Essam Said Hanandeh

@zu.edu.jo

Faculty of Information Technology - Computer Science
Zarqa University

Essam Said Hanandeh


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https://researchid.co/hanandeh

RESEARCH INTERESTS

Database,Information Retrieval,Data Mining
44

Scopus Publications

2696

Scholar Citations

20

Scholar h-index

27

Scholar i10-index

Scopus Publications

  • The Integration of Artificial Intelligence and Robotics for Autonomous Systems
    Essam Hanandeh, Javed Jimanal, Husam Mashaqbeh, Peiying Zhang, Virbea Deharan, Zhe Liu, Gang Hu, Aseel Smerat, Laith Abualigah
    Deep Learning Applications Select Topics, 2026
    Artificial Intelligence (AI) and robotics complemented each other and transformed industries where machines have to complete activities that need not only accuracy but intelligence as well. This paper presents issues of AI integration into robotics, and the enhancements that facilitate robots autonomously perceive, reason, and self-optimize things over a period. We provide details on important AI mechanisms, which are deep learning, reinforcement learning, and computer vision, with their general application in robotic systems. Through various case studies and experiments, we show how AI-driven robotics has succeeded in improving industries such as healthcare, automation, and mass manufacturing, and autonomous transportation. There is also mention of the issues and ethics of artificial intelligence robotic integrations as well as a perspective on the prospects of such interactions.
  • Convolutional Neural Networks: The Power Behind Image Recognition
    Mohammad H. Almomani, Essam Hanandeh, Canan Batur Şahin, Peiying Zhang, Zuzho Zuong, Ahmad Nasayreh, Aseel Smerat, Laith Abualigah
    A to Z of Deep Learning and AI, 2025
    A number of artificial intelligence advancements have emerged that allow computerizes the same critical thinking tasks that were solely more suited to humans such as image recognition of objects etc. One such advancement that is the focus of the paper is the Convolutional Neural Networks. This paper details the structural design, how they perform the tasks assigned and how they function as a contribution to the image recognition area. Additionally, we show through a case study of three CNN models how they can be evaluated in relation to one set of common data effectively and efficiently. The data shows that there was improvement in processing time and accuracy which emphasises the role of CNN in the detailed domains. Some future trends in the CNN development and its usages are presented.
  • Quantum Computing with Artifcial Intelligence: A Paradigm Shift in Intelligent Systems
    Essam Hanandeh, Shengxiang Zang, Jiajin Kang, Gang Hu, Samila Sighm, Aseel Smerat, Absalom E. Ezugwu, Vaclav Snasel, Laith Abualigah
    A to Z of Deep Learning and AI, 2025
    Quantum artificial intelligence is an important step forward in the relationship with both quantum computing and AI. This paper investigates the use of quantum computing technique as an augmentation to AI capabilities efficiencies in data retrieval, model development, and problem resolution. A very general description is provided of self-consistence concepts of quantum computing, the main milestones in the field of quantum artificial intelligence, and practical analogs in a range of areas. Algorithm development, the development of hardware, and ethics are the obstacles that are mentioned, which then give some perspectives concerning the future within this new field.
  • Generative Adversarial Networks (GANs): A Paradigm Shift and Revolutionizing Content Creation with Artifcial Intelligence Creativity
