排灌机械工程学报2026，Vol.44Issue(5)：511-520,10.DOI:10.3969/j.issn.1674-8530.25.0148
基于NARX神经网络的基质草莓腾发量超前预测
Lead-time prediction of evapotranspiration for substrate-grown strawberries based on NARX neural network
摘要
Abstract
To address the limitations of traditional models in achieving lead-time prediction of crop evapotranspiration(ET),the lead-time prediction capability and inherent limitations of the conventional NARX neural network for ETof substrate-grown strawberries were systematically investiga-ted.An enhanced NARX-based architecture incorporating a delay elimination technique for single-step-ahead prediction was proposed.The automated greenhouse system continuously monitored microclimate parameters,including greenhouse temperature,humidity,and photosynthetically active radiation(PAR),as well as gravimetric data.ETwas quantified using the water balance method.Data from the fruit expansion to maturity stage were selected,and the original time series was segmented into six time intervals(1,2,3,4,6,24 hours)for modeling and analysis.The results show that the NARX open-loop model only establishes a dynamic baseline mapping between microclimate parameters,ETat time t and ETat the same time step t,and therefore lacks lead-time prediction capability.The NARX closed-loop model exhibits pronounced initial-state sensitivity and error accumulation effects during multi-step forecasting.Furthermore,its dependence on future environmental inputs substantially amplifies predic-tion uncertainty.The prediction error exhibits a supralinear growth with extended time intervals,and the 1-hour step size(RMSE=3.31 g)best matches the dynamic drip irrigation demand for strawberries.The NARX single-step prediction model achieves robust forecasting with only 6 historical observations.During peak transpiration periods,it maintains stable errors of 5.2%±4.5%,outperfor-ming BP and TDNN neural network models of comparable parameter scale.Therefore,the NARX sin-gle-step-ahead prediction model can provide reliable technical support for intelligent irrigation of sub-strate-grown strawberries.关键词
草莓腾发量/NARX神经网络/时间序列预测/精准农业/温室水分管理Key words
strawberry evapotranspiration/NARX neural network/time-series forecasting/precision agriculture/greenhouse water management分类
农业科技引用本文复制引用
霍倩,朱立保,檀海斌,郑成海..基于NARX神经网络的基质草莓腾发量超前预测[J].排灌机械工程学报,2026,44(5):511-520,10.基金项目
河北省重点研发计划项目(22327211D) （22327211D）
