Z
Zainah Ibrahim
Researcher at University of Malaya
Publications - 150
Citations - 2962
Zainah Ibrahim is an academic researcher from University of Malaya. The author has contributed to research in topics: Damper & Finite element method. The author has an hindex of 24, co-authored 137 publications receiving 1914 citations. Previous affiliations of Zainah Ibrahim include Universiti Tun Hussein Onn Malaysia.
Papers
More filters
Journal ArticleDOI
Nondestructive test methods for concrete bridges: A review
TL;DR: NDT methods applicable to concrete bridges are reviewed in this paper, where a flow chart based on damage level along with NDT methods and potential remedial measures are proposed for periodic health monitoring of structures.
Journal ArticleDOI
Potential of adaptive neuro fuzzy inference system for evaluating the factors affecting steel-concrete composite beam's shear strength
Maryam Safa,Mahdi Shariati,Zainah Ibrahim,Ali Toghroli,Shahrizan Baharom,Norazman Mohamad Nor,Dalibor Petković +6 more
TL;DR: In this paper, the shear strength of steel-concrete composite beams was analyzed based on the respective variable parameters and the methodology used by ANFIS (Adaptive Neuro Fuzzy Inference System) was adopted for this purpose.
Journal ArticleDOI
Prediction of shear capacity of channel shear connectors using the ANFIS model
Nor Hafizah Ramli Sulong,Ali Toghroli,Mohammad Mohammadhassani,Mahdi Shariati,Meldi Suhatril,Zainah Ibrahim +5 more
TL;DR: The outcome shows that the use of ANFIS produces highly accurate, precise and satisfactory results as opposed to the classical linear regressions.
Journal ArticleDOI
Potential of soft computing approach for evaluating the factors affecting the capacity of steel–concrete composite beam
Ali Toghroli,Meldi Suhatril,Zainah Ibrahim,Maryam Safa,Mahdi Shariati,Shahaboddin Shamshirband +5 more
TL;DR: Estimation and prediction results of the ELM models were compared with genetic programming (GP) and artificial neural networks (ANNs) models and indicate that on the whole, the newflanged algorithm creates good generalization presentation.
Journal ArticleDOI
RETRACTED ARTICLE: Analysis of influential factors forpredicting the shear strength of a V-shaped angle shear connector in composite beamsusing an adaptive neuro-fuzzy technique
TL;DR: The results exhibited that the proposed shear connector (V-shaped angle) contained the potentiality to be used practically after several improvements, and might be the improvement of the testing process for different predictive models with more input variables that will improve the predictive power of the created models.