摘要
随着人工智能技术的快速发展,智能算法在声呐目标识别领域的应用逐渐成为研究热点。概述神经网络、支持向量机、深度学习等智能算法的基本原理及其在声呐目标识别中的应用优势。详细讨论数据预处理与特征提取策略、模型选择与训练策略、识别性能评估与优化策略,为声呐目标识别的实际应用提供全面指导。对于实时性与健壮性对算法选择的影响,提出了针对不同任务特性的算法选择策略。基于智能算法的应用实践,提出了融合与创新的发展建议,以期推动声呐技术的进一步发展。
With the rapid development of artificial intelligence technology,the application of intelligent algorithms in the field of sonar target recognition has gradually become a research hotspot.This paper outlines the basic principles of intelligent algorithms such as neural networks,support vector machines,and deep learning,as well as their application advantages in sonar target recognition.It discusses in detail the strategies for data preprocessing and feature extraction,model selection and training,as well as evaluation and optimization of recognition performance,providing comprehensive guidance for the practical application of sonar target recognition.The paper also proposes algorithm selection strategies tailored to different task characteristics,considering the impact of real-time performance and robustness on algorithm selection.Based on the practical application of intelligent algorithms,it further suggests development recommendations for integration and innovation,aiming to promote the further advancement of sonar technology.
作者
张钰竹
ZHANG Yuzhu(No.710 R&D Institute,CSSC,Yichang 443003,China;Qingjiang Innovation Center,Wuhan 430076,China)
出处
《电声技术》
2024年第9期53-56,共4页
Audio Engineering
关键词
智能算法
声呐目标识别
神经网络
支持向量机
深度学习
intelligent algorithm
sonar target recognition
neural network
support vector machine
deep learning
