Intelligent tomato greenhouse temperature early-warning system based on minimum vector machine

Abstract

The invention discloses an intelligent tomato greenhouse temperature early-warning system based on a minimum vector machine. The early-warning system is characterized by being composed of a tomato greenhouse environmental parameter acquisition and intelligent prediction platform based on a CAN field bus and an intelligent tomato greenhouse temperature early-warning system. By means of the intelligent tomato greenhouse temperature early-warning system based on the minimum vector machine in the invention, many problems still in the environment in a closed tomato greenhouse due to the reasons ofunreasonable design, backward equipment, incomplete control system and the like in the traditional tomato greenhouse environment can be effectively solved; and furthermore, the control problem that the tomato greenhouse environment temperature is greatly influenced due to the fact that the existing tomato greenhouse environment monitoring system does not monitor and predict the temperature in thetomato greenhouse environment according to the characteristics of nonlinearity and large lag of tomato greenhouse environmental temperature change, large tomato greenhouse area, complex temperature change and the like can be effectively solved.

Description

technical field [0001] The invention relates to the technical field of agricultural greenhouse automation equipment, in particular to an intelligent early warning system for tomato greenhouse temperature based on a minimum vector machine. Background technique [0002] Tomato, as a kind of vegetable that loves temperature, has a suitable temperature range of about 20-25°C during the daytime when it grows; the most suitable temperature range at night is about 13-17°C. The suitable temperature of tomato can effectively promote photosynthesis at night and during the day, and the suitable temperature at night can promote the assimilation of substances in the most vigorous part of tomato during the day, and realize the full transfer in stem, fruit and root. High temperature will make the temperature appear to promote growth. With the continuous decrease of assimilation and the accumulation of nutrients, the plant will stagnate during growth, but keeping low temperature for a long ...

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Problems solved by technology

[0003] The invention provides an intelligent monitoring device for tomato greenhouse environment parameters based on ANFIS neural network. There are still many problems, and the existing tomato greenhouse environment monitoring system is effectively solved. It does not monitor the temperature of the tomato greenhouse environment according to the characteristics of the nonlinear temperature change of the tomato greenhouse environment, large lag, and the large area of ​​the tomato greenhouse and the complex temperature change. and prediction, thus greatly affecting the regulation of the ambient temperature of the tomato greenhouse

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