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Research articles

ScienceAsia 50S (2024):ID 2024s001 1-7 |doi: 10.2306/scienceasia1513-1874.2024.s001


A modified projective bi-inertial forward-backward splitting algorithm for detecting bone mineral density


Pentham Yothawuta, Pronpat Peeyadab, Wongthawat Liawrungrueangc, Watcharaporn Cholamjiakb,*

 
ABSTRACT:     In this work, we introduce a projective bi-inertial forward-backward splitting algorithm for solving the sum of two monotone operators in a real Hilbert space, one is maximally monotone and the other is Lipschitz continuous. Under standard assumptions, we prove weak convergence theorems of the proposed algorithm. Furthermore, we provide an application for data classification using an extreme learning machine. To gauge the effectiveness of the algorithm, a reliable dataset for bone mineral density prediction was taken from the Harvard Dataverse. Among the algorithms that have been compared, the best performance was obtained with our algorithm in terms of accuracy, precision, recall, and F1-score. The data classification results show that our algorithm is more efficient in handling classification problems.

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a Demonstration School, University of Phayao, Phayao 56000 Thailand
b Department of Mathematics, School of Science, University of Phayao, Phayao 56000 Thailand
c Department of Orthopaedics, School of Medicine, University of Phayao, Phayao 56000 Thailand

* Corresponding author, E-mail: watcharaporn.ch@up.ac.th

Received 14 Feb 2024, Accepted 6 Jul 2024