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

Algorithm 5

.

Input: , , , , , where, represents the number of individuals which are generated, and is the candidate

   function library)

Output: (population)

()

() for each in

()  add into

() end

()

() // add the elements of , and into the queue successively, , add into

() _temp = traditionalRandomIndividual(, )

() add _temp into

()

() _temp = traditionalRandomIndividual()

() add _temp into

() return