TRAINING A FEED -FORWARD N EURAL N ETWORK W ITH ARTIFICIAL BEE COLONY BASED BACK - PROPAGATION M ETHOD

Back-propagation algorithm is one of the most widely used and popul ar techniques to optimize the feed forward neural network training. Nature inspired meta -heuristic algorithms also provide derivative -free solution to optimize complex problem. Artificial bee colony algorithm is a nature inspired meta -heuristic algorithm, mimicking the foraging or food source searching behaviour of bees in a bee colony and this algorithm is implemented in several applications for an improved optimized outcome. The proposed method in this paper includes an improved artificial bee colony alg orithm based back-propagation neural network training method for fast and improved convergence rate of the hybrid neural network learning method. The result is analysed with the genetic algorithm based back -propagation method, and it is another hybridizedprocedure of its kind. Analysis is performed over standard data sets, reflecting the light of efficiency of proposed method in terms of convergence speed and rate.