Search Results - "Faris, Hossam"
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1
Harris hawks optimization: Algorithm and applications
Published in Future generation computer systems (01-08-2019)“…In this paper, a novel population-based, nature-inspired optimization paradigm is proposed, which is called Harris Hawks Optimizer (HHO). The main inspiration…”
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MTDE: An effective multi-trial vector-based differential evolution algorithm and its applications for engineering design problems
Published in Applied soft computing (01-12-2020)“…In this article, an effective metaheuristic algorithm named multi-trial vector-based differential evolution (MTDE) is proposed. The MTDE is distinguished by…”
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3
Grasshopper optimization algorithm for multi-objective optimization problems
Published in Applied intelligence (Dordrecht, Netherlands) (01-04-2018)“…This work proposes a new multi-objective algorithm inspired from the navigation of grass hopper swarms in nature. A mathematical model is first employed to…”
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Salp Swarm Algorithm: A bio-inspired optimizer for engineering design problems
Published in Advances in engineering software (1992) (01-12-2017)“…•A novel optimization algorithm called Salp Swarm Optimizer (SSA) is proposed.•Multi-objective Salp Swarm Algorithm (MSSA) is proposed to solve multi-objective…”
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A Hybrid Swarm Intelligent Neural Network Model for Customer Churn Prediction and Identifying the Influencing Factors
Published in Information (Basel) (17-11-2018)“…Customer churn is one of the most challenging problems for telecommunication companies. In fact, this is because customers are considered as the real asset for…”
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6
Binary dragonfly optimization for feature selection using time-varying transfer functions
Published in Knowledge-based systems (01-12-2018)“…•Novel feature selection approaches based on Binary Dragonfly Algorithm (BDA) are proposed.•Eight time varying S-shaped and V-shaped transfer functions are…”
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An evolutionary gravitational search-based feature selection
Published in Information sciences (01-09-2019)“…•Gravitational Search Algorithm (GSA) was used as a search strategy in a Feature Selection approach.•Crossover and Mutation evolutionary operators were used to…”
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An enhanced associative learning-based exploratory whale optimizer for global optimization
Published in Neural computing & applications (01-05-2020)“…Whale optimization algorithm (WOA) is a recent nature-inspired metaheuristic that mimics the cooperative life of humpback whales and their spiral-shaped…”
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Feature selection using binary grey wolf optimizer with elite-based crossover for Arabic text classification
Published in Neural computing & applications (01-08-2020)“…Text classification is one of the challenging computational tasks in machine learning community due to the increased amounts of natural language text documents…”
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Evolutionary Population Dynamics and Grasshopper Optimization approaches for feature selection problems
Published in Knowledge-based systems (01-04-2018)“…Searching for the optimal subset of features is known as a challenging problem in feature selection process. To deal with the difficulties involved in this…”
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Clustering analysis using a novel locality-informed grey wolf-inspired clustering approach
Published in Knowledge and information systems (01-02-2020)“…Grey wolf optimizer (GWO) is known as one of the recent popular metaheuristic algorithms inspired from the social collaboration and team hunting activities of…”
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Evolving random weight neural networks based on oversampled-segmented examples for IoT intrusion detection
Published in The Journal of supercomputing (2024)“…The intrusion detection system is responsible for revealing different intrusion activities, including the denial of service, man-in-middle, Mirai, Scan, and…”
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13
Feature engineering for detecting spammers on Twitter: Modelling and analysis
Published in Journal of information science (01-04-2018)“…Twitter is a social networking website that has gained a lot of popularity around the world in the last decade. This popularity made Twitter a common target…”
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14
Relational Learning Analysis of Social Politics using Knowledge Graph Embedding
Published in Data mining and knowledge discovery (01-07-2021)“…Knowledge Graphs (KGs) have gained considerable attention recently from both academia and industry. In fact, incorporating graph technology and the copious of…”
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A Modified Multi-objective Particle Swarm Optimizer-Based Lévy Flight: An Approach Toward Intrusion Detection in Internet of Things
Published in Arabian journal for science and engineering (2011) (01-08-2020)“…The emerging of the Internet of things (IoT), and more, the advent of the Internet of everything have revolutionized the computer networks industry. The high…”
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EvoImputer: An evolutionary approach for Missing Data Imputation and feature selection in the context of supervised learning
Published in Knowledge-based systems (25-01-2022)“…Missing data is a considerable problem in knowledge extraction where the completeness and the quality of the data play a major role in data analysis. In many…”
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Specialty detection in the context of telemedicine in a highly imbalanced multi-class distribution
Published in PloS one (16-11-2023)“…The Covid-19 pandemic has led to an increase in the awareness of and demand for telemedicine services, resulting in a need for automating the process and…”
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A Multi-Layer Classification Approach for Intrusion Detection in IoT Networks Based on Deep Learning
Published in Sensors (Basel, Switzerland) (24-04-2021)“…The security of IoT networks is an important concern to researchers and business owners, which is taken into careful consideration due to its direct impact on…”
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Intelligent detection of hate speech in Arabic social network: A machine learning approach
Published in Journal of information science (01-08-2021)“…Nowadays, cyber hate speech is increasingly growing, which forms a serious problem worldwide by threatening the cohesion of civil societies. Hate speech…”
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Hybridized Extreme Learning Machine Model with Salp Swarm Algorithm: A Novel Predictive Model for Hydrological Application
Published in Complexity (New York, N.Y.) (2020)“…The capability of the extreme learning machine (ELM) model in modeling stochastic, nonlinear, and complex hydrological engineering problems has been proven…”
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