Mohammed Falah Mohammed

11 papers Journal 10Unranked 1
YearRankTypeTitle / Venue / Authors
2024 J jnl
A flexible enhanced fuzzy min-max neural network for pattern classification.
Expert Syst. Appl.
Essam Alhroob, Mohammed Falah Mohammed, Osama Nayel Al Sayaydeh, Fadhl Hujainah, Ngahzaifa Ab Ghani, Chee Peng Lim
2022 J jnl
Investigation of contraction process issue in fuzzy min-max models.
Int. J. Data Min. Model. Manag.
Essam Alhroob, Mohammed Falah Mohammed, Fadhl Hujainah, Osama Nayel Al Sayaydeh, Ngahzaifa Ab Ghani
2020 J jnl
A Refined Fuzzy Min-Max Neural Network With New Learning Procedures for Pattern Classification.
IEEE Trans. Fuzzy Syst.
Osama Nayel Al Sayaydeh, Mohammed Falah Mohammed, Essam Alhroob, Hai Tao, Chee Peng Lim
2019 J jnl
A Critical Review on Selected Fuzzy Min-Max Neural Networks and Their Significance and Challenges in Pattern Classification.
IEEE Access
Essam Alhroob, Mohammed Falah Mohammed, Chee Peng Lim, Hai Tao
2019 — conf
Analysis on Misclassification in Existing Contraction of Fuzzy Min-Max Models.
IRICT
Essam Alhroob, Mohammed Falah Mohammed, Osama Nayel Al Sayaydeh, Fadhl Hujainah, Ngahzaifa Ab Ghani
2019 J jnl
Survey of Fuzzy Min-Max Neural Network for Pattern Classification Variants and Applications.
IEEE Trans. Fuzzy Syst.
Osama Nayel Al Sayaydeh, Mohammed Falah Mohammed, Chee Peng Lim
2018 J jnl
SAIRF: A similarity approach for attack intention recognition using fuzzy min-max neural network.
J. Comput. Sci.
Abdulghani Ali Ahmed, Mohammed Falah Mohammed
2017 J jnl
A new hyperbox selection rule and a pruning strategy for the enhanced fuzzy min-max neural network.
Neural Networks
Mohammed Falah Mohammed, Chee Peng Lim
2017 J jnl
Improving the Fuzzy Min-Max neural network with a K-nearest hyperbox expansion rule for pattern classification.
Appl. Soft Comput.
Mohammed Falah Mohammed, Chee Peng Lim
2015 J jnl
An Enhanced Fuzzy Min-Max Neural Network for Pattern Classification.
IEEE Trans. Neural Networks Learn. Syst.
Mohammed Falah Mohammed, Chee Peng Lim
2014 J jnl
A novel trust measurement method based on certified belief in strength for a multi-agent classifier system.
Neural Comput. Appl.
Mohammed Falah Mohammed, Chee Peng Lim, Anas Quteishat