资源列表
8_puzzle
- 8数码问题,包含代码,可执行文件,readme,运行截图-8 puzzle, including code, executable files, readme, run shot
dossier
- For the incomplete methods, we kept the representation of the queens by a table and the method of calculation to determine if two queens are in conflict, which is much faster for this kind of problems than the representation by a matrix. heuristics
BP_MY
- 神经网络模型算法,做了优化,可以自动识别数字- Neural Network algorithm, and is optimized, recognize character automatically
KNearestCls
- 模式识别中的K近邻法和快速K近邻法的VC++实现-Pattern Recognition and rapid K neighbors K neighbors law VC to achieve
winc3d
- 本程序是计算机视觉稠密匹配的程序,对两幅序列图像能够实现一个稠密视差图。-Computer Vision populated matching procedures, two image sequence to achieve a dense disparity map.
Puzzle
- 利用遗传算法编写的24数码程序,对学习遗传算法和图形界面编程非常有用-Using the genetic algorithm written in 24 digital programs, to learn of genetic algorithm and graphical interface programming is very useful
onlineldavb
- python写的online lda,LDA算法的实时实现,根据lda已经计算出来的主题,强化后面没计算出来的主题-Online lda,LDA algorithm for real-time implementation of Python written, based on the theme of the LDA has been computed, theme of strengthening the back does not come out
chapter3
- Matlab神经网络30个案例,第三章的源码-Matlab neural network of 30 cases, the third chapter of the source
对冲7.0.zip
- 对冲7.0(MT5版本)万元账户周盈利 50% 的底层逻辑 策略经实测 1 万元账户一周盈利 50%,核心是 “控风险、抓机会、稳收益” 的三层逻辑设计,具体优势如下: 一、交易规则:灵活捕捉行情 • 开启多空双向交易,涨跌行情都能参与,不浪费盈利机会。 • 首单优先 + 5 层订单布局,按固定间隔开仓,摊薄成本的同时避免风险集中。 • 不追趋势开单,减少高位套牢风险,适配震荡及缓涨缓跌行情。 二、手数管理:轻仓起步 + 复利递增 • 初始手数 0.01,轻仓启动,降低起步风险。
Genetic_algorithm_to_optimize_the_BP_neural_networ
- 根据遗传算法和BP神经网络理论,在MATLAB软件中编程实现基于遗传算法优化的BP神经网络非线性系统拟合算法。-Based on genetic algorithm and BP neural network, software, programming in MATLAB genetic algorithm based on BP neural network fitting algorithm of nonlinear systems.
Bionic-Pattern-Recognition
- 这是仿生模式识别和拓扑模式识别的一篇论文,提出了一种新的模式识别方法和应用的模型-this is a paper about Bionic (Topological) Pattern Recognition
chapt
- 基于RBF网络的动态面自适应控制,以飞行器航迹角自适应神经网络动态面为例进行了讲解。-Adaptive dynamic surface control based on RBF network, with the flight path angle neural network based adaptive dynamic surface as an example to explain.
