Optimized machine learning with hyperparameter tuning and response surface methodology for predicting tribological performance in bio‐composite materials

Documents similaires

• Integrating response surface methodology and machine learning for analyzing the unconventional machining properties of hybrid fiber‐reinforced composites
  par: V. Vinoth, et autres
  Publié: (2024)
• Assessment of mechanical, thermal, and sliding wear performance of chemically treated alumina‐filled biocomposites using machine learning and response surface methodology
  par: V. S. Shaisundaram, et autres
  Publié: (2025)
• Enhanced Mechanical, Dynamic Mechanical Analysis, Thermal, and Tribological Properties of Bio Composites Reinforced With Biosilica From Paddy Straw
  par: Saravanakumar Sengottaiyan
  Publié: (2025)
• Enhancing mechanical and tribological performance of hybrid composites: An experimental study utilizing response surface methodology and firefly algorithm
  par: Soumya Dash, et autres
  Publié: (2024)
• Effect of filling materials on the tribological performance of polytetrafluoroethylene in different wear modes
  par: Sinan Fidan, et autres
  Publié: (2024)