A Hybrid Model Based on Ensemble Empirical Mode Decomposition and Fruit Fly Optimization Algorithm for Wind Speed Forecasting

Algorithm 1

FOA.

Objective:

Maxmize smell concentration

Output:

The best smell concentration (Smellbest)

Parameters:

Iteration number (Maxgen). Population size (sizepop). Location range (LR). Random fly direction and distance zone of fruit fly

(Smellbest)

()    / Initialization /

()    /Set Maxgen, sizepop /

()    /Initialization swarm location LR and fly range FR /

()    Iter = 0

()   _axis = rand (LR), _axis = rand (LR)

()    / Calculate initial smell concentration /

()    Smellbest = Function ( _axis, _axis).

()    Repeat

()    While  

() /Osphresis searching process. /

() /Given the random direction and distance for food searching of any individual fruit fly. /

() _axis + rand (FR), _axis + rand (FR)

() /Calculate the distance of food source to the initialization location. /

() .

() /Calculate the smell concentration judgment value. /

() .

() /Calculate the smell concentration./

()

() /Find out the fruit fly with maximal smell concentration among the swarm./

()

() / Vision searching process /

() If  bestSmell > Smellbest  then  Smellbest = bestSmell;

()  _axis = (bestIndex), _axis = (bestIndex)

()  Iter = Iter + 1

() Until  Iter = Maxgen