Application of machine learning models to investigate the performance of stainless steel type 904 with agricultural waste

Engineering

• Fuzzy Inference System 100%
• Stainless Steel 100%
• Corrosion Rate 40%
• Root Mean Square Error 40%
• Absolute Deviation 40%
• Inhibition 40%
• Artificial Neural Network 40%
• Exposure Time 20%
• Hidden Layer 20%
• Machine Learning Algorithm 20%
• Activation Function 20%

Chemical Engineering

• Learning System 100%
• Fuzzy System 100%
• Neural Network 60%

Keyphrases

• Fast Tool 20%
• Exposure Temperature 20%
• Single Hidden Layer Neural Network 20%
• Inhibition Performance Prediction 20%