Interpretable Machine Learning for Predicting Freeze-Thaw-Induced Sandstone Strength Degradation: Physical Mechanisms and Engineering Validation

This publication has 78 references indexed in Scilit:

• AI-powered GUI for prediction of axial compression capacity in concrete-filled steel tube columns
  Neural Computing and Applications, 2024
• Image‐Based Biological Heart Age Estimation Reveals Differential Aging Patterns Across Cardiac Chambers
  Journal of Magnetic Resonance Imaging, 2023
• Hyperparameter optimization: Foundations, algorithms, best practices, and open challenges
  WIREs Data Mining and Knowledge Discovery, 2023
• Study on a Damage Model and Uniaxial Compression Simulation Method of Frozen–Thawed Rock
  Rock Mechanics and Rock Engineering, 2021
• Prediction of cement-based mortars compressive strength using machine learning techniques
  Neural Computing and Applications, 2021
• Improved Levenberg–Marquardt backpropagation neural network by particle swarm and whale optimization algorithms to predict the deflection of RC beams
  Engineering with Computers, 2021
• Mechanical Properties of Acid-corroded Sandstone Under Uniaxial Compression
  Rock Mechanics and Rock Engineering, 2020
• A comparative study of ANN and ANFIS models for the prediction of cement-based mortar materials compressive strength
  Neural Computing and Applications, 2020
• Developing GEP tree-based, neuro-swarm, and whale optimization models for evaluation of bearing capacity of concrete-filled steel tube columns
  Engineering with Computers, 2019
• Ridge regression
  WIREs Computational Statistics, 2009