神经网络在作物需水量估算中的应用分析  

Application Analysis of Neural Networks in the Estimation of Crop Water Requirements

作　　者：马良翮 MA Lianghe

机构地区：[1]山西开放大学,太原030027

出　　处：《智慧农业导刊》2024年第9期9-12,共4页JOURNAL OF SMART AGRICULTURE

基　　金：山西开放大学2023年度校级课题(SXKDKT202312)。

摘　　要：面对全球水资源紧缺的挑战,准确估算作物需水量已经成为农业节水灌溉领域的关键环节。以反向传播神经网络和长短时记忆网络为代表的神经网络技术在参考作物蒸发蒸腾量估算方面具有独特优势。针对在农业水利领域的具体技术应用,提出一系列措施,包括特征工程、模型优化、决策系统整合以及技术普及推广。这些措施旨在推动神经网络技术在农业灌溉和气候政策支持方面的实用价值,为提升作物需水量估算的精准度和效率提供新的视角和工具,进而推动水资源的高效利用和农业的可持续发展。In the face of the challenge of global water shortage,accurate estimation of crop water demand has become a key link in the field of agricultural water-saving irrigation.Neural network technology,represented by back propagation neural network and short-term memory network,has unique advantages in reference crop evaporation estimation.Aiming at the specific technical application in the field of agricultural water conservancy,a series of measures are put forward,including feature engineering,model optimization,decision-making system integration and technology popularization.These measures aim to promote the practical value of neural network technology in agricultural irrigation and climate policy support,and provide new perspectives and tools for improving the accuracy and efficiency of crop water demand estimation.and then promote the efficient use of water resources and the sustainable development of agriculture.

关 键 词：参考作物需水量 神经网络 估算 农业水利 应用研究 

分 类 号：TV93[水利工程—水利水电工程]