scholarly journals A cost-effective algorithm for the solution of engineering problems with particle swarm optimization

2010 ◽  
Vol 42 (5) ◽  
pp. 471-495 ◽  
Author(s):  
Giordano Tomassetti
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Cost Effective ◽  
Effective Algorithm ◽  
Swarm Optimization ◽  
Engineering Problems

Biogeography-based particle swarm optimization with fuzzy elitism and its applications to constrained engineering problems

2013 ◽  
Vol 46 (11) ◽  
pp. 1465-1484 ◽  
Author(s):  
Weian Guo ◽  
Wuzhao Li ◽  
Qun Zhang ◽  
Lei Wang ◽  
Qidi Wu ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Engineering Problems

scholarly journals Using particle swarm optimization to solve test functions problems

2021 ◽  
Vol 10 (6) ◽  
pp. 3422-3431
Author(s):  
Issa Ahmed Abed ◽  
May Mohammed Ali ◽  
Afrah Abood Abdul Kadhim
Keyword(s):  
Genetic Algorithm ◽  
Particle Swarm Optimization ◽  
Standard Deviation ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Speed Of Convergence ◽  
Test Functions ◽  
Objective Functions ◽  
Swarm Optimization ◽  
Engineering Problems

In this paper the benchmarking functions are used to evaluate and check the particle swarm optimization (PSO) algorithm. However, the functions utilized have two dimension but they selected with different difficulty and with different models. In order to prove capability of PSO, it is compared with genetic algorithm (GA). Hence, the two algorithms are compared in terms of objective functions and the standard deviation. Different runs have been taken to get convincing results and the parameters are chosen properly where the Matlab software is used. Where the suggested algorithm can solve different engineering problems with different dimension and outperform the others in term of accuracy and speed of convergence.

scholarly journals Optimization of DNA Sensor Model Based Nanostructured Graphene Using Particle Swarm Optimization Technique

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Hediyeh Karimi ◽  
Rubiyah Yusof ◽  
Rasoul Rahmani ◽  
Mohammad Taghi Ahmadi
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Technique ◽  
Particle Swarm ◽  
Cost Effective ◽  
Dna Sensor ◽  
Dna Sensors ◽  
Dna Adsorption ◽  
Swarm Optimization ◽  
Particle Swarm Optimization Technique ◽  
Optimized Model

It has been predicted that the nanomaterials of graphene will be among the candidate materials for postsilicon electronics due to their astonishing properties such as high carrier mobility, thermal conductivity, and biocompatibility. Graphene is a semimetal zero gap nanomaterial with demonstrated ability to be employed as an excellent candidate for DNA sensing. Graphene-based DNA sensors have been used to detect the DNA adsorption to examine a DNA concentration in an analyte solution. In particular, there is an essential need for developing the cost-effective DNA sensors holding the fact that it is suitable for the diagnosis of genetic or pathogenic diseases. In this paper, particle swarm optimization technique is employed to optimize the analytical model of a graphene-based DNA sensor which is used for electrical detection of DNA molecules. The results are reported for 5 different concentrations, covering a range from 0.01 nM to 500 nM. The comparison of the optimized model with the experimental data shows an accuracy of more than 95% which verifies that the optimized model is reliable for being used in any application of the graphene-based DNA sensor.

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