资源列表
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.
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。
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
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
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
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.
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
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
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
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
CGraph类及示例工程
- 天体运动处理系统，实现天体图象的背景处理，运动判定分步。解压密码：123-celestial movement in dealing system that the background image objects, found step-by-step movement. Extracting Password : 123
knn_vb
- In pattern recognition, the k-nearest neighbor algorithm (k-NN) is a method for classifying objects based on closest training examples in the feature space. k-NN is a type of instance-based learning, or lazy learning where the function is only approx