2021/06/08 by Jaafar Hammoud, A. M. Eisa, Hammoud, Jaafar +5
Computer Science · Engineering · Mathematics · #Advanced Optimization Algorithms Research #Computation and Language (cs.CL) #FOS: Computer and information sciences #FOS: Mathematics #Metaheuristic Optimization Algorithms Research #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques
paper · pdf · doi:10.48550/arxiv.2106.04383
openalex publication_date 2021/06/08 · openalex created_date 2021/06/22 · openalex updated_date 2026/07/28
Gradient methods have applications in multiple fields, including signal processing, image processing, and dynamic systems. In this paper, we present a nonlinear gradient method for solving convex supra-quadratic functions by developing the search direction, that done by hybridizing between the two conjugate coefficients HRM [2] and NHS [1]. The numerical results proved the effectiveness of the presented method by applying it to solve standard problems and reaching the exact solution if the objective function is quadratic convex. Also presented in this article, an application to the problem of named entities in the Arabic medical language, as it proved the stability of the proposed method and its efficiency in terms of execution time.