[Retracted] Intelligent Control of Agricultural Irrigation through Water Demand Prediction Based on Artificial Neural Network

人工神经网络 计算机科学 农业 控制(管理) 灌溉 人工智能 农学 生态学 生物
作者
Qiuyu Bo,Wuqun Cheng
出处
期刊:Computational Intelligence and Neuroscience [Hindawi Publishing Corporation]
卷期号:2021 (1) 被引量:6
标识
DOI:10.1155/2021/7414949
摘要

In irrigated areas, the intelligent management and scientific decision‐making of agricultural irrigation are premised on the accurate estimation of the ecological water demand for different crops under different spatiotemporal conditions. However, the existing estimation methods are blind, slow, or inaccurate, compared with the index values of the water demand collected in real time from irrigated areas. To solve the problem, this paper innovatively introduces the spatiotemporal features of ecological water demand to the forecast of future water demand by integrating an artificial neural network (ANN) for water demand prediction with the prediction indices of water demand. Firstly, the ecological water demand for agricultural irrigation of crops was calculated, and a radial basis function neural network (RBFNN) was constructed for predicting the water demand of agricultural irrigation. On this basis, an intelligent control strategy was presented for agricultural irrigation based on water demand prediction. The structure of the intelligent control system was fully clarified, and the main program was designed in detail. The proposed model was proved effective through experiments.
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