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2020 – today
- 2025
[j11]Rawan Ghnemat, Nailah Al-Madi, Mohammad Awad:
An intelligent approach for autism spectrum disorder diagnosis and rehabilitation features identification. Neural Comput. Appl. 37(4): 2557-2580 (2025)- 2024
- [j10]May Alsaidi, Nadim Obeid, Nailah Al-Madi, Hazem Hiary
, Ibrahim Aljarah:
A Convolutional Deep Neural Network Approach to Predict Autism Spectrum Disorder Based on Eye-Tracking Scan Paths. Inf. 15(3): 133 (2024) - [j9]Shrouq Al-Fuqaha'a, Nailah Al-Madi, Bassam Hammo:
A robust classification approach to enhance clinic identification from Arabic health text. Neural Comput. Appl. 36(13): 7161-7185 (2024) - 2023
- [j8]Bilal Al-Ahmad, Nailah Al-Madi, Abdullah Alzaqebah, Rami S. Alkhawaldeh, Khaled Aldebei, Md Faisal Kabir, Ismail Al-Taharwa, Mua'ad Abu-Faraj, Ibrahim Aljarah:
Meta-Heuristic Guided Feature Optimization for Enhanced Authorship Attribution in Java Source Code. IEEE Access 11: 141657-141673 (2023) - 2020
- [j7]Ibrahim Aljarah, Maria Habib, Hossam Faris, Nailah Al-Madi, Ali Asghar Heidari, Majdi M. Mafarja, Mohamed E. Abd Elaziz, Seyedali Mirjalili:
A dynamic locality multi-objective salp swarm algorithm for feature selection. Comput. Ind. Eng. 147: 106628 (2020) - [j6]Nazeeh Ghatasheh, Hossam Faris, Ruba Abukhurma, Pedro A. Castillo, Nailah Al-Madi, Antonio Miguel Mora, Ala' M. Al-Zoubi, Ahmad Basheer Hassanat:
Cost-sensitive ensemble methods for bankruptcy prediction in a highly imbalanced data distribution: a real case from the Spanish market. Prog. Artif. Intell. 9(4): 361-375 (2020) - [c8]Othman Istaiteh, Tala Owais, Nailah Al-Madi, Saleh Abu-Soud:
Machine Learning Approaches for COVID-19 Forecasting. IDSTA 2020: 50-57 - [c7]Eman Al Nagi, Nailah Al-Madi:
Predicting Students Performance in Online Courses using Classification Techniques. IDSTA 2020: 58-65
2010 – 2019
- 2019
- [j5]Ibrahim Aljarah, Hossam Faris, Seyedali Mirjalili, Nailah Al-Madi, Alaa F. Sheta, Majdi M. Mafarja:
Evolving neural networks using bird swarm algorithm for data classification and regression applications. Clust. Comput. 22(4): 1317-1345 (2019) - [j4]Nailah Al-Madi, Hossam Faris, Seyedali Mirjalili:
Binary multi-verse optimization algorithm for global optimization and discrete problems. Int. J. Mach. Learn. Cybern. 10(12): 3445-3465 (2019) - 2018
- [j3]Ibrahim Aljarah, Hossam Faris, Seyedali Mirjalili, Nailah Al-Madi:
Training radial basis function networks using biogeography-based optimizer. Neural Comput. Appl. 29(7): 529-553 (2018) - [c6]Amaal R. Al Shorman, Hossam Faris, Pedro A. Castillo, Juan Julián Merelo Guervós, Nailah Al-Madi:
The Influence of Input Data Standardization Methods on the Prediction Accuracy of Genetic Programming Generated Classifiers. IJCCI 2018: 79-85 - 2016
- [j2]Nailah Al-Madi:
Mike Preuss: Multimodal optimization by means of evolutionary algorithms - Springer, 2015, 175 pp, ISBN: 978-3-319-07407-8. Genet. Program. Evolvable Mach. 17(3): 315-316 (2016) - [j1]Hossam Faris, Ibrahim Aljarah, Nailah Al-Madi, Seyedali Mirjalili:
Optimizing the Learning Process of Feedforward Neural Networks Using Lightning Search Algorithm. Int. J. Artif. Intell. Tools 25(6): 1650033:1-1650033:32 (2016) - 2014
- [c5]Nailah Al-Madi, Ibrahim Aljarah, Simone A. Ludwig:
Parallel glowworm swarm optimization clustering algorithm based on MapReduce. SIS 2014: 189-196 - 2013
- [c4]Nailah Al-Madi, Simone A. Ludwig:
Improving genetic programming classification for binary and multiclass datasets. CIDM 2013: 166-173 - [c3]Nailah Al-Madi, Simone A. Ludwig:
Segment-based genetic programming. GECCO (Companion) 2013: 133-134 - [c2]Nailah Al-Madi, Simone A. Ludwig:
Scaling Genetic Programming for data classification using MapReduce methodology. NaBIC 2013: 132-139 - 2012
- [c1]Nailah Al-Madi, Simone A. Ludwig:
Adaptive genetic programming applied to classification in data mining. NaBIC 2012: 79-85
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