Research Article A Modified Scaled Spectral-Conjugate Gradient-Based Algorithm for Solving Monotone Operator Equations Auwal Bala Abubakar , 1,2 Kanikar Muangchoo , 3 Abdulkarim Hassan Ibrahim , 4 SundayEmmanuelFadugba , 5 KazeemOlalekanAremu , 2,6 andLateefOlakunleJolaoso 2 1 Department of Mathematical Sciences, Faculty of Physical Sciences, Bayero University, Kano, Kano, Nigeria 2 Department of Mathematics and Applied Mathematics, Sefako Makgatho Health Sciences University, Ga-Rankuwa, Pretoria 0204, South Africa 3 Faculty of Science and Technology, Rajamangala University of Technology Phra Nakhon (RMUTP), 1381, Pracharat 1 Road, Wongsawang, Bang Sue, Bangkok 10800, ailand 4 KMUTT Fixed Point Research Laboratory, Room SCL 802 Fixed Point Laboratory, Science Laboratory Building, Department of Mathematics, Faculty of Science, King Mongkut’s University of Technology onburi (KMUTT), 126 Pracha-Uthit Road, Bang Mod, rung Khru, Bangkok 10140, ailand 5 Department of Mathematics, Ekiti State University, Ado Ekiti 360001, Nigeria 6 Department of Mathematics, Faculty of Science, Usmanu Danfodio University Sokoto, Sokoto, Nigeria Correspondence should be addressed to Kanikar Muangchoo; kanikar.m@rmutp.ac.th Received 13 January 2021; Revised 11 April 2021; Accepted 13 April 2021; Published 26 April 2021 Academic Editor: Jen-Chih Yao Copyright © 2021 Auwal Bala Abubakar et al. is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. is paper proposes a modified scaled spectral-conjugate-based algorithm for finding solutions to monotone operator equations. e algorithm is a modification of the work of Li and Zheng in the sense that the uniformly monotone assumption on the operator is relaxed to just monotone. Furthermore, unlike the work of Li and Zheng, the search directions of the proposed algorithm are shown to be descent and bounded independent of the monotonicity assumption. Moreover, the global convergence is established under some appropriate assumptions. Finally, numerical examples on some test problems are provided to show the efficiency of the proposed algorithm compared to that of Li and Zheng. 1. Introduction We desire in this work to propose an algorithm to solve the problem: F(x)� 0, x ∈ C, (1) where F: R n ⟶ R n is monotone and Lipschitz continuous and C ⊆ R n is nonempty, closed, and convex. Solving problems of form (1) are becoming interesting in recent years due to its appearance in many areas of science, engineering, and economy, for example, in forecasting of financial market [1], constrained neural networks [2], eco- nomic and chemical equilibrium problems [3, 4], signal and image processing [5, 6], phase retrieval [7, 8], power flow equations [9], nonnegative matrix factorisation [10, 11], and many more. Some notable methods for finding solution to (1) are: Newton’s method, quasi-Newton method, Gauss–Newton method, Levenberg–Marquardt method, and their vari- ants [12–15]. ese methods are prominent due to their fast convergence property. However, their convergence is local, and they require computing and storing of the Jacobian matrix at each iteration. In addition, there is a need to solve a linear equation at each iteration. ese and other reasons make them unattractive especially for large- scale problems. To avoid the above drawbacks, methods that are globally convergent and also do not require computing and storing of the Jacobian matrix were Hindawi Journal of Mathematics Volume 2021, Article ID 5549878, 9 pages https://doi.org/10.1155/2021/5549878