    Essam Hanandeh, Khaled Aldiabat, A'kif Al-Fugara, Samila Sighm, Han-Liwa Xuanm, Shengxiang Zang, Aseel Smerat, Amir H. Gandomi, Laith Abualigah
    A to Z of Deep Learning and AI, 2025
    Generative Adversarial Networks (GANs) have become a remarkable innovation in the field of artificial intelligence that has revolutionized the way machines can make or generate content. With the use of a generator and a discriminator, two neural networks, GANs produce realistic data which does mimic real-world distributions. This paper examines the architecture and workings of GANs, details their different use cases in different sectors, and assesses their appropriateness with the help of empirical results. We discuss our experimental results that include the performance of models on standard datasets and the ethical concerns and potential effects of GANs on the aspect of creativity and AI. The paper ends, with addressing future research possibilities regarding GAN technology development showing and stressing the importance of being responsible in development.
  • Optimizing Deep Learning Scalability: Harnessing Distributed Systems and Cloud Computing for Next-Generation AI
    Essam Hanandeh, Hung Vo Thanh, Faiza Gul, Magd Abdel Wahab, Ibrahim Al-Shourbaji, Nima Khodadadi, Absalom E. Ezugwu, Aseel Smerat, Laith Abualigah
    A to Z of Deep Learning and AI, 2025
    Deep learning has come to define entire pockets of sectors such as image and voice optimization, medical treatment and even self-driving cars. While at the same time, the complexity of the models has increased to scale new heights and thus the computational and data ingestion requirements have outgrown heavily. Therefore, in order to efficiently scale deep learning, energized and more streamlined computational backbone is required. This paper examines how distributed systems and cloud computing help in maintaining scaling of deep learning. It examines the problems of working with large models, the benefits of distributed training, and what is being proposed on cloud platforms. There is also a case study in which the effectiveness of deep learning models trained in different units was compared. Finally, research efforts and prospects for the use of new distributed systems and new cloud infrastructure for better scalability of deep learning models are discussed.
  • Backpropagation and Gradient Descent: Key Techniques for Neural Network Optimization
    Essam Hanandeh, Zahing Boo Laa, Haming Jia, A'kif Al-Fugara, Peiying Zhang, Zhe Liu, Ibrahim Al-Shourbaji, Aseel Smerat, Amir H. Gandomi, Laith Abualigah
    A to Z of Deep Learning and AI, 2025
    Deep learning is one of the most advanced fields of artificial intelligence today, and the field has prospered mainly due to deep learning’s characteristic feature of utilizing neural networks to learn complex patterns in data. As the networks consist of layers of nodes (neurons) connected to one another, they can learn large amounts of given data and captivate the relationships or dependencies that may be hard for traditional algorithms to grasp. These networks seem to have numerous advantages over other techniques, but they also present a major risk. That is, training these networks properly is very difficult, especially concerning the parameters of these networks that require rigorous tuning to be able to predict accurately. Optimization techniques are an integral part of training the network and enhancing its application in various machine-learning tasks. Among the different optimization techniques, the gradients descent and backpropagation are the most relevant and basic to the optimization, and therefore model training. The principles of these techniques