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很好的遗传算法值得一看
很好的遗传算法值得一看-well worth looking at the genetic algorithm
- 2022-03-16 23:47:41下载
- 积分：1
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On the Particle Swarm Optimization Algorithm. Using java language.
关于粒子群优化算法的实现.使用java语言实现。-On the Particle Swarm Optimization Algorithm. Using java language.
- 2022-07-08 23:50:45下载
- 积分：1
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c语言版基本粒子群算法源程序
c语言版基本粒子群算法源程序-c-language version of elementary particles algorithm source code
- 2023-03-23 06:55:03下载
- 积分：1
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生产线上的上车数量注册软件的部分源代码，用于注册杭车数量，以便进行自动控制...
生产线上的上车数量注册软件的部分源代码，用于注册杭车数量，以便进行自动控制-The production line picking up the number of registered software, part of the source code used to register Hang cars for automatic control
- 2022-02-02 00:22:08下载
- 积分：1
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This is a use of MATLAB to use a simple classification of the PCA implementation...
这是一个利用MATLAB利用PCA实现的简单分类程序，对于模式识别的初学者学习PCA知识并进行仿真会有很大帮助，其中male.txt和female.txt是训练样本，test.txt是测试样本，分类效果非常好。-This is a use of MATLAB to use a simple classification of the PCA implementation process, the PCA pattern recognition study for beginners and simulation of knowledge would be of considerable help, and one of male.txt samples female.txt training, test.txt is the measurement, very good classification results.
- 2022-07-18 08:33:05下载
- 积分：1
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- 2022-02-24 09:13:40下载
- 积分：1
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支持向量机(3)svm_light
支持向量机(3)svm_light-Support Vector Machines(3):svm_light
- 2023-05-31 01:00:03下载
- 积分：1
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Source code of DBSCAN algorathm of data mining with VC
数据挖掘中dbscan算法的vc实现的源代码-Source code of DBSCAN algorathm of data mining with VC
- 2022-05-07 09:36:39下载
- 积分：1
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A genetic algorithm using maltab gentitc toolbox ,abundant in content.Whats s m...
maltab 的一个遗传算法的例子,比较全,有教你怎么初始化初始种群,设定参数,还有demo提供学习-A genetic algorithm using maltab gentitc toolbox ,abundant in content.Whats s more, you are teached how to initialize the initial population, set parameters. It also provide learning demos.
- 2023-07-12 06:10:03下载
- 积分：1
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使用二进制和实数编码变量的遗传算法实现。混合变量…
This a GA implementation using binary and real coded variables. Mixed variables can be used. Constraints can also be handled. All constraints must be greater-than-equal-to type (g >= 0) and normalized (see the sample problem in prob1 in objective()).-This a GA implementation using binary and real coded variables. Mixed variables can be used. Constraints can also be handled. All constraints must be greater-than-equal-to type (g gt;= 0) and normalized (see the sample problem in prob1 in objective()).
- 2022-02-07 16:02:59下载
- 积分：1
