传感技术学报2024，Vol.37Issue(2)：256-267,12.DOI:10.3969/j.issn.1004-1699.2024.02.010
基于改进樽海鞘群算法的含瓦斯煤破裂过程信号特征识别
Identification of Signal Characteristics of Gas Bearing Coal Fracture Process Based on Improved Salp Swarm Algorithm
摘要
Abstract
Aiming at the shortcomings of salp swarm algorithms,such as insufficient calculation accuracy and ease to fall into local opti-mum,an improved salp swarm algorithm with multi-strategy integtation is proposed.In the initialization stage,the linear congruence ran-dom generators is introduced.The wild horse optimization algorithm is used for improving the leader's position,and the following mecha-nism of salp swarm algorithm is improved by using golden jackal optimization.Through the comparison of test function optimization ex-periments,it is proved that the improved salp swarm algorithm based on multi-strategy integration has a significant improvement in ro-bustness and stability compared with other intelligent algorithms.The improved salp swarm algorithm with multi-strategy integration is applied to the signal feature identification of the gas bearing coal fracture process.The experimental results show that the proposed sig-nal feature identification model of the gas bearing coal fracture process has a better performance,with an accuracy rate of 93.33％.Com-pared with other identification models,the identification rate is higher.关键词
含瓦斯煤破裂/智能优化算法/樽海鞘群算法/多策略融合/信号特征识别Key words
coal containing gas fracture/intelligent optimization algorithm/salp swarm algorithm/multi-strategy fusion/identification of signal characteristics分类
计算机与自动化引用本文复制引用
付华,管智峰,刘尚霖,刘昊,陈子林..基于改进樽海鞘群算法的含瓦斯煤破裂过程信号特征识别[J].传感技术学报,2024,37(2):256-267,12.基金项目
国家自然科学基金项目(51974151 （）
71771111) （）
辽宁省高等学校国(境)外培养项目(2019GJWZD002) （境）
辽宁省高等学校创新团队项目(LT2019007) （LT2019007）
辽宁省教育厅科技项目(LJ2019QL015) （LJ2019QL015）
