Soft sensor modeling of AlCl3•6H2O content based on powell-BP
CAR'10 Proceedings of the 2nd international Asia conference on Informatics in control, automation and robotics - Volume 2
Locating seismic-sense stations through genetic algorithm: genetic algorithms
Proceedings of the 13th annual conference on Genetic and evolutionary computation
| Hi-index | 0.00 |
By integrating the global searching advantage of Genetic Algorithm (GA) and the local searching ability of BP Artificial Neural Network (BP ANN), this paper proposes a new model of BP ANN based on GA (called GA-BP ANN). Firstly, it applies GA to optimize the initial interconnecting weights and thresholds of BP ANN. Then, it utilizes the BP algorithm to train the neural network more accurately. This method can speed up the convergence and avoid local minimum of BP ANN. The experiments of earthquake prediction with general BP ANN and optimized GA-BP ANN are respectively conducted as a case study. The results show that the BP ANN optimized with GA can not only get better network configurations, but also improve the efficiency, precision and stability of earthquake prediction.