Using Genetic Programming with Prior Formula Knowledge to Solve Symbolic Regression Problem

Algorithm 6

PFK-GP.

Input: data, PFKB, , , , , , , , interval

Output: (candidate formulas set)

()    (data, PFKB)

()     = CountSamePartF(, )

()    (, )

()    (, , , , )

()    while (bestFitness    threshold &&  )

()      = crossover()

()      = mutate()

()      = ParetoOptimise() // prevent the formula model too complex

()     _fitnees = EvaluatePopulation()

()  bestFitness, = Selectbest(, _fitness, ) // choose the best individuals and get the best fitness value from the individuals

()  if mod interval

()   (, , , )

()    = traditionalRandomIndividual()

()   

()  else

()    = traditionalRandomIndividual()

()   

()  end

()  ++

() end

() return