An intelligent irrigation method for ecological restoration in photovoltaic zones based on automated machine learning

Abstract

The invention relates to the field of ecological restoration and irrigation technology in desert photovoltaic zones, and discloses an intelligent irrigation method for ecological restoration in photovoltaic zones based on automated machine learning. The method includes: acquiring environmental monitoring data of photovoltaic zones; performing data format unification, abnormal data normalization, and redundant data cleaning on the environmental monitoring data to establish a database; conducting feature selection, feature extraction, and feature construction on the environmental monitoring data in the database to establish a feature set; performing model training, model evaluation, and model management on an intelligent model to obtain an irrigation decision model; inputting the environmental monitoring data of photovoltaic zones into the irrigation decision model, and when the output result of the irrigation decision model indicates the need for irrigation, generating a water pump activation command and a valve opening adjustment command for irrigation. The invention integrates various monitoring devices and utilizes the irrigation decision model to achieve automatic irrigation based on soil and meteorological conditions, thereby efficiently utilizing water resources.