activity
20232025
most citedAn Improved FOX Optimization Algorithm Using Adaptive Exploration and Exploitation for Global Optimization

4 citations · 9 across the 7 of their papers we have counts for

collaborators

7 papers

cs.AI2025★ 4 cited

An Improved FOX Optimization Algorithm Using Adaptive Exploration and Exploitation for Global Optimization

Mahmood A. Jumaah, Yossra H. Ali, Tarik A. Rashid

Optimization algorithms are essential for solving many real-world problems. However, challenges such as getting trapped in local minima and effectively balancing exploration and ex…

cs.AI2025★ 4 cited

Artificial Liver Classifier: A New Alternative to Conventional Machine Learning Models

Mahmood A. Jumaah, Yossra H. Ali, Tarik A. Rashid

Supervised machine learning classifiers sometimes face challenges related to the performance, accuracy, or overfitting. This paper introduces the Artificial Liver Classifier (ALC),…

cs.NE2024

MOANA: Multi-Objective Ant Nesting Algorithm for Optimization Problems

Noor A. Rashed, Yossra H. Ali Tarik A. Rashid, Seyedali Mirjalili

This paper presents the Multi-Objective Ant Nesting Algorithm (MOANA), a novel extension of the Ant Nesting Algorithm (ANA), specifically designed to address multi-objective optimi…

cs.NE2024

Unraveling the Versatility and Impact of Multi-Objective Optimization: Algorithms, Applications, and Trends for Solving Complex Real-World Problems

Noor A. Rashed, Yossra H. Ali, Tarik A. Rashid +1

Multi-Objective Optimization (MOO) techniques have become increasingly popular in recent years due to their potential for solving real-world problems in various fields, such as log…

cs.NE2024★ 1 cited

FOXANN: A Method for Boosting Neural Network Performance

Mahmood A. Jumaah, Yossra H. Ali, Tarik A. Rashid +1

Artificial neural networks play a crucial role in machine learning and there is a need to improve their performance. This paper presents FOXANN, a novel classification model that c…

cs.LG2024

QF-tuner: Breaking Tradition in Reinforcement Learning

Mahmood A. Jumaah, Yossra H. Ali, Tarik A. Rashid

In reinforcement learning algorithms, the hyperparameters tuning method refers to choosing the optimal parameters that may increase the overall performance. Manual or random hyperp…

cs.NE2023

BCDDO: Binary Child Drawing Development Optimization

Abubakr S. Issa, Yossra H. Ali, Tarik A. Rashid

A lately created metaheuristic algorithm called Child Drawing Development Optimization (CDDO) has proven to be effective in a number of benchmark tests. A Binary Child Drawing Deve…