A hybrid genetic algorithm and linear regression for prediction of NOx emission in power generation plant

• Main Authors: Bunyamin M.A., Yap K.S., Aziz N.L.A.A., Tiong S.K., Wong S.Y., Kamal M.F.
• 其他作者: 55812855600
• 格式: Conference paper
• 出版: Institute of Physics Publishing 2023
• 主题: Estimation; Gas emissions; Genetic algorithms; Nitrogen oxides; Optimal systems; Accurate prediction; Emission estimation; Explanatory variables; Hybrid genetic algorithms; Model parameters; Optimal solutions; Power generation plants; Prediction errors; comparative study; electricity generation; error analysis; estimation method; genetic algorithm; industrial emission; numerical model; optimization; parameterization; regression analysis; Forecasting

This paper presents a new approach of gas emission estimation in power generation plant using a hybrid Genetic Algorithm (GA) and Linear Regression (LR) (denoted as GA-LR). The LR is one of the approaches that model the relationship between an output dependant variable, y, with one or more explanato...