Hossam Faris

TL;DR: The search capabilities of a recent nature-inspired algorithm called Multi-verse Optimizer is utilized to optimize clustering problems in two different approaches, one of which is a dynamic clustering algorithm, in which the number of clusters is automatically detected without any prior information.

TL;DR: This work proposes a hybrid machine learning approach to enhance sentiment analysis; as it builds a classification model based on three classes, which are positive, neutral, and negative emotions, using Support Vector Machines (SVM) classifier, while combining two feature selection techniques using the ReliefF and Multi-Verse Optimizer algorithms.

TL;DR: It is ascertained that the SSA-ELM model is a qualified data-intelligent model for monthly river flow prediction at the Tigris river, Iraq, which outperformed the classical ELM and other artificial intelligence models.

TL;DR: This article reviews the latest research works to determine the most effective features that were investigated for spam detection in the literature and reveals the important role of some features like the reputation of the account, average length of the tweet, average mention per tweet, age of the accounts, and the average time between posts in the process of identifying spammers in the social network.

TL;DR: A novel wrapper feature selection approach based on augmented Whale Optimization Algorithm (WOA), which adopted in the context of IoT attacks detection and handles the high dimensionality of the problem is presented.