搜索资源列表
GA
- GA.dll是封装遗传算法的动态连接库,内部潮流计算使用的是PQ方法,该潮流计算方法已封装在该DLL内。如果需要采用其他的潮流计算方法,需要重新来设计DLL的接口函数及更改遗传算法中目标函数的计算方法。-GA.dll genetic algorithm is encapsulated dynamic link library, the internal flow calculation using the PQ method, the power flow calculation method
pid_chanshu
- 基于遗传算法的PID参数的PID参数整定,在matlab环境下的源程序.PID参数的整定有两种可用的方法,理论设计法及实验确定法.-Based on genetic algorithm of the PID parameters of PID parameter tuning in matlab source environment. PID tuning parameters, there are two available methods, theory and experimental d
Neural_Network_Design
- < 神经网络设计源代码>>一书的源代码。-err
AI_CrossRiver
- 人工智能课程 产生式部分的一个实验设计:用产生式解决“过河问题”-Production of artificial intelligence course as a part of experimental design: The production solve the " problem across the river"
fisher
- 基于Fisher准则线性分类器设计,理解Fisher准则方法确定最佳线性分界面方法的原理,以及Lagrande乘子求解的原理。-Based on Fisher linear classifier design guidelines, understanding the criteria Fisher method to determine the best linear method of the principle of the interface, as well as solving La
EightPuzzle
- 程序实现的是用A*算法求解八数码问题,初始状态和目标状态均可在源码中自行设置,程序运行后会得到从初始状态到目标状态的最佳解的逆序显示,文件help.txt中提供了程序的算法,程序的具体设计在源码中都有相应的注释-Program implementation is to use A* algorithm to solve 8 digital issues, the initial state and target state can be set up in the source code of
SA_GA
- 基于遗传模拟退火算法的聚类算法。将模拟退火算法与遗传算法相结合用于聚类分析,由于模拟退火算法和遗传算法可以互相取长补短,因此有效地克服了传统遗传算法的早熟现象,同时根据聚类问题的具体情况设计遗传编码方式、适应度函数,使该算法更有效、更快速地收敛到全局最优解。 -Genetic simulated annealing algorithm based on clustering algorithms. Simulated annealing algorithm and genetic algo
BP
- BP神经网络的整个训练过程(从数据剔除,平滑处理,归一化,到构建训练网络,反归一化,你拟合作图)毕设课题作业,保证可用-BP neural network the training process (removed from the data, smoothing, normalization, to build the training network, anti-normalization, you wish to cooperate diagram) subjects completed
code
- 此为数据挖掘课程大作业,主要功能是对已给定的描述生物分子三维结构的139351 个属性中,分类预测出该分子化合物对目标体的化学活性,从而达到帮助药物设计的目的。实验现有的数据包括:110个已标记活性标签的描述分子三维结构的139351维数据,634 个为标记活性标签的三维结构数据。希望根据这些提供的数据,采用适当的分类方法,提供出一个经过训练的分类器,能够尽可能准确的帮助未标记活性的分子化合物确定其活性。-This is a big job data mining courses, the ma
plast
- 该软件包采用MATLAB和C混合编程的方法实现了计算智能界新发现的, 也是国际最流行的神经元算法, 即Spike-Timing Dependent Plasticity. 本人完全独立设计及编制了该软件包,并经大量计算机模拟实验验证, 得到了权威专家的认可. 该软件包实现了复杂的STDP算法, 且全部参数可调. 本人使用此软件包进行的实验结果已经发表在IEEE Transactions on Neural Networks, Neurocomputing, IJNS等国际权威刊物上. 请放心使用
AI_Program
- 人工智能课程设计,包含一个刺激响应的人工蚂蚁小程序以及一个完整的遗传算法程序,有较为详细的设计说明文档以及可执行文件,需要学习人工蚂蚁及遗传算法的同学可以参考-Artificial intelligence program designed to stimulate the response that contains a small program of artificial ants, and a complete genetic algorithm process, there is a
eyelabel
- 该代码用于眼睛的人工标定,并记录数据只用,是MFC图形化界面设计。用于模式识别,人眼定位,人工智能方面做前期机器学习或训练。-The code used for the artificial eye calibration, and record data only is the graphical interface design MFC. For pattern recognition, the human eye positioning, pre-done in artificial in
protege_learning
- tutorials for learning protege(open source softwar to design the ontology)
BP-code
- 基于C语言编写的BP 神经网络程序 经过大量样本训练满足 设计要求!-C language based on BP neural network of a large number of samples after a training program to meet the design requirements!
C
- BP神经网络 学习 毕业设计用源代码 使用C编程,使用bp神经网络matlab工具箱-BP neural network learning graduate design program with source code using C, use of bp neural network toolbox matlab
ada
- 基于BP_Adaboost的强分类器设计-公司财务预警建模,基于神经网络的matlab参考代码。-Strong classifier based on BP_Adaboost design- the company' s financial early warning model, based on neural network matlab reference code.
solutions
- Computer Organization and Design 3e solutions 白算盘第三版习题解答-Computer Organization and Design 3e solutions white thinking to answer the third edition of Exercises
LPR-mobile
- 视频车辆牌照识别,包含汉字处理算法,BP神经网络设计。识别率高达90%以上。-Video vehicle license plate recognition, including the Chinese characters processing algorithms, BP neural network design. Recognition rate as high as 90 .
matlabdsf
- 神经网络的源程序基于MATLAB系统分析与设计--神经网络的源程序\EX3001.M-neural network based on MATLAB source of analysis and design-- neural network source \ EX 3001.M
Multi-stepPredictiveControl
- 多步预测,设计简单规范,基于信息建模,具有很强的抗干扰性和鲁棒性.-Multi-step prediction, the design of simple norms, based on information modeling, which has strong anti-jamming and robustness.