Machine Learning-Based Sine-Cosine Algorithm for Wastewater Quality Assessment Using Activated Carbon
Algorithm 3
VELM-SCA.
Input: sample of training dataset , with label of
is the water quality indicator of wastewater plant ; is the total number of organic materials in the wastewater at ; is the crossover probability and its mutation.
Output: prediction of carbon in the wastewater plant.
Step 1: randomly select the water quality indicator parameter
Step 2: evaluate fitness value of using Equation (2).
Step 3: choose the next parameter of water quality indicator . Crossover and mutation on are calculated.
Step 4: using Algorithm 2, determine the best fitness .
Step 5: update the best solution out of all water quality indicator parameter value.
Step 6: update the position of adsorption of carbon in the wastewater plant by using
