An Alternate Iterative Differential Evolution Algorithm for Parameter Identification of Chaotic Systems

Algorithm 1

The procedure of AIDE.

()    Initialize the population X using opposition-based learning

()    Let represent the population composed of the best one of each individual () in

   history

()    Set //Iterative variable

()    while    do

()    for   to   do

()     Choose the best individual from the current population, and let best represent its index

()     Generate two random integer numbers

()     if    then

()      Perform differential mutation according to (4)

()   Set

()  else

()   Perform differential mutation according to (8)

()   Set

()  end if

()  Do bound constraints handling according to (7)

()  Generate trial vector according to (5) and compute its objective value

()  if   is better than   then

()   Replace with immediately

()  else

()   Substitute the worst individual in current population with immediately and is the index of the worst

        individual

()   if   is better than   then

()     and

()   end if

()  end if

()  if    then

()   Set and ; //Big evolution

()  else

()   Set and ; //Small evolution

()  end if

() end for

() //Disaster mutation

() if    then

()  Sort the population according to objective value order by ascent and replace the first individuals with

    randomly generated individuals

()  Set

() end if

() Record the best solution found so far

() if  the best solution is updated  then

()  Set

() else

()  Set

() end if

() Set

() end while