with a special focus on the optimization of the neural network weights as well as their changes will be the subject of this work. These are quite common techniques, and this paper will help in extending their practical utilization. The focus will be mainly on the statistical and empirical aspect of different gradient descent methods for various neural network architectures explaining their convergence and training efficiency. The last section of the paper will deal with the future of optimization depicting an emotional picture of where the field will be most relevant in deep learning’s current state.
  • Ethical Frontiers in Artifcial Intelligence: Addressing the Challenges of Machine Intelligence
    Essam Hanandeh, Faisal Al-Saqqar, Mohammad Said El-Bashir, Raed Abu Zitar, Hung Vo Thanh, Magd Abdel Wahab, Mohammad H. Nadimi-Shahraki, Aseel Smerat, Amir H. Gandomi, Vaclav Snasel, Laith Abualigah
    A to Z of Deep Learning and AI, 2025
    The more artificial intelligence systems (AI) are applied in the day to day activities, the more people seek for ethics in the manner the AI systems are developed and used. The AI ethics is however complex and contradictory as it entails a number of interlinked factors, some of which are highlighted in this paper, including, but not limited to: discrimination, the increasing prominence of AI, questions of responsibility and privacy and surveillance by machines. The purpose of this study, through the analysis of literature and relevant case studies, is to pinpoint key ethical issues, assess existing practices, and seek to establish ethical AI development strategies. The research results point to the need of teamwork between representatives of technology, policy, and ethics to be able to develop meaningful guidelines that ensure AI technology is used responsibly.
  • Modified Aquila Optimizer Feature Selection Approach and Support Vector Machine Classifier for Intrusion Detection System
    Laith Abualigah, Saba Hussein Ahmed, Mohammad H. Almomani, Raed Abu Zitar, Anas Ratib Alsoud, Belal Abuhaija, Essam Said Hanandeh, Heming Jia, Diaa Salama Abd Elminaam, Mohamed Abd Elaziz
    Multimedia Tools and Applications, 2024
  • Salp swarm algorithm: survey, analysis, and new applications
    Laith Abualigah, Worod Hawamdeh, Raed Abu Zitar, Shadi AlZu’bi, Ala Mughaid, Essam Said Hanandeh, Anas Ratib Alsoud, El-Sayed M. El-kenawy
    Metaheuristic Optimization Algorithms Optimizers Analysis and Applications, 2024
  • Arithmetic optimization algorithm: a review and analysis
    Laith Abualigah, Aya Abusaleem, Abiodun M. Ikotun, Raed Abu Zitar, Anas Ratib Alsoud, Nima Khodadadi, Absalom E. Ezugwu, Essam Said Hanandeh, Heming Jia
    Metaheuristic Optimization Algorithms Optimizers Analysis and Applications, 2024
  • Aquila optimizer: review, results and applications
    Laith Abualigah, Batool Sbenaty, Abiodun M. Ikotun, Raed Abu Zitar, Anas Ratib Alsoud, Nima Khodadadi, Absalom E. Ezugwu, Essam Said Hanandeh, Heming Jia
    Metaheuristic Optimization Algorithms Optimizers Analysis and Applications, 2024
  • A review of krill herd algorithm: optimization and its applications
    Laith Abualigah, Mohammad Al-Zyod, Abiodun M. Ikotun, Mohammad Shehab, Mohammed Otair, Absalom E. Ezugwu, Essam Said Hanandeh, Ali Raza, El-Sayed M. El-kenawy
    Metaheuristic Optimization Algorithms Optimizers Analysis and Applications, 2024
  • A Survey of cuckoo search algorithm: optimizer and new applications
    Laith Abualigah, Ashraf Ababneh, Abiodun M. Ikotun, Raed Abu Zitar, Anas Ratib Alsoud, Nima Khodadadi, Absalom E. Ezugwu, Essam Said Hanandeh, Heming Jia
    Metaheuristic Optimization Algorithms Optimizers Analysis and Applications, 2024
