计算机应用与软件2026，Vol.43Issue(5)：156-163,8.DOI:10.3969/j.issn.1000-386x.2026.05.021
基于数据融合的棉花仓库环境监测
ENVIRONMENTAL MONITORING OF COTTON WAREHOUSES BASED ON DATA FUSION
摘要
Abstract
A high-precision fusion strategy for layered wireless sensor networks is proposed to address the problems of large errors in collected data and poor monitoring real-time and accuracy of wireless sensor networks in cotton warehouses.In the bottom layer,the collected data were denoised by CEEMDAN joint wavelet thresholding.In the middle layer,the FASTDTW algorithm was used to optimize the fuzzy support function for the weighted fusion of similar sensor data.In the top layer,the improved pelican optimization algorithm was used to optimize the deep confidence neural network for the feature fusion of dissimilar sensor data.The experimental results show that the fusion strategy has strong anti-interference ability,short fusion time,and enriches the fusible feature categories while ensuring the fusion ac-curacy.关键词
无线传感器网络/仓库环境监测/数据融合/快速动态规整算法/改进鹈鹕优化算法Key words
Wireless sensor networks/Warehouse environmental monitoring/Data fusion/FASTDTW/IPOA分类
信息技术与安全科学引用本文复制引用
毛同一,南新元..基于数据融合的棉花仓库环境监测[J].计算机应用与软件,2026,43(5):156-163,8.基金项目
国家自然科学基金项目(52065064,62263031). （52065064,62263031）
