An intelligent detection system for eggplant greenhouse environment based on wavelet neural network

Abstract

The invention discloses an eggplant greenhouse environment intelligent detection system based on wavelet neural network, which is characterized in that: the detection system is composed of two parts: an eggplant greenhouse environment parameter collection platform based on a wireless sensor network and an eggplant greenhouse output intelligent early warning system; The present invention effectively solves the problem that the output of the existing eggplant greenhouse is not affected by the non-linearity, large lag, large area of ​​the eggplant greenhouse, and complex temperature changes of the eggplant greenhouse. The precise detection and adjustment of temperature will greatly affect the environmental yield prediction and production management of eggplant greenhouses.

Description

technical field [0001] The invention relates to the technical field of agricultural greenhouse automation equipment, in particular to an eggplant greenhouse environment intelligent detection system based on a wavelet neural network. Background technique [0002] Eggplant is one of the main types of vegetables in the north and south of my country. It occupies an important position in production and is widely cultivated in various parts of our country. At present, my country's eggplant production has achieved annual supply, basