资源列表
MPPTTTTT
- 基于PIC16F877单片机的PICC语言编写的MPPT程序-it s a code of mppt
Artificial-Intelligence
- 《人工智能哲学》收集了人工智能研究领域著名学者的15篇代表性论文，这些论文为计算机科学的发展和人工智能哲学的建立做出了开创性的贡献。人工智能哲学是伴随现代信息理论和计算机技术发展起来的一个哲学分支。-" Artificial Intelligence philosophy" a collection of 15 papers representative of artificial intelligence research famous scholars, these pap
genetic
- 对于未知非线性函数，利用非线性拟合能力和遗传算法的非线性寻优能力寻找函数极值。-For unknown nonlinear function, non-linear optimization capability by nonlinear fitting ability and genetic algorithm to find the extreme value functions.
Astar
- 用于智能机器人的路径规划，A*算法，可以借鉴-path finding
palate_recognition
- 对于车牌识别方面的问题进行了自己的分析以及车牌角度矫正等细节问题进行了优化以及修正-For the license plate recognition aspects of the problem of their own analysis and license plate angle correction and other details of the problem was optimized and amended
BP_NN
- 针对变压器故障诊断，在MATLAB环境下采用BP神经网络对故障类型进行分析。-Fault Diagnosis of Transformer
GA_Flow-Shop
- 流水线型车间作业调度问题可以描述如下：n个任务在流水线上进行m个阶段的加工，每一阶段至少有一台机器且至少有一个阶段存在多台机器，并且同一阶段上各机器的处理性能相同，在每一阶段各任务均要完成一道工序，各任务的每道工序可以在相应阶段上的任意一台机器上加工-Pipelined job shop scheduling problem can be described as follows: n tasks for the m-th stage processing on the assembly lin
Genetic-Algorithms
- 遗传算法的程序，其中包含编码，选择，变异，交叉，等遗传算子的实现，从而解决数学问题。- 遗传算法的程序，其中包含编码，选择，变异，交叉，等遗传算子的实现，从而解决数学问题。 Genetic algorithm program, which contains coding, selection, mutation, crossover, and other genetic operators to achieve, so as to solve mathematical problems.
fusion-tritraining
- 多源决策融合semi-supervised-multi classification learning machine for decision fusion in semi-supervised learning
Speed-control-based-on-fuzzy-control
- 基于模糊控制的速度控制，地面智能移动车辆速度控制系统，文档中有相关matlab实现代码以及C代码-Speed control based on fuzzy control, intelligent mobile vehicle speed control system on the ground, in the document with related matlab code and C code
Deep-Learning-Tutorial
- 深度学习最入门的文档，一天可以搞懂，李宏毅著-Depth learning the most entry-level documents, one day can get to know, Li Hongyi with
codes
- 手写数码（0到9）识别的神经网络框架。附有数据训练集和测试集。采用随机梯度下降的BP算法。可以修改参数，加入drop out和动量法。-Digital handwriting (0 to 9) of the neural network recognition framework. With training and test data sets. BP algorithm using stochastic gradient descent. Parameters can be modified