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dc.contributor.authorSingh, Abhishek Kumar
dc.contributor.authorMehra, Mani
dc.date.accessioned2026-08-23T07:49:31Z
dc.date.available2026-08-23T07:49:31Z
dc.date.copyright2026/06/01
dc.date.issued2026
dc.identifier.issn1555-1415
dc.identifier.othercnd-24-1196.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4315661
dc.description.abstractAbstract. The least squares method provides the best-fit curve by minimizing the total squared error. In this work, we propose a modified least squares method based on fractional orthogonal polynomials that belong to the space Mnλ:=span{1,xλ,x2λ,…,xnλ}, λ∈(0,2]. Numerical experiments demonstrate how to solve different problems using the modified least squares method. Moreover, the results show the advantage of the modified least squares method compared to the classical least squares method. Furthermore, we discuss the various applications of the modified least squares method in fields such as fractional differential/integral equations and machine learning.
dc.publisherThe American Society of Mechanical Engineers (ASME)
dc.titleModified Least Squares Method and a Review of Its Applications in Machine Learning and Fractional Differential/Integral Equations
dc.typeJournal Paper
dc.journal.volume21
dc.journal.issue6
dc.journal.titleJournal of Computational and Nonlinear Dynamics
dc.identifier.doi10.1115/1.4071021
dc.journal.fristpage147
dc.journal.lastpage174
dc.page28
dc.treeJournal of Computational and Nonlinear Dynamics:;2026:;volume( 021 ):;issue:006
dc.contenttypeFulltext


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