  • Whale optimization algorithm: analysis and full survey
    Laith Abualigah, Roa’a Abualigah, Abiodun M. Ikotun, Raed Abu Zitar, Anas Ratib Alsoud, Nima Khodadadi, Absalom E. Ezugwu, Essam Said Hanandeh, Heming Jia
    Metaheuristic Optimization Algorithms Optimizers Analysis and Applications, 2024
  • Marine predator’s algorithm: a survey of recent applications
    Laith Abualigah, Suhier Odah, Abiodun M. Ikotun, Anas Ratib Alsoud, Agostino Forestiero, Absalom E. Ezugwu, Essam Said Hanandeh, Heming Jia, Mohsen Zare
    Metaheuristic Optimization Algorithms Optimizers Analysis and Applications, 2024
  • Teaching–learning-based optimization algorithm: analysis study and its application
    Laith Abualigah, Eman Abu-Dalhoum, Abiodun M. Ikotun, Raed Abu Zitar, Anas Ratib Alsoud, Nima Khodadadi, Absalom E. Ezugwu, Essam Said Hanandeh, Heming Jia
    Metaheuristic Optimization Algorithms Optimizers Analysis and Applications, 2024
  • Spider monkey optimizations: application review and results
    Laith Abualigah, Sahar M. Alshatti, Abiodun M. Ikotun, Raed Abu Zitar, Anas Ratib Alsoud, Nima Khodadadi, Absalom E. Ezugwu, Essam Said Hanandeh, Heming Jia, Mohsen Zare
    Metaheuristic Optimization Algorithms Optimizers Analysis and Applications, 2024
  • Revolutionizing sustainable supply chain management: A review of metaheuristics
    Laith Abualigah, Essam Said Hanandeh, Raed Abu Zitar, Cuong-Le Thanh, Samir Khatir, Amir H. Gandomi
    Engineering Applications of Artificial Intelligence, 2023
  • Improved Reptile Search Algorithm by Salp Swarm Algorithm for Medical Image Segmentation
    Laith Abualigah, Mahmoud Habash, Essam Said Hanandeh, Ahmad MohdAziz Hussein, Mohammad Al Shinwan, Raed Abu Zitar, Heming Jia
    Journal of Bionic Engineering, 2023
  • A Novel Methodology for Human Kinematics Motion Detection Based on Smartphones Sensor Data Using Artificial Intelligence
    Ali Raza, Mohammad Rustom Al Nasar, Essam Said Hanandeh, Raed Abu Zitar, Ahmad Yacoub Nasereddin, Laith Abualigah
    Technologies, 2023
  • Arabic Text Categorization Algorithm Using Vector Space Model
    Essam Hanandeh, Mohamed Shajahan
    Studies in Computational Intelligence, 2023
  • Extractive Arabic Text Summarization-Graph-Based Approach
    Yazan Alaya AL-Khassawneh, Essam Said Hanandeh
    Electronics Switzerland, 2023
  • Issues in Electronic Distance Learning
    Aref abu Awad, Essam Hanandeh, Halah Nasseif
    Studies in Computational Intelligence, 2023
  • Extractive Text Summarization Using Syntactic Sub-graph Models
    Yazan Alaya AL-Khassawneh, Essam Said Hanandeh, Sattam Almatarneh
    Lecture Notes on Data Engineering and Communications Technologies, 2023
  • Studying Risks of Hybrid Reengineering on Air-Transportation Systems Management 'A Case Study on Jordanian Civil Aviation Regulatory Commission (CARC)'
    Al Refai Mohammed N., Taani M.K. K., Ahmed Ali Otoom, Ghassan Samara, Hanandeh E. S, Hayel Khafajeh
    2023 24th International Arab Conference on Information Technology Acit 2023, 2023
  • Machine Learning and Network Traffic to Distinguish Between Malware and Benign Applications
    Laith Abualigah, Sayel Abualigah, Mothanna Almahmoud, Agostino Forestiero, Gagan Sachdeva, Essam S. Hanandeh
    Lecture Notes of the Institute for Computer Sciences Social Informatics and Telecommunications Engineering Lnicst, 2023
  • Image Processing Identification for Sapodilla Using Convolution Neural Network (CNN) and Transfer Learning Techniques
    Ali Khazalah, Boppana Prasanthi, Dheniesh Thomas, Nishathinee Vello, Suhanya Jayaprakasam, Putra Sumari, Laith Abualigah, Absalom E. Ezugwu, Essam Said Hanandeh, Nima Khodadadi
    Studies in Computational Intelligence, 2023
  • Classify Arabic Text using Vector Space Models
    Essam S. Hanandeh, Aref Abu Awwad, Yazan Khassawneh
    2021 22nd International Arab Conference on Information Technology Acit 2021, 2021
  • An improved b-hill climbing optimization technique for solving the text documents clustering problem
    Laith Mohammad Abualigah, Essam Said Hanandeh, Ahamad Tajudin Khader, Mohammed Abdallh Otair, Shishir Kumar Shandilya
    Current Medical Imaging Reviews, 2020
  • Modified krill herd algorithm for global numerical optimization problems
    Laith Mohammad Abualigah, Ahamad Tajudin Khader, Essam Said Hanandeh
    Eai Springer Innovations in Communication and Computing, 2019
  • Hybrid clustering analysis using improved krill herd algorithm
    Laith Mohammad Abualigah, Ahamad Tajudin Khader, Essam Said Hanandeh
    Applied Intelligence, 2018
  • A combination of objective functions and hybrid Krill herd algorithm for text document clustering analysis
    Laith Mohammad Abualigah, Ahamad Tajudin Khader, Essam Said Hanandeh
    Engineering Applications of Artificial Intelligence, 2018
  • A new feature selection method to improve the document clustering using particle swarm optimization algorithm
    Laith Mohammad Abualigah, Ahamad Tajudin Khader, Essam Said Hanandeh
    Journal of Computational Science, 2018
  • A novel weighting scheme applied to improve the text document clustering techniques
    Laith Mohammad Abualigah, Ahamad Tajudin Khader, Essam Said Hanandeh
    Studies in Computational Intelligence, 2018
  • A hybrid strategy for krill herd algorithm with harmony search algorithm to improve the data clustering
    Laith Mohammad Abualigah, Ahamad Tajudin Khader, Essam Said Hanandeh
    Intelligent Decision Technologies, 2018
  • A novel hybridization strategy for krill herd algorithm applied to clustering techniques
    Laith Mohammad Abualigah, Ahamad Tajudin Khader, Essam Said Hanandeh, Amir H. Gandomi
    Applied Soft Computing Journal, 2017
  • Feature Selection with β-Hill Climbing Search for Text Clustering Application
    Laith Mohammad Abualigah, Ahamad Tajudin Khader, Mohammed Azmi Al-Betar, Zaid Abdi Alkareem Alyasseri, Osama Ahmad Alomari, Essam Said Hanandeh
    Proceedings 2017 Palestinian International Conference on Information and Communication Technology Picict 2017, 2017
  • Unsupervised text feature selection technique based on particle swarm optimization algorithm for improving the text clustering
    Laith Mohammad Abualigah, Ahamad Tajudin Khader, Mohammed Azmi AlBetar, Essam Said Hanandeh
    Compse 2016 1st Eai International Conference on Computer Science and Engineering, 2017
  • A new hybridization strategy for krill herd algorithm and harmony search algorithm applied to improve the data clustering
    Compse 2016 1st Eai International Conference on Computer Science and Engineering, 2017
  • A novel botnet detection system for P2P networks
    Atef Ahmed Obeidat, Majd Mahmoud Al-Kofahi, Mohammad Jazi Bawaneh, Essam Said Hanandeh
    Journal of Computer Science, 2017
  • Effective information retrieval method based on matching adaptive genetic algorithm
    Journal of Theoretical and Applied Information Technology, 2015
  • Evaluating and enhancing e-learning in Jordan
    Khaled Maabreh, Essam Hanandeh
    International Journal of Technology Enhanced Learning, 2015
  • Genetic algorithm with neighbor solution approach for traveling salesman problem
    Neural Network World, 2007
  • The execution of strategic information system planning in industrial potash plant
    Proceedings of the 2005 International Conference on Information and Knowledge Engineering IKE 05, 2005

RECENT SCHOLAR PUBLICATIONS

  • Quantum Computing with Artificial Intelligence: A Paradigm Shift in Intelligent Systems
    E Hanandeh, S Zang, J Kang, G Hu, S Sighm, A Smerat, AE Ezugwu, ...
    Mastering the Minds of Machines, 156-163 , 2025
    2025
    Citations: 1
  • 12 Backpropagation Descent: Network Optimization Key Techniques and Gradient for Neural
    E Hanandeh, ZB Laa, H Jia, A Al-Fugara, P Zhang, Z Liu, I Al-Shourbaji, ...
    Mastering the Minds of Machines, 91 , 2025
    2025
  • Convolutional Neural Networks: The Power Behind Image Recognition
    MH Almomani, E Hanandeh, CB Şahin, P Zhang, Z Zuong, A Nasayreh, ...
    Mastering the Minds of Machines, 50-56 , 2025
    2025
    Citations: 1
  • Optimizing Deep Learning Scalability: 18 HarnessingCloud Distributed Systems and
    E Hanandeh, HV Thanh, F Gul, MA Wahab, I Al-Shourbaji, N Khodadadi, ...
    Mastering the Minds of Machines 3, 142 , 2025
    2025
  • Optimizing Deep Learning Scalability: Harnessing Distributed Systems and Cloud Computing for Next-Generation AI
    E Hanandeh, HV Thanh, F Gul, MA Wahab, I Al-Shourbaji, N Khodadadi, ...
    Mastering the Minds of Machines, 142-148 , 2025
    2025
    Citations: 1
  • Ethical Frontiers in Artificial Intelligence: Addressing the Challenges of Machine Intelligence
    E Hanandeh, F Al-Saqqar, MS El-Bashir, RA Zitar, HV Thanh, MA Wahab, ...
    Mastering the Minds of Machines, 108-116 , 2025
    2025
    Citations: 1
  • Modified aquila optimizer feature selection approach and support vector machine classifier for intrusion detection system
    L Abualigah, SH Ahmed, MH Almomani, RA Zitar, AR Alsoud, B Abuhaija, ...
    Multimedia Tools and Applications 83 (21), 59887-59913 , 2024
    2024
    Citations: 55
  • Spider monkey optimizations: application review and results
    AE Ezugwu¹¹, ES Hanandeh, H Jia
    Metaheuristic Optimization Algorithms: Optimizers, Analysis, and … , 2024
    2024
  • A Survey of cuckoo search algorithm: optimizer and new applications
    L Abualigah, A Ababneh, AM Ikotun, RA Zitar, AR Alsoud, N Khodadadi, ...
    Metaheuristic optimization algorithms, 45-57 , 2024
    2024
    Citations: 18
  • Spider monkey optimizations: application review and results
    L Abualigah, SM Alshatti, AM Ikotun, RA Zitar, AR Alsoud, N Khodadadi, ...
    Metaheuristic optimization algorithms, 117-131 , 2024
    2024
    Citations: 12
  • Marine predator’s algorithm: a survey of recent applications
    L Abualigah, S Odah, AM Ikotun, AR Alsoud, A Forestiero, AE Ezugwu, ...
    Metaheuristic optimization algorithms, 133-145 , 2024
    2024
    Citations: 9
  • Aquila optimizer: review, results and applications
    L Abualigah, B Sbenaty, AM Ikotun, RA Zitar, AR Alsoud, N Khodadadi, ...
    Metaheuristic optimization algorithms, 89-103 , 2024
    2024
    Citations: 10
  • Whale optimization algorithm: analysis and full survey
    L Abualigah, R Abualigah, AM Ikotun, RA Zitar, AR Alsoud, N Khodadadi, ...
    Metaheuristic optimization algorithms, 105-115 , 2024
    2024
    Citations: 39
  • A review of krill herd algorithm: optimization and its applications
    L Abualigah, M Al-Zyod, AM Ikotun, M Shehab, M Otair, AE Ezugwu, ...
    Metaheuristic Optimization Algorithms, 231-239 , 2024
    2024
    Citations: 15
  • Arithmetic optimization algorithm: a review and analysis
    L Abualigah, A Abusaleem, AM Ikotun, RA Zitar, AR Alsoud, N Khodadadi, ...
    Metaheuristic optimization algorithms, 73-87 , 2024
    2024
    Citations: 26
  • Salp swarm algorithm: survey, analysis, and new applications
    L Abualigah, W Hawamdeh, RA Zitar, S AlZu’bi, A Mughaid, ...
    Metaheuristic optimization algorithms, 241-258 , 2024
    2024
    Citations: 23
  • Teaching–learning-based optimization algorithm: analysis study and its application
    L Abualigah, E Abu-Dalhoum, AM Ikotun, RA Zitar, AR Alsoud, ...
    Metaheuristic Optimization Algorithms, 59-71 , 2024
    2024
    Citations: 8
  • Original Research Article An investigation to identify the factors that cause failure in English essay, precis, and composition papers in CSS exams
    K Gul, W Shahzad, A Raza, E Hanandeh, RA Zitar, K Aldiabat, R Shboul, ...
    Journal of Autonomous Intelligence 7 (5) , 2024
    2024
    Citations: 2
  • Issues in Electronic Distance Learning
    A Awad, E Hanandeh, H Nasseif
    Artificial Intelligence, Internet of Things, and Society 5.0, 417-429 , 2023
    2023
  • Arabic Text Categorization Algorithm Using Vector Space Model
    E Hanandeh, M Shajahan
    Artificial Intelligence, Internet of Things, and Society 5.0, 41-50 , 2023
    2023

MOST CITED SCHOLAR PUBLICATIONS

  • A new feature selection method to improve the document clustering using particle swarm optimization algorithm
    LM Abualigah, AT Khader, ES Hanandeh
    Journal of Computational Science 25, 456-466 , 2018
    2018
    Citations: 594
  • Hybrid clustering analysis using improved krill herd algorithm: LM Abualigah et al.
    LM Abualigah, AT Khader, ES Hanandeh
    Applied Intelligence 48 (11), 4047-4071 , 2018
    2018
    Citations: 374
  • A combination of objective functions and hybrid krill herd algorithm for text document clustering analysis
    LM Abualigah, AT Khader, ES Hanandeh
    Engineering Applications of Artificial Intelligence 73, 111-125 , 2018
    2018
    Citations: 304
  • A novel hybridization strategy for krill herd algorithm applied to clustering techniques
    AG Laith Abualigaha, Ahamad Khadera, Essam Hanandehb
    Applied Soft Computing 60 (Issue 1), 423-435 , 2017
    2017
    Citations: 290
  • Applying genetic algorithms to information retrieval using vector space model
    LMQ Abualigah, ES Hanandeh
    International Journal of Computer Science, Engineering and Applications … , 2015
    2015
    Citations: 256
  • Revolutionizing sustainable supply chain management: A review of metaheuristics
    L Abualigah, ES Hanandeh, RA Zitar, CL Thanh, S Khatir, AH Gandomi
    Engineering Applications of Artificial Intelligence 126, 106839 , 2023
    2023
    Citations: 126
  • Improved reptile search algorithm by salp swarm algorithm for medical image segmentation
    L Abualigah, M Habash, ES Hanandeh, AMA Hussein, MA Shinwan, ...
    Journal of bionic engineering 20 (4), 1766-1790 , 2023
    2023
    Citations: 85
  • A hybrid strategy for krill herd algorithm with harmony search algorithm to improve the data clustering
    LM Abualigah, AT Khader, ES Hanandeh
    Intelligent Decision Technologies 12 (1), 3-14 , 2018
    2018
    Citations: 61
  • Modified aquila optimizer feature selection approach and support vector machine classifier for intrusion detection system
    L Abualigah, SH Ahmed, MH Almomani, RA Zitar, AR Alsoud, B Abuhaija, ...
    Multimedia Tools and Applications 83 (21), 59887-59913 , 2024
    2024
    Citations: 55
  • Feature selection with β-hill climbing search for text clustering application
    LM Abualigah, AT Khader, MA Al-Betar, ZAA Alyasseri, OA Alomari, ...
    2017 Palestinian International Conference on Information and Communication … , 2017
    2017
    Citations: 53
  • A novel weighting scheme applied to improve the text document clustering techniques
    LM Abualigah, AT Khader, ES Hanandeh
    Innovative Computing, Optimization and Its Applications: Modelling and … , 2017
    2017
    Citations: 48
  • Whale optimization algorithm: analysis and full survey
    L Abualigah, R Abualigah, AM Ikotun, RA Zitar, AR Alsoud, N Khodadadi, ...
    Metaheuristic optimization algorithms, 105-115 , 2024
    2024
    Citations: 39
  • Modified krill herd algorithm for global numerical optimization problems
    LM Abualigah, AT Khader, ES Hanandeh
    Advances in nature-inspired computing and applications, 205-221 , 2018
    2018
    Citations: 39
  • A novel methodology for human kinematics motion detection based on smartphones sensor data using artificial intelligence
    A Raza, MR Al Nasar, ES Hanandeh, RA Zitar, AY Nasereddin, ...
    Technologies 11 (2), 55 , 2023
    2023
    Citations: 37
  • Extractive Arabic text summarization-graph-based approach
    YA AL-Khassawneh, ES Hanandeh
    Electronics 12 (2), 437 , 2023
    2023
    Citations: 35
  • Unsupervised text feature selection technique based on particle swarm optimization algorithm for improving the text clustering
    LM Abualigah, AT Khader, MA AlBetar, ES Hanandeh
    EAI international conference on computer science and engineering , 2017
    2017
    Citations: 34
  • A new hybridization strategy for krill herd algorithm and harmony search algorithm applied to improve the data clustering
    LM Abualigah, AT Khader, MA AlBetar, ES Hanandeh
    1st EAI International Conference on computer science and engineering, 54 , 2016
    2016
    Citations: 34
  • Arithmetic optimization algorithm: a review and analysis
    L Abualigah, A Abusaleem, AM Ikotun, RA Zitar, AR Alsoud, N Khodadadi, ...
    Metaheuristic optimization algorithms, 73-87 , 2024
    2024
    Citations: 26
  • Salp swarm algorithm: survey, analysis, and new applications
    L Abualigah, W Hawamdeh, RA Zitar, S AlZu’bi, A Mughaid, ...
    Metaheuristic optimization algorithms, 241-258 , 2024
    2024
    Citations: 23
  • Hybrid harmony search algorithm to solve the feature selection for data mining applications
    L Mohammad Abualigah, M Al‐diabat, M Al Shinwan, K Dhou, B Alsalibi, ...
    Recent advances in hybrid metaheuristics for data clustering, 19-37 , 2020
    2020
    Citations: 23