航空兵器2025，Vol.32Issue(2)：128-136,9.DOI:10.12132/ISSN.1673-5048.2024.0140
基于改进卷积神经网络的机场跑道封锁效能评估
Evaluation of Airport Runway Blockade Effectiveness Based on Improved Convolutional Neural Network
摘要
Abstract
In response to the inefficiency and inability to utilize image data inherent in traditional airport runway blockade effectiveness assessment methods,this paper presents an improved convolutional neural network algorithm for assessing the blockade effectiveness of airport runways.A nonlinear model is established between the damage data of the airport runway and the success of blockade,avoiding the excessive time consumption caused by direct iteration.The size and number of convolutional kernels are modified according to the characteristics of the runway damage images,and batch normalization layers and Mish activation functions are introduced to address the issue of gradient disappea-rance during training.Simulation results demonstrate that the algorithm can effectively determine whether the runway is successfully blocked and calculate the blockade probability for a set of aiming points,and it has a significant advantage in recognition speed compared to traditional algorithms.关键词
机场跑道/封锁效能评估/封锁概率/跑道毁伤/卷积神经网络Key words
airport runway/blockade effectiveness assessment/blockade probability/runway damage/convolu-tional neural network分类
武器工业引用本文复制引用
操龙平,陈谋,周同乐..基于改进卷积神经网络的机场跑道封锁效能评估[J].航空兵器,2025,32(2):128-136,9.基金项目
国家自然科学基金青年科学基金项目(62203217) （62203217）
江苏省基础研究计划自然科学基金青年基金项目(BK20220885) （BK20220885）
天元实验室基金项目(24-JSKY-ZZKT-29) （24-JSKY-ZZKT-29）
