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New Studies for General Fractional Financial Models of Awareness and Trial Advertising Decisions

dc.contributor.author Abou Hasan, Muner M.
dc.contributor.author Baleanu, Dumitru
dc.contributor.author Sweilam, Nasser H.
dc.contributor.authorID 56389 tr_TR
dc.contributor.other 02.02. Matematik
dc.contributor.other 02. Fen-Edebiyat Fakültesi
dc.contributor.other 01. Çankaya Üniversitesi
dc.date.accessioned 2020-03-03T11:16:36Z
dc.date.accessioned 2025-09-18T12:10:21Z
dc.date.available 2020-03-03T11:16:36Z
dc.date.available 2025-09-18T12:10:21Z
dc.date.issued 2017
dc.description Abou Hasan, Muner/0000-0001-7610-6985; Sweilam, Nasser/0000-0001-7428-5799 en_US
dc.description.abstract In this paper, two numerical techniques are introduced to study numerically the general fractional advertising model. This system describes the flux of the consumers from unaware individuals group to aware or purchased group. The first technique is an asymptotically stable difference scheme, which was structured depending on the nonstandard finite difference method. This scheme preserves the properties of the solutions of the model problem as the positivity and the boundedness. The second technique is the Jacobi-Gauss-Lobatto spectral collocation method which is exponentially accurate. By means of this approach, such problem is reduced to solve a system of nonlinear algebraic equations and are greatly simplified the problem. Numerical comparisons to test the behavior of the used techniques are run out. We conclude from the computational work that: the Jacobi-Gauss-Lobatto spectral collocation method is more accurate whereas the nonstandard finite difference method requires less computational time. (C) 2017 Elsevier Ltd. All rights reserved. en_US
dc.description.publishedMonth 11
dc.identifier.citation Sweilam, Nasser H.; Abou Hasan, Muner M.; Baleanu, Dumitru, "New studies for general fractional financial models of awareness and trial advertising decisions", Chaos Solitons&Fractals, Vol.104, pp.772784, (2017). en_US
dc.identifier.doi 10.1016/j.chaos.2017.09.013
dc.identifier.issn 0960-0779
dc.identifier.issn 1873-2887
dc.identifier.scopus 2-s2.0-85030698926
dc.identifier.uri https://doi.org/10.1016/j.chaos.2017.09.013
dc.identifier.uri https://hdl.handle.net/123456789/11696
dc.language.iso en en_US
dc.publisher Pergamon-elsevier Science Ltd en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.subject Financial Models For Awareness And Trial en_US
dc.subject Nonstandard Finite Difference Method en_US
dc.subject Jacobi Polynomials en_US
dc.subject Collocation Method en_US
dc.subject Fractional Derivative en_US
dc.title New Studies for General Fractional Financial Models of Awareness and Trial Advertising Decisions en_US
dc.title New studies for general fractional financial models of awareness and trial advertising decisions tr_TR
dc.type Article en_US
dspace.entity.type Publication
gdc.author.id Abou Hasan, Muner/0000-0001-7610-6985
gdc.author.id Sweilam, Nasser/0000-0001-7428-5799
gdc.author.institutional Baleanu, Dumitru
gdc.author.scopusid 6507922829
gdc.author.scopusid 57190567470
gdc.author.scopusid 7005872966
gdc.author.wosid Baleanu, Dumitru/B-9936-2012
gdc.author.wosid Sweilam, Nasser/Q-2175-2019
gdc.description.department Çankaya University en_US
gdc.description.departmenttemp [Sweilam, Nasser H.] Cairo Univ, Dept Math, Fac Sci, Giza, Egypt; [Abou Hasan, Muner M.] Damascus Univ, Fac Econ 2, Dept Appl Stat, Damascus, Syria; [Baleanu, Dumitru] Cankaya Univ, Dept Math, Eskisehir Yolu 29 Km, TR-06810 Ankara, Turkey; [Baleanu, Dumitru] Inst Space Sci, Magurele, Romania en_US
gdc.description.endpage 784 en_US
gdc.description.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality Q1
gdc.description.startpage 772 en_US
gdc.description.volume 104 en_US
gdc.description.woscitationindex Science Citation Index Expanded
gdc.description.wosquality Q1
gdc.identifier.openalex W2761109152
gdc.identifier.wos WOS:000415298800081
gdc.openalex.fwci 3.47508091
gdc.openalex.normalizedpercentile 0.93
gdc.openalex.toppercent TOP 10%
gdc.opencitations.count 55
gdc.plumx.mendeley 19
gdc.plumx.scopuscites 63
gdc.scopus.citedcount 63
gdc.wos.citedcount 48
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