Al-Biruni Earth Radius Optimization Based Algorithm for Improving Prediction of Hybrid Solar Desalination System

The performance of a hybrid solar desalination system is predicted in this work using an enhanced prediction method based on supervised machine-learning algorithm. A humidification–dehumidification (HDH) unit and single-stage flashing evaporation (SSF) make up the system. Al-Biruni Earth Radius (BER) Particle Swarm Optimization (PSO) algorithms serve as foundation for suggested Using experimental data, BER–PSO algorithm trained evaluated. cold fluid injected air volume flow rates were algorithms’ inputs, their outputs hot fluids’ outlet temperatures well pressure drop across heat exchanger. Both mass rate input fluids are regarded constants. results obtained show great ability proposed to identify nonlinear link between operating circumstances process responses. In addition, compared other analyzed models, it offers better statistical measures temperature values.