Application of Improved Particle-Swarm-Optimization Neural Network in Coalmine Safety Evaluation

4th International Conference on Applied Materials and Manufacturing Technology

材料科学;机械制造

Rongjun, H.E.^1 ; Yunhang, D.U.^2

ChongQing Vocational Institute of Engineering, ChongQing

402260, China^1

YunNan Vocational Institute of Energy Technology, Yunnan

655001, China^2

关键词: Coal mine safety evaluations;    Coal-mine safeties;    Comprehensive evaluation model;    Convergence speed;    Improved particle swarm optimization algorithms;    Improved particle swarms;    Optimal balance;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/423/1/012007/pdf
DOI  :  10.1088/1757-899X/423/1/012007

学科分类：材料科学（综合）

来源: IOP

【 摘 要 】

Based on the principle of improved particle-swarm-optimization neural network, a comprehensive evaluation model is established by taking into account the various indexes of coal mine safety evaluation. The method is based on neural networks, and uses improved particle-swarm-optimization to find the optimal balance weight, and improves the convergence speed and accuracy of the neural network. Practice has proved that the model has the ability of global optimization of the improved particle swarm optimization algorithm and the extensive mapping ability of the neural network. It has a strong prediction ability and provides an important way for coal mine safety evaluation.