Application in support of preparatory tunnel with adaptive combining hierarchy genetic RBF neural network

Based on the investigation and statistics of the preparatory tunnel data in Chengchao Iron Mine, using the adjustable parameters adaptive genetic algorithm with combining hierarchical structure to optimize structure and solve parameters of the radial base function neural network(ACHG-RBF), the algorithm had trained and predicted the network and optimized the network topology. In addition, it has enhanced the network study performance as well, which can obtain a high precision and strong generalization capability. It has a higher value in application and dissemination.