Progressive Iterative Approximation Method with Memory and Sequences of Weights for Least Square Curve Fitting

บทความในวารสาร

ผู้เขียน/บรรณาธิการ

กลุ่มสาขาการวิจัยเชิงกลยุทธ์

รายละเอียดสำหรับงานพิมพ์

รายชื่อผู้แต่ง: Channark, Saknarin; Kumam, Poom; Chaipunya, Parin; Jirakitpuwapat, Wachirapong;

ปีที่เผยแพร่ (ค.ศ.): 2023

Volume number: 28

Issue number: 1

หน้าแรก: 90

หน้าสุดท้าย: 107

จำนวนหน้า: 18

นอก: 2586-9000

URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85151531313&partnerID=40&md5=11500dcb1937ce5ce7ba24ef410082fe

ภาษา: English-Great Britain (EN-GB)

บทคัดย่อ

The progressive iterative approximation method with memory and sequences of weights for least square curve fitting (SSLSPIA) is presented in this paper. This method improves the MLSPIA method by varying the weights of the moving average between it-erations, using three sequences of weights derived from the singular values of a colloca-tion matrix. It is proved that a sequence of fitting curves with an appropriate alternative of weights converge to the solution of least square fitting and that the convergence rate of the new method is faster than that of the MLSPIA method. Some examples and applications in this paper prove the SSLSPIA method is superior. © 2023, Thammasat University. All rights reserved.

คำสำคัญ

Least square curve fitting, Sequences of weights