Çankaya GCRIS Standart veritabanının içerik oluşturulması ve kurulumu Research Ecosystems (https://www.researchecosystems.com) tarafından devam etmektedir. Bu süreçte gördüğünüz verilerde eksikler olabilir.
 

Fractional Order Computing and Modeling with Portending Complex Fit Real-World Data

dc.contributor.authorKaraca, Yeliz
dc.contributor.authorRahman, Mati ur
dc.contributor.authorBaleanu, Dumitru
dc.contributor.authorID56389tr_TR
dc.date.accessioned2024-06-03T13:08:03Z
dc.date.available2024-06-03T13:08:03Z
dc.date.issued2023
dc.departmentÇankaya Üniversitesi, Fen - Edebiyat Fakültesi, Matematik Bölümüen_US
dc.description.abstractFractional computing models identify the states of different systems with a focus on formulating fractional order compartment models through the consideration of differential equations based on the underlying stochastic processes. Thus, a systematic approach to address and ensure predictive accuracy allows that the model remains physically reasonable at all times, providing a convenient interpretation and feasible design regarding all the parameters of the model. Towards these manifolding processes, this study aims to introduce new concepts of fractional calculus that manifest crossover effects in dynamical models. Piecewise global fractional derivatives in sense of Caputo and Atangana-Baleanu-Caputo (ABC) have been utilized, and they are applied to formulate the Zika Virus (ZV) disease model. To have a predictive analysis of the behavior of the model, the domain is subsequently split into two subintervals and the piecewise behavior is investigated. Afterwards, the fixed point theory of Schauder and Banach is benefited from to prove the existence and uniqueness of at least one solution in both senses for the considered problem. As for the numerical simulations as per the data, Newton interpolation formula has been modified and extended for the considered nonlinear system. Finally, graphical presentations and illustrative examples based on the data for various compartments of the systems have been presented with respect to the applicable real-world data for different fractional orders. Based on the impact of fractional order reducing the abrupt changes, the results obtained from the study demonstrate and also validate that increasing the fractional order brings about a greater crossover effect, which is obvious from the observed data, which is critical for the effective management and control of abrupt changes like infectious diseases, viruses, among many more unexpected phenomena in chaotic, uncertain and transient circumstances.en_US
dc.identifier.citationKaraca, Yeliz; Rahman, Mati ur; Baleanu, Dumitru. Fractional Order Computing and Modeling with Portending Complex Fit Real-World Data, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 23rd International Conference on Computational Science and Its Applications, ICCSA 2023, 3 July 2023through 6 July 2023, Vol. 14104 LNCS, pp. 144 - 159,en_US
dc.identifier.doi10.1007/978-3-031-37105-9_11
dc.identifier.endpage159en_US
dc.identifier.issn0302-9743
dc.identifier.startpage144en_US
dc.identifier.urihttp://hdl.handle.net/20.500.12416/8466
dc.identifier.volume14104 LNCSen_US
dc.language.isoenen_US
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectABC Fractional Derivativesen_US
dc.subjectComplex Fit Real-World Dataen_US
dc.subjectComputational Biologyen_US
dc.subjectCrossover Behavioren_US
dc.subjectDifferential Equationsen_US
dc.subjectDynamics of Multi-Compartment Modelsen_US
dc.subjectEquicontinuous Mappingen_US
dc.subjectFractional Calculusen_US
dc.subjectFractional Computing Modelsen_US
dc.subjectFractional Order Compartment Modelsen_US
dc.subjectMathematical Biologyen_US
dc.subjectNewton Interpolation Formulaen_US
dc.subjectPiecewise Global Fractional Derivativesen_US
dc.subjectSchauder’s Fixed Point Theoremen_US
dc.subjectStochastic Differential Equationsen_US
dc.titleFractional Order Computing and Modeling with Portending Complex Fit Real-World Datatr_TR
dc.titleFractional Order Computing and Modeling With Portending Complex Fit Real-World Dataen_US
dc.typeConference Objecten_US
dspace.entity.typePublication

Files

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: