Rational Function Model Optimization Based On Swarm Intelligence Metaheuristic Algorithms

dc.contributor.authorMezouar, Oussama
dc.contributor.authorMeskine, Fatiha
dc.contributor.authorBoukerch, Issam
dc.date.accessioned2022-04-14T11:20:21Z
dc.date.available2022-04-14T11:20:21Z
dc.date.issued2022-01-24
dc.descriptionForum Intervention of Artificial Intelligence and Its Applications. Faculty of Exat science. University of Eloueden_US
dc.description.abstractThe Rrational Function Model (RFM) is progressively being familiar to the mapping and photogrammetric researchersand has been widely used as an approximate to rigorous Models. According to it ability to preserve the complete accuracy of various types of physical sensors and its independence of sensors and platforms, it can be had with any coordination system. Nevertheless, the RFM coefficients are also known as rational polynomial coefficients (RPCs) dependent on a large number of ground control points which makes the model susceptible to over parameterization error and a time-consuming also the RPCs have no physical meaning, as a result, selecting the best combination of RPCs is difficult. The intelligent algorithms based meta-heuristic optimization seem to be an effective approach for overcoming this problem. This paper focuses on the application of recent swarm intelligence based meta-heuristic algorithms for RFM optimization. The most popular optimization methods considered are ant colony algorithm, genetic algorithms and particle swarm optimization.Furthermore in this research we proposed an parallel hybrid metaheuristic optimization algorithm that combines the genetic algorithm and particle swarm optimization concepts to overcoming the swarm intelligent limitations for RFM optimization. The different algorithms are applied for two data sets provided from the Algerian satellite (ALSAT2).The results demonstrated that the proposed method is more accurate than the threesuggested based meta-heuristic methods.en_US
dc.identifier.citationMezouar, Oussama. Meskine, Fatiha. Boukerch, Issam. Rational Function Model Optimization Based On Swarm Intelligence Metaheuristic Algorithms. Forum of Artificial Intelligence and Its Applications. 24-26 Jan 2022. Faculty of Exat science. University of Eloued. [visited in ../../….]. available from [copy the link here]en_US
dc.identifier.urihttps://dspace.univ-eloued.dz/handle/123456789/10832
dc.language.isoenen_US
dc.publisherUniversity of Eloued جامعة الواديen_US
dc.subjectRational function model, ant colony algothms, Genetic algorithms, particle swarm optimization, hybrid algorithms.en_US
dc.titleRational Function Model Optimization Based On Swarm Intelligence Metaheuristic Algorithmsen_US
dc.typeOtheren_US

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Rational Function Model Optimization Based On.pdf
Size:
1003.96 KB
Format:
Adobe Portable Document Format
Description:
Forum Intervention of Artificial Intelligence and Its Applications. Faculty of Exat science. University of Eloued

License bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description: