Description: 计算坐标系中三个点的镜像对称距离_以某一点为基准.-calculated coordinates is three points away from the mirror symmetry _ to a certain point as the benchmark. Platform: |
Size: 1024 |
Author: |
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Description: 免疫遗传算法解决TSP问题的源程序，属于本人写文章测试benchmark problem用的程序。-Immune genetic algorithm to solve TSP problem source, which I write the test procedures used benchmark problem. Platform: |
Size: 4096 |
Author:朱京红 |
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Description: matlab中等值线图，显示等值线数值，多个子图设置相同标尺-matlab in isogram shows isopleth value, more than the same benchmark set subgraph Platform: |
Size: 29696 |
Author:songli |
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Description: 本人修改过的elm的matlab算法，该算法比原来的elm的算法在超过3个神经元后的计算速度能明显加快！原理是运用函数产生列矩阵！！
ELM 是一种快速的神经网络算法，本人已经比较过，比很多流行的算法（BP,SVM）都快,而且效果很好，运行环境是matlab，可以测试所有的benchmark的数据-I modified elm of matlab algorithm elm than the original algorithm in more than three neurons after the computing speed can significantly speed up! The principle is to use functions to generate the matrix out! ! ELM is a fast neural network algorithm, I have a comparison, than many popular algorithms (BP, SVM) faster, and the effect of good operating environment is matlab, you can test all of the benchmark data Platform: |
Size: 3072 |
Author:chenlei |
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Description: 本人编写的GramSchmidt神经网络算法，和传统的神经网络算法比较，该算法能自动产生神经元，节约时间，速度快！
本人还加了自动产生分类的方法和适合各种函数的转换，该zip包括两个文件，一个是GramSchmidt正交分解，是个子函数，主函数是orth_GramSchmidt，放在同一目录下，就可运行，可以对benchmark的逼近和分类问题提供解决方案-I prepared GramSchmidt neural network algorithm, and the traditional neural network algorithm, the algorithm can automatically generate neurons, saving time, fast! I also added a method of automatically generated classification and conversion for a variety of functions, the zip includes two documents, one is GramSchmidt orthogonal decomposition is a sub-function, the main function is orth_GramSchmidt, on the same directory, you can run can benchmark approximation and classification problems to provide solutions Platform: |
Size: 2048 |
Author:chenlei |
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Description: 基于生物免疫系统的自适应学习、免疫记忆、抗体多样性及动态平衡维持等功能,提出一种动态多目标免疫
优化算法处理动态多目标优化问题.算法设计中,依据自适应ζ邻域及抗体所处位置设计抗体的亲和力,基于Pa-
reto控制的概念,利用分层选择确定参与进化的抗体,经由克隆扩张及自适应高斯变异,提高群体的平均亲和力,利
用免疫记忆、动态维持和Average linkage聚类方法,设计环境识别规则和记忆池,借助3种不同类型的动态多目标
测试问题,通过与出众的动态环境优化算法比较,数值实验表明所提出算法解决复杂动态多目标优化问题具有较大
潜力.-:A dynamic multi-objective immune optimization algorithm suitable for dynamic multi-objective
optimization problems is proposed based on the functions of adaptive learning, immune memory, antibody
diversity and dynamic balance maintenance, etc. In the design of the algorithm, the scheme of antibody af-
finity was designed based on the locations of adaptive-neighborhood and antibody antibodies participating
in evolution were selected by Pareto dominance. In order to enhance the average affinity of the population,
clonal proliferation and adaptive Gaussian mutation were adopted to evolve excellent antibodies. Further-
more, the average linkage method and several functions of immune memory and dynamic balance mainte-
nance were used to design environmental recognition rules and the memory pool. The proposed algorithm
was compared against several popular multi-objective algorithms by means of three different kinds of dy-
namic multi-objective benchmark problems. Simulations show Platform: |
Size: 499712 |
Author:王飞 |
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Description: This code expains kalmanswarm optimization method.All files have been written on matlab 2007a. This method has been explianed with various benchmark functions. This optimization method can be directly compared with other unconstrained optimization method like GA or pso for effieciency and speed.
This method is much faster as compared to genetic algorithim. Platform: |
Size: 5120 |
Author:missed2010 |
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Description: This code expains bayesian particle swarm optimization method.All files have been written on matlab 2007a. This method has been explianed with various benchmark functions. This optimization method can be directly compared with other unconstrained optimization method like GA or pso for effieciency and speed.
Platform: |
Size: 4096 |
Author:missed2010 |
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Description: Constrained optimization has been explained with matlab 2007a. This has been explained with various benchmark functions. The main program can be directly applied to knapsack problem and portfolio optimization problem directly.
These programs have been written in a menu driven manner. Platform: |
Size: 5120 |
Author:missed2010 |
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Description: TEC_test.m and TEC_test_rot.m are the main functions.
TEC_test.m is for the unrotated problem and TEC_test_rot.m is for the rotated ones.
TEC_test_function.m includes the benchmark functions, and the data files are the corrsponding data for the benchmark functions. Platform: |
Size: 1217536 |
Author:zahid |
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Description: 鲸鱼优化算法，用matlab实现的，优化问题为基准测试函数。(Whale optimization algorithm, using MATLAB to achieve the optimization problem as the benchmark function.) Platform: |
Size: 3072 |
Author:fanchd
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Description: 用matlab求数学问题，如有关矩阵的相关问题(The algorithm was programmed in MATLAB, and tested with a benchmark problem.) Platform: |
Size: 26624 |
Author:LYNN1212
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Description: Matlab中智能算法最优化测试函数公式及代码，有30几个，可用来验证算法的性能(There are more than 30 intelligent algorithm optimization test function formulas and codes in Matlab, which can be used to verify the performance of the algorithm.) Platform: |
Size: 999424 |
Author:jayleebest |
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Search - benchmark matlab