New technique to predict solar inverter temperature

An international research team has developed a novel approach for predicting inverter temperature through symbolic regression based on particle swarm optimization. A group of scientists from Colombia's Pontifical Bolivarian University has developed a novel temperature prediction method for PV inverters that utilizes symbolic regression (SR) based on particle swarm optimization (PSO) for prediction. SR is a machine learning technique that identifies mathematical expressions describing the relationship between input variables and output data; PSO is a bio-inspired optimization algorithm. "Proper ...

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