Hossam Faris

TL;DR: The experimental results show that the performance of the GA that uses the proposed regression-based technique for population seeded outperforms other GAs that uses traditional population seeding techniques such as the random and the nearest neighbor based techniques in terms of error rate, and average convergence.

TL;DR: The comparative study demonstrates that NPIR outperforms the other algorithms for the majority of the data sets in terms of different evaluation measures including Homogeneity Score, Completeness Score, V-measure, Adjusted Mutual Information, and Adjusted Rand Index.

TL;DR: This chapter first discusses inspirations, methematicam models, and an in-depth literature of the recently proposed Grey Wolf Optimizer (GWO) to analyze and benchmark the performance of different variants and improvements of this algorithm.

TL;DR: In this article, a new methodology for the detection of Ransomware that is depending on an evolutionary-based machine learning approach is introduced, where the binary particle swarm optimization algorithm is utilized for tuning the hyperparameters of the classification algorithm, as well as performing feature selection.

TL;DR: The research applies the proposed Modified Multi-Verse Optimization algorithm to several knapsack case studies and demonstrates its application in resource allocation of Adaptive Multimedia Systems (AMS).