资源列表
NEAT-Sweepers
- 具有遗传功能的自组织结构神经网络扫雷机器人源程序-With the genetic function of the organizational structure of neural network demining robot source
TSP
- 使用遗传算法进行求解路线最短路径问题的VC++6.0源程序-Using a genetic algorithm to solve the line shortest path problem VC++6.0 source
GA-Lunar-Lander---Unmanned
- 使用遗传算法实现飞船着陆摩拟，采用VC++6.0开发的源程序-Using a genetic algorithm to achieve spacecraft landing Mount intends, VC++6.0 developed source
QEAsolvePath
- 用量子进化算法解决路径规划问题,程序非常容易看懂.对理解量子进化算法很有好处.-Quantum evolutionary algorithm to solve the problem of path planning, the program is very easy to understand. Very good understanding of the quantum evolutionary algorithm.
quamultiobjection
- 量子多目标进化算法代码 .用量子旋转门更新量子染色体种群-Quantum multi-objective evolutionary algorithm code. Quantum rotation gate updates the quantum chromosome population
lssvmpso
- 简单的遗传算法用于优化使用PSO算法的参数。 -SIMPLE GENETICAL GORITHM To optimize parameters by using the PSO algorithm.
Real-CodedQuantum
- 实数编码的单目标量子进化算法，介绍了如何用实数对染色体进行编码-A New Real-Coded Quantum Evolutionary Algorithm，How to use the real number is encoded on chromosome
GH0ST
- ghost远控是开源的远控，功能在其他远控中都十分出色。-Ghost remote control is an open source remote control, function in other remote control is very good.
HumanDet
- 公交车系统模式识别，能够自动识别人头部位，统计某个座位的人数。-The bus system, pattern recognition, can automatically identify the poll site, and statistics of the number of a seat.
Kalman_matlab
- 卡尔曼滤波方法用于估计物体运动参数，卡尔曼滤波在运动目标跟踪问题中。超级推荐，绝对可以运行，随机模拟运动估计，效果非常不错，是个老外写的。-Kalman filtering method used to estimate the object motion parameters, the Kalman filter in moving object tracking problem. Super recommended, can definitely run, the stochastic si
procalltest
- 基于matlab的语言情感识别仿真，可以实现用户注册，识别使用者说话时的喜怒哀乐等情感，人数少时可以实现很高的准确率。-Emotion Recognition based on Matlab language simulation, you can implement user registration, the number of emotions such as feelings, identify the user to speak came from a high accuracy ca
VFSA
- 求模拟退火算法解旅行商问题,求解最优路径，为用户计算得到最经济的路线，一遍做决策。-Solving Traveling Salesman Problem seeking the simulated annealing algorithm for solving the optimal path, calculate the most economic route for the user, again to make decisions.