Machine learning-based prediction of wear behaviour of AZ31 hybrid composites reinforced with NbC and ZrC
T. Satish Kumar(Amrita Vishwa Vidyapeetham), Kanak Kalita(Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology), S. Shalini(PSG INSTITUTE OF TECHNOLOGY AND APPLIED RESEARCH), Jana Petrů(VSB - Technical University of Ostrava)
Cited by 5
Related Papers
A Comparative Study of Linear, Random Forest and AdaBoost Regressions for Modeling Non-Traditional Machining
|Processes|2021|172
Random Forest Regression-Based Machine Learning Model for Accurate Estimation of Fluid Flow in Curved Pipes
|Processes|2021|128
Machine Learning-Based Predictive Modelling of Biodiesel Production—A Comparative Perspective
|Energies|2021|109
Efficient Feature Selection Using Weighted Superposition Attraction Optimization Algorithm
|Applied Sciences|2023|106
A SWARA-CoCoSo-Based Approach for Spray Painting Robot Selection
|Informatica|2021|86