Back propagation neural network based on artificial bee colony algorithm
Feihu Jin, Guang Shu · 2012
The artificial bee colony algorithm is a novel simulated evolutionary algorithm. The artificial bee colony algorithm has positive feedback, distributed computation and a constructive greedy heuristic convergence. Back propagation is a kind of feed forward neural network widely used in many areas, but it has some shortcomings, such as low precision solutions, slow search speed and easy convergence to the local minimum. The combination of artificial bee colony algorithm and back propagation neural network is adopted so that a nonlinear model can be identified and an inverted pendulum can be controlled. Simulation results show that the extensive mapping ability of neural network and the rapid global convergence of artificial bee colony algorithm can be obtained by combining artificial bee colony algorithm and neural network.