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[AI-NN-PRbpso

Description: 用C#编写的基本微粒群算法的源程序代码,非常使用方便!-C# prepared in basic particle swarm algorithm source code is very easy to use!
Platform: | Size: 325632 | Author: 阿科 | Hits:

[AI-NN-PRBPSO

Description: 一个BPSO实现,基本上实现了BPSO的代码-BPSO achieve a basically achieved BPSO code
Platform: | Size: 5120 | Author: | Hits:

[AI-NN-PRPSO

Description: 许多的PSO优化算法,包括BPSO、HybridPSO、QPSO、SPSO等等。-Many of the PSO optimization algorithms, including BPSO, HybridPSO QPSO, SPSO, etc.
Platform: | Size: 14336 | Author: | Hits:

[matlabbpso

Description: 标准粒子群算法,应用matlab进行编程,执行文件为当中的main.m这个M文件-Standard Particle Swarm Opimization Algorithm
Platform: | Size: 660480 | Author: 徐言华 | Hits:

[Education soft systemBPSO

Description: 粒子群优化算法,是一种连续空间的优化的算法-Particle swarm optimization is an optimization algorithm for continuous space
Platform: | Size: 4096 | Author: wangjianyu | Hits:

[matlabbpso

Description: the program is for a function (x-15)^2+(x-20)^2
Platform: | Size: 9216 | Author: bhavana | Hits:

[matlabBPSO

Description: 粒子群算法源程序,matlab编程实现,欢迎互相学习-partical swarm optiamtion
Platform: | Size: 4096 | Author: 杨春生 | Hits:

[3D GraphicBPSO

Description: BPSO 二进制粒子群优化算法matlab源代码实现 -Binary particle swarm optimization algorithm
Platform: | Size: 2048 | Author: 范明阳 | Hits:

[Otherrule-mining-by-BPSO

Description: 本文提出来一种基于关联规则挖掘的二进制粒子群优化算法(BPSO),该算法与apriori算法不同,在从交易数据集中提取关联规则的过程中不需要给定支持度与置信度的阈值。-In this paper, we developed a binary particle swarm optimization (BPSO) based association rule miner. Our BPSO based association rule miner generates the association rules from the transactional database by formulating a combinatorial global optimization problem, without specifying the minimum support and minimum confi dence unlike the a priori algorithm.
Platform: | Size: 211968 | Author: xiaowei | Hits:

[CSharpBPSO

Description: 此為找尋系統最佳化方法,粒子群優BPSO之模型,只需要改一下目標函示即可執行囉-This system is the best method to find the model BPSO, the only change what the objective function is shown to perform Hello !!
Platform: | Size: 1024 | Author: 張騰文 | Hits:

[Data structsQuantum-Inspired-BPSO

Description: 此為應用MATHCAD來編寫BPSO,為粒子群優演算法,可應用於求解最佳化過程,可跑小系統之模擬,簡單又好用-This is the application to write MATHCAD BPSO, particle swarm optimization algorithm can be applied to solve the optimization process, the simulation can run a small system, simple and easy to use
Platform: | Size: 18432 | Author: 張騰文 | Hits:

[matlabEnhanced-Binary-Particle-Swarm-Optimization-(BPSO

Description: Enhanced Binary Particle Swarm Optimization (BPSO) with 6 new transfer functions
Platform: | Size: 101376 | Author: tigerman | Hits:

[matlabBPSO

Description: BPSO algorithm for solution power system with binary particle swarm optimization source code. Usually This program compare by another algorithm methods to result
Platform: | Size: 88064 | Author: sabhan | Hits:

[matlabAdaptive-BPSO-for-FS-MATLAB

Description: Adaptive BPSO for FS-MATLAB
Platform: | Size: 1341440 | Author: wangqing | Hits:

[Software EngineeringBPSO

Description: BPSO algorithm(matlab code)
Platform: | Size: 2048 | Author: nimasaberi | Hits:

[matlabBPSO

Description: matlab tool box for BPSO
Platform: | Size: 2048 | Author: FOFO | Hits:

[matlabBPSO - 副本

Description: 简单的BPSO的程序,粒子群算法源程序,matlab编程实现,欢迎互相学习(this program is the particle swarm algorithm source program,welcome to learn from each other.)
Platform: | Size: 2048 | Author: qmgqrb | Hits:

[Otherbpso-master

Description: 离散的粒子群算法 是用 python写, 输入都是0和1(The discrete particle swarm optimization is written in Python, and the input is 0 and 1.)
Platform: | Size: 10240 | Author: edwina414 | Hits:

[OtherBPSO for feature selection

Description: 二进制粒子群算法(Binary particle swarm optimization algorithm,BPSO)解决特征选择问题。(Binary particle swarm optimization algorithm for feature selection problem)
Platform: | Size: 3072 | Author: 禾兮 | Hits:

[matlabBPSO

Description: 二元粒子群优化(BPSO)用于特征选择任务,可以选择潜在特征,提高分类精度。(binary particle swarm optimization (BPSO) for feature selection tasks, which can select the potential features to improve the classification accuracy.)
Platform: | Size: 61440 | Author: 皮张 | Hits:
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