M. Z. Naser
Orcid: 0000-0003-1350-3654
According to our database1,
M. Z. Naser
authored at least 34 papers
between 2019 and 2025.
Collaborative distances:
Collaborative distances:
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Bibliography
2025
SPINEX-anomaly: similarity-based predictions with explainable neighbors exploration for anomaly and outlier detection.
J. Big Data, December, 2025
SPINEX-clustering: similarity-based predictions with explainable neighbors exploration for clustering problems.
Clust. Comput., October, 2025
The Engineer's Dilemma: A Review of Establishing a Legal Framework for Integrating Machine Learning in Construction by Navigating Precedents and Industry Expectations.
CoRR, July, 2025
Neural Comput. Appl., June, 2025
SPINEX-symbolic regression: similarity-based symbolic regression with explainable neighbors exploration.
J. Supercomput., May, 2025
A Look into How Machine Learning is Reshaping Engineering Models: the Rise of Analysis Paralysis, Optimal yet Infeasible Solutions, and the Inevitable Rashomon Paradox.
CoRR, January, 2025
A Guide to Machine Learning Epistemic Ignorance, Hidden Paradoxes, and Other Tensions.
WIREs Data. Mining. Knowl. Discov., 2025
Inf. Fusion, 2025
SPINEX-TimeSeries: Similarity-based predictions with explainable neighbors exploration for time series and forecasting problems.
Comput. Ind. Eng., 2025
2024
A review on machine learning and deep learning image-based plant disease classification for industrial farming systems.
J. Ind. Inf. Integr., March, 2024
Causality and causal inference for engineers: Beyond correlation, regression, prediction and artificial intelligence.
WIREs Data. Mining. Knowl. Discov., 2024
A deep learning approach to detect diseases in pomegranate fruits via hybrid optimal attention capsule network.
Ecol. Informatics, 2024
SPINEX_ Symbolic Regression: Similarity-based Symbolic Regression with Explainable Neighbors Exploration.
CoRR, 2024
SPINEX-TimeSeries: Similarity-based Predictions with Explainable Neighbors Exploration for Time Series and Forecasting Problems.
CoRR, 2024
SPINEX-Clustering: Similarity-based Predictions with Explainable Neighbors Exploration for Clustering Problems.
CoRR, 2024
SPINEX: Similarity-based Predictions with Explainable Neighbors Exploration for Anomaly and Outlier Detection.
CoRR, 2024
A Review of 315 Benchmark and Test Functions for Machine Learning Optimization Algorithms and Metaheuristics with Mathematical and Visual Descriptions.
CoRR, 2024
CoRR, 2024
Beyond development: Challenges in deploying machine learning models for structural engineering applications.
CoRR, 2024
Large Language Models in Fire Engineering: An Examination of Technical Questions Against Domain Knowledge.
CoRR, 2024
SPINEX: Similarity-based predictions with explainable neighbors exploration for regression and classification.
Appl. Soft Comput., 2024
2023
Machine learning and model driven bayesian uncertainty quantification in suspended nonstructural systems.
Reliab. Eng. Syst. Saf., September, 2023
SPINEX: Similarity-based Predictions and Explainable Neighbors Exploration for Regression and Classification Tasks in Machine Learning.
CoRR, 2023
Can AI Chatbots Pass the Fundamentals of Engineering (FE) and Principles and Practice of Engineering (PE) Structural Exams?
CoRR, 2023
2022
Simplifying Causality: A Brief Review of Philosophical Views and Definitions with Examples from Economics, Education, Medicine, Policy, Physics and Engineering.
CoRR, 2022
Causal Discovery and Causal Learning for Fire Resistance Evaluation: Incorporating Domain Knowledge.
CoRR, 2022
CoRR, 2022
2021
Can past failures help identify vulnerable bridges to extreme events? A biomimetical machine learning approach.
Eng. Comput., 2021
Demystifying Ten Big Ideas and Rules Every Fire Scientist & Engineer Should Know About Blackbox, Whitebox & Causal Artificial Intelligence.
CoRR, 2021
Explainable Machine Learning using Real, Synthetic and Augmented Fire Tests to Predict Fire Resistance and Spalling of RC Columns.
CoRR, 2021
RAI: Rapid, Autonomous and Intelligent machine learning approach to identify fire-vulnerable bridges.
Appl. Soft Comput., 2021
2020
Eng. Comput., 2020
2019
AI-based cognitive framework for evaluating response of concrete structures in extreme conditions.
Eng. Appl. Artif. Intell., 2019