DSSZ
www.dssz.org
Search
Sign in
Create an account
Hot Search :
Source
embeded
web
remote control
p2p
game
More...
Location :
Home
Search - PSO-GA
Main Category
SourceCode
Documents
Books
WEB Code
Develop Tools
Other resource
Search - PSO-GA - List
【
matlab
】
MATLAB_ANN_30
DL : 0
30个例程,非常好用,带有bp,GA,PSO等多种常见算法和模型,别看小,保证是全的-30 routines, very easy to use, with bp, GA, PSO and other common algorithms and models, do not look small, guaranteed to be full of
Update
: 2024-05-03
Size
: 5805056
Publisher
:
jy
【
matlab
】
GODLIKE
DL : 0
GODLIKE is an abbreviation of Global Optimum Determination by Linking and Interchanging Kindred Evaluators. This algorithm is an attempt to gen- eralize and improve the robustness of the four meta-heuristic optimization al- gorithms GA, PSO, DE and ASA, and generalize the optimization process by being capable to solve both single-objective and multi-objective optimization problems.
Update
: 2024-05-03
Size
: 286720
Publisher
:
applepie12356
【
Other
】
tsp
DL : 0
SA、GA、PSO解决TSP问题的C++源代码-SA, GA, PSO to solve the TSP problem. C++
Update
: 2024-05-03
Size
: 9216
Publisher
:
demi
【
Other
】
06725452
DL : 0
This work investigates the practical application of support vector machine (SVM) to power transformer condition assessment. Partiuclarly, this paper proposes to integrate the SVM algorithm with two heuristic optimization algorithms which are particle swarm optimization algorithm (PSO) and genetic algorithm optimization (GA). These two optimization algorothms are used for efficiently and effectively determine the optimal parameters for SVM. The resulatant two hybrid algorithms, i.e. SVM-PSO and SVM-GA can improve the performances of the original SVM algorithm on classifying the incipient faults in power transformers. Extensive case studies and statistic comparison among the original SVM, SVM-PSO, and SVM-GA over multiple datasets are also provided. Calculation results may demonstrate the effectiveness and applicability of the two hybrid algorithms in improving the classification accuracy of SVM for condition assessment of power transformer.
Update
: 2024-05-03
Size
: 985088
Publisher
:
pse
【
Software Engineering
】
39378
DL : 0
This work investigates the practical application of support vector machine (SVM) to power transformer condition assessment. Partiuclarly, this paper proposes to integrate the SVM algorithm with two heuristic optimization algorithms which are particle swarm optimization algorithm (PSO) and genetic algorithm optimization (GA). These two optimization algorothms are used for efficiently and effectively determine the optimal parameters for SVM. The resulatant two hybrid algorithms, i.e. SVM-PSO and SVM-GA can improve the performances of the original SVM algorithm on classifying the incipient faults in power transformers. Extensive case studies and statistic comparison among the original SVM, SVM-PSO, and SVM-GA over multiple datasets are also provided. Calculation results may demonstrate the effectiveness and applic
Update
: 2024-05-03
Size
: 1890304
Publisher
:
pse
【
Software Engineering
】
Yang_nature_book_part
DL : 0
This work investigates the practical application of support vector machine (SVM) to power transformer condition assessment. Partiuclarly, this paper proposes to integrate the SVM algorithm with two heuristic optimization algorithms which are particle swarm optimization algorithm (PSO) and genetic algorithm optimization (GA). These two optimization algorothms are used for efficiently and effectively determine the optimal parameters for SVM. The resulatant two hybrid algorithms, i.e. SVM-PSO and SVM-GA can improve the performances of the original SVM algorithm on classifying the incipient faults in power transformers. Extensive case studies and statistic comparison among the original SVM, SVM-PSO, and SVM-GA over multiple datasets are also provided. Calculation results may demonstrate the effectiveness and applicability of the two hybrid algorit
Update
: 2024-05-03
Size
: 930816
Publisher
:
pse
【
Software Engineering
】
39326
DL : 0
This work investigates the practical application of support vector machine (SVM) to power transformer condition assessment. Partiuclarly, this paper proposes to integrate the SVM algorithm with two heuristic optimization algorithms which are particle swarm optimization algorithm (PSO) and genetic algorithm optimization (GA). These two optimization algorothms are used for efficiently and effectively determine the optimal parameters for SVM. The resulatant two hybrid algorithms, i.e. SVM-PSO and SVM-GA can improve the performances of the original SVM algorithm on classifying the incipient faults in power transformers. Extensive case studies and statistic comparison among the original SVM, SVM-PSO, and SVM-GA over multiple datasets are also provided. Calculation results may demonstrate the effectiveness and applicability of the two hybrid algorithms in improving the classification accuracy of SVM for condition
Update
: 2024-05-03
Size
: 670720
Publisher
:
pse
【
Software Engineering
】
GA-on-pso-
DL : 0
基于遗传算法的电力系统无功优化的C语言程序-Power system based on genetic algorithm optimization of reactive C language program
Update
: 2024-05-03
Size
: 12288
Publisher
:
wanghan
【
Algorithm
】
fpa_demo
DL : 0
Flower pollination is an intriguing process in the natural world. Its evolutionary characteristics can be used to design new optimization algorithms. In this paper, we propose a new algorithm, namely, flower pollination algorithm, inspired by the pollina- tion process of flowers. We first use ten test functions to validate the new algorithm, and compare its performance with genetic algorithms and particle swarm optimization. Our simulation results show the flower algorithm is more efficient than both GA and PSO. We also use the flower algorithm to solve a nonlinear design benchmark, which shows the convergence rate is almost exponential.
Update
: 2024-05-03
Size
: 3072
Publisher
:
John
【
Other
】
code
DL : 0
这是我自己编写的二进制频谱分配算法的代码,分别用粒子群算法和遗传算法实现.-spectrum allocation code for PSO and GA
Update
: 2024-05-03
Size
: 4096
Publisher
:
yehao
【
matlab
】
pandey-final
DL : 0
this code consists of both GA and pso based and comparison with aco for tsp-this code consists of both GA and pso based and comparison with aco for tsp......................
Update
: 2024-05-03
Size
: 61440
Publisher
:
pandey_ji
【
source in ebook
】
AII
DL : 0
matlab ga,pso,ant colony programs in pdf
Update
: 2024-05-03
Size
: 63488
Publisher
:
pandiyan
【
matlab
】
GAaPSO
DL : 0
MATLAB环境下,有关遗传算法以及粒子群算法的程序-the program of GA and PSO in matlab
Update
: 2024-05-03
Size
: 9216
Publisher
:
何和新
【
matlab
】
original
DL : 0
When doing optimization, GA algorithm was initially selected, but the instability of the GA (or local optimization) is really frustrating, before and after the resulting difference can at times reach more than 30 , at that time due to time reasons, I chose to optimize 1000 times, then the minimum value of the most optimal solution. Although the problems are solved, but an academic, this style of running is pretty embarrassing. So, I downloaded a GA-PSO algorithm, try using the combination of GA and PSO optimizing strategies, results algorithm issues, efficiency and good. I downloaded the original algorithm, there is a problem is that it is aimed at all upper and lower limits of the design variables are the same, so I modified the program and improvements, you can now deal with upper and lower limits of the inconsistency problem and fix the bug. Now, program modifications, and share, hoping to be useful to you-When doing optimization, GA algorithm was initially selected, but the instability of the GA (or local optimization) is really frustrating, before and after the resulting difference can at times reach more than 30 , at that time due to time reasons, I chose to optimize 1000 times, then the minimum value of the most optimal solution. Although the problems are solved, but an academic, this style of running is pretty embarrassing. So, I downloaded a GA-PSO algorithm, try using the combination of GA and PSO optimizing strategies, results algorithm issues, efficiency and good. I downloaded the original algorithm, there is a problem is that it is aimed at all upper and lower limits of the design variables are the same, so I modified the program and improvements, you can now deal with upper and lower limits of the inconsistency problem and fix the bug. Now, program modifications, and share, hoping to be useful to you
Update
: 2024-05-03
Size
: 2048
Publisher
:
firkin
【
matlab
】
GA_PSO
DL : 1
GA_PSO为GA和PSO混合的优化算法,粒子群算法与遗传算法结合-GA_PSO optimization algorithm for mixed GA and PSO, PSO and Genetic Algorithm
Update
: 2024-05-03
Size
: 3072
Publisher
:
zcx
【
matlab
】
Files
DL : 1
I send a file that contains 7 source code and simulation in matlab. source codes contain GA and HGAPSO and PSO local&global.simulink files contain svpwm,matrix converter direct&improve.
Update
: 2024-05-03
Size
: 48128
Publisher
:
Mohsen Rezaie
【
Program doc
】
FEX-GODLIKE-0.5
DL : 0
单/多目标优化程序,内含说明文档和Matlab程序-Global Optimum Determination by Linking and Interchanging Kindred Evaluators. This algorithm is an attempt to gen- eralize and improve the robustness of the four meta-heuristic optimization al- gorithms GA, PSO, DE and ASA, and generalize the optimization process by being capable to solve both single-objective and multi-objective optimization problems.
Update
: 2024-05-03
Size
: 289792
Publisher
:
丁飞
【
Other
】
GA(PSO)
DL : 0
遗传算法改进的粒子群算法,分享出来,希望对大家有用!-Genetic algorithm, the improved particle swarm algorithm, sharing, the hope that useful to everybody!
Update
: 2024-05-03
Size
: 5120
Publisher
:
liu
【
matlab
】
cuckoo_search.m
DL : 0
Xin she Yang提出的布谷鸟算法,用来解决最优化问题。相比于传统的遗传算法和粒子群算法,该算法的效率更高。-It is published by Xin she Yang and is able to solve the optimization question。it is one of the heuristic algorithm and has the advantage compared with the GA and PSO.
Update
: 2024-05-03
Size
: 3072
Publisher
:
李寄玮
【
AI-NN-PR
】
COR(v1.1)
DL : 0
资源竞争算法,此算法经过测算由于PSO、GA、SA等等,可以快速有效的优化。- Competition Over Resource Optimization Algorithm,
Update
: 2024-05-03
Size
: 2048
Publisher
:
孙少龙
«
1
2
3
4
5
6
7
8
9
10
11
»
DSSZ
is the largest source code store in internet!
Contact us :
1999-2046
DSSZ
All Rights Reserved.