Computing air demand using the takagi-sugeno model for dam outlets

Engineering

• Fuzzy Inference System 100%
• Levenberg-Marquardt Algorithm 66%
• Feedforward 33%
• Root Mean Square Error 33%
• Performance Criterion 33%
• Data Point 33%
• Sutcliffe 33%
• Nonlinear Parameter 33%
• Physical Model 33%
• Least Square 33%
• Backpropagation 33%
• Learning Algorithm 33%
• Fuzzy Rules 33%
• Air Discharge 33%
• Square Estimate 33%

Keyphrases

• Air Demand 100%
• Levenberg-Marquardt Artificial Neural Network 66%
• Outlet Works 33%
• Relationship-based 33%
• Least Squares Estimate 33%
• Experimental Information 33%
• Subtractive Clustering 33%
• Fuzzy Rule-based Model 33%
• Nonlinear Parameter 33%
• Nash-Sutcliffe Efficiency 33%
• Hybrid Learning Algorithm 33%
• Air Discharge 33%
• Gate Opening 33%
• Embankment Dam 33%
• Simulation Performance 33%

Computer Science

• adaptive neuro-fuzzy inference system 100%
• Levenberg Marquardt 66%
• Neural Network 66%
• Least Squares Method 33%
• Physical Model 33%
• Backpropagation 33%
• Clustering Technique 33%
• Performance Model 33%
• Simulation Performance 33%
• Learning Algorithm 33%
• Square Estimate 33%
• Performance Criterion 33%
• Linear Parameter 33%