Field crop evapotranspiration prediction system based on machine learning

Abstract

The invention discloses a field crop evapotranspiration prediction system based on machine learning. The system comprises an acquisition terminal, a server end and a client end. The acquisition terminal is used for collecting meteorological data information of each monitoring point of a farmland in real time and transmitting the meteorological data information to the server end through a communication network; the server end writes the meteorological data into a database, and carries out pretreatment on the collected meteorological data and carries out data model training through a machine learning algorithm; and a data visualization module enables an evapotranspiration predication result to be drawn into an evapotranspiration prediction map, and sends the result of the data model to the client end through the communication network so as to carry out predication result display. The system provides more scientific and reasonable irrigation guidance for large-area farmland crop irrigation.

Description

technical field [0001] The invention relates to the field of crop monitoring, in particular to a machine learning-based prediction system for farmland crop evapotranspiration. Background technique [0002] Machine learning theory and related technologies have been applied in various fields. At present, the more mature ones are face recognition and intelligent transportation, which are also reflected in many fields such as intelligent agriculture, weather forecast, physiological pathology, and environmental monitoring research, and have been widely used. [0003] For the irrigation situation during the growth of farmland crops, the traditional method is to check manually in the field. Although the accuracy of judging the water demand is high, it requires a lot of labor costs in the face of the relatively large area of ​​farmland concentrated planting. , and there is no way to check it in real time, it is often only noticed when there is a need for timely irrigation in a small...

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Problems solved by technology

[0003] For the irrigation situation during the growth of farmland crops, the traditional method is to check manually in the field. Although the accuracy of judging the water demand is high, it requires a lot of labor costs in the face of the relatively large area of ​​farmland concentrated planting. , and there is no way to check it in real time, it is often only noticed when there is a need for timely irrigation in a small area, which seriously affects agricultural production activities

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