移动机器人路径规划方面的论文-Abstract：Improves the BP neural network algorithm，so the shortage of path —planning with the ． BP neural network algorithm is overcomed ．The simulation results indicate that on the bases of accessional momentum met
PathPlanningforMobileRobotsBasedontheNeuralNetwork
- ：针对移动机器人传统路径规划算法效率不高，寻优能力差等问题，提出一种基 于神经网络和粒子群优化算法相结合的移动机器人路径规划方法．该方法利用神经网 络实现大量的并行和分布计算，发挥PSO简单、容易实现的优点，提高了路径规划的计 算效率和可靠性．仿真结果表明，这种新路径规划方法是可行且有效的．-The quality and eficiency of calculation is the two puzzling problems in the tradi— tional algo
AIA2
- 人工免疫克隆选择算法是一种比较新型的智能算法，其基本算法结构与遗传算法是类似的，以下源码是为网络节点分组调度问题而设计的算法。-Artificial immune clonal selection algorithm is a relatively new type of intelligent algorithms, the basic algorithm structure and the genetic algorithm is similar to, the following sour
BMDCP
- 突变分为如下主要的几种：均值突变（最常见）、方差突变、线性回归突变（也称趋势突变）、概率突变、空间型突变、谱突变、模型参数突变，等等。贝叶斯突变检测属于概率突变检测方法，其特点是能给出突变点的概率分布图。-Mutations are divided into the following main categories: the mean mutation (the most common), variance mutation, linear regression mutation (also