Treffer: New inertial self-adaptive algorithms for the split common null-point problem: application to data classifications

Title:
New inertial self-adaptive algorithms for the split common null-point problem: application to data classifications
Authors:
Ratthaprom Promkam, Pongsakorn Sunthrayuth, Suparat Kesornprom, Ekapak Tanprayoon
Source:
Journal of Inequalities and Applications, Vol 2023, Iss 1, Pp 1-32 (2023)
Publisher Information:
Springer Science and Business Media LLC, 2023.
Publication Year:
2023
Subject Terms:
p-uniformly convex Banach spaces, Inverse Problems in Mathematical Physics and Imaging, Economics, FOS: Political science, Norm (philosophy), 0211 other engineering and technologies, 02 engineering and technology, Fixed-Point Problems, Null (SQL), Self-adaptive algorithm, Biochemistry, Gene, 01 natural sciences, Interior-Point Methods, Nonexpansive Mappings, Political science, Mathematical Physics, Numerical Analysis, Numerical Optimization Techniques, Physics, Mathematical optimization, Iterative Algorithms for Nonlinear Operators and Optimization, Discrete mathematics, 3. Good health, Regular polygon, Algorithm, Chemistry, Computational Theory and Mathematics, Physical Sciences, Convergence (economics), Split common null-point problem, Convex Optimization, Geometry, FOS: Law, Operator (biology), Mathematical analysis, Quantum mechanics, Bounded function, QA1-939, FOS: Mathematics, Iterative Algorithms, 0101 mathematics, Weak convergence, Data mining, Economic growth, Banach space, Applied mathematics, Computer science, Maximal monotone operator, Computer Science, Repressor, Inertial frame of reference, Transcription factor, Law, Mathematics
Document Type:
Fachzeitschrift Article<br />Other literature type
Language:
English
ISSN:
1029-242X
DOI:
10.1186/s13660-023-03049-2
DOI:
10.60692/tjadw-28s24
DOI:
10.60692/76ewz-en876
Access URL:
https://doaj.org/article/dae8132c46fb4851aa5bd5409445106d
Rights:
CC BY
Accession Number:
edsair.doi.dedup.....40bf8d1d77a3e93a97b3d6e471c49d97
Database:
OpenAIRE

Weitere Informationen

In this paper, we propose two inertial algorithms with a new self-adaptive step size for approximating a solution of the split common null-point problem in the framework of Banach spaces. The step sizes are adaptively updated over each iteration by a simple process without the prior knowledge of the operator norm of the bounded linear operator. Under suitable conditions, we prove the weak-convergence results for the proposed algorithms inp-uniformly convex and uniformly smooth Banach spaces. Finally, we give several numerical results in both finite- and infinite-dimensional spaces to illustrate the efficiency and advantage of the proposed methods over some existing methods. Also, data classifications of heart diseases and diabetes mellitus are presented as the applications of our methods.