Abu Zitar, Raed
An Intensive and Comprehensive Overview of JAYA Algorithm, its Versions and Applications
2022, Zitar, Raed, Al‑Betar, Mohammed Azmi, Awadallah, Mohammed A., Abu Doush, Iyad, Assaleh, Khaled
In this review paper, JAYA algorithm, which is a recent population-based algorithm is intensively overviewed. The JAYA algorithm combines the survival of the fittest principle from evolutionary algorithms as well as the global optimal solution attractions of Swarm Intelligence methods. Initially, the optimization model and convergence characteristics of JAYA algorithm are carefully analyzed. Thereafter, the proposed versions of JAYA algorithm have been surveyed such as modified, binary, hybridized, parallel, chaotic, multi-objective and others. The various applications tackled using relevant versions of JAYA algorithm are also discussed and summarized based on several problem domains. Furthermore, the open sources code of JAYA algorithm are identified to provide enrich resources for JAYA research communities. The critical analysis of JAYA algorithm reveals its advantages and limitations in dealing with optimization problems. Finally, the paper ends up with conclusion and possible future enhancements suggested to improve the performance of JAYA algorithm. The reader of this overview will determine the best domains and applications used by JAYA algorithm and can justify their JAYA-related contributions.
Intensive Review of Drones Detection and Tracking: Linear Kalman Filter Versus Nonlinear Regression, an Analysis Case
2023, Abu Zitar, Raed, Mohsen, Amani, Seghrouchni, Amal ElFallah, Barbaresco, Frederic, Al-Dmour, Nidal A.
In this paper, an extensive review for objects and drones (AUVs) detection and tracking is presented. The article presents state of the art methods used in detection and tracking of drones with adequate analysis and comparisons summarizing the findings of the most recent research material in that field. The most famous technique used in drones tracking is Kalman Filters (KFs) in its different forms. The paper presents analysis and comparisons for drones tracking based on Linear Kalman Filters (LKF) compared to tracking using Nonlinear Polynomial Regression (NPR) techniques. Interesting findings reflect the need for both methods at different circumstances depending on the noise conditions of the measurements. On the other hand, many new methods such as Artificial Intelligence (AI) based techniques are recently used in drones detection and recognition. Detection methods could come separate or combined with tracking techniques. The work presents broad and deep literature review with critical analysis of most famous methods used in drones detection and tracking.
Differential Evolution and Its Applications in Image Processing Problems: A Comprehensive Review
2023, Chakraborty, Sanjoy, Saha, Apu Kumar, Ezugwu, Absalom E., Agushaka, Jeffrey O., Abu Zitar, Raed, Abualigah, Laith
Differential evolution (DE) is one of the highly acknowledged population-based optimization algorithms due to its simplicity, user-friendliness, resilience, and capacity to solve problems. DE has grown steadily since its beginnings due to its ability to solve various issues in academics and industry. Different mutation techniques and parameter choices influence DE's exploration and exploitation capabilities, motivating academics to continue working on DE. This survey aims to depict DE's recent developments concerning parameter adaptations, parameter settings and mutation strategies, hybridizations, and multiobjective variants in the last twelve years. It also summarizes the problems solved in image processing by DE and its variants.
Gradient-Based Optimizer (GBO): A Review, Theory, Variants, and Applications
2023, Daoud, Mohammad Sh., Shehab, Mohammad, Al-Mimi, Hani M., Abualigah, Laith, Zitar, Raed, Shambour, Mohd Khaled Yousef
This paper introduces a comprehensive survey of a new population-based algorithm so-called gradient-based optimizer (GBO) and analyzes its major features. GBO considers as one of the most effective optimization algorithm where it was utilized in different problems and domains, successfully. This review introduces set of related works of GBO where distributed into; GBO variants, GBO applications, and evaluate the efficiency of GBO compared with other metaheuristic algorithms. Finally, the conclusions concentrate on the existing work on GBO, showing its disadvantages, and propose future works. The review paper will be helpful for the researchers and practitioners of GBO belonging to a wide range of audiences from the domains of optimization, engineering, medical, data mining and clustering. As well, it is wealthy in research on health, environment and public safety. Also, it will aid those who are interested by providing them with potential future research.