Artificial neural network-based cooling capacity estimation of various radiator configurations for power transformers operated in ONAN mode

Keyphrases

• Neural Network 100%
• Artificial Neural Network 100%
• Capacity Estimation 100%
• Power Transformer 100%
• Cooling Capacity 100%
• Radiator 100%
• Mean Squared Error 20%
• Design Parameters 20%
• Computational Fluid Dynamics 20%
• Electrical Energy 20%
• Thermal Energy 20%
• Mass Flow Rate 20%
• Machine Learning 20%
• Coefficient of Determination 20%
• Electrical Power Network 20%
• Low Voltage 20%
• Transformer Winding 20%
• Capacity Value 20%
• Margin of Deviation 20%
• Verification Study 20%
• Bayesian Regularization 20%
• Deviation Mean 20%
• Transformer Cores 20%
• Useful Elements 20%
• Air Mode 20%
• Effective Dissipation 20%
• Natural Modes 20%
• High-to-Low 20%
• Fin number 20%

Engineering

• Cooling Capacity 100%
• Artificial Neural Network 100%
• Mean-Squared-Error 33%
• Metrics 33%
• Computational Fluid Dynamics 33%
• Experimental Result 33%
• Electrical Energy 33%
• Mass Flowrate 33%
• Electrical Power 33%
• Natural Mode 33%
• Numerical Approach 33%
• Experimental Finding 33%
• Natural Oil 33%
• Design Parameter 33%
• Regularization Method 33%
• Learning System 33%
• Thermal Energy 33%

Material Science

• Computational Fluid Dynamics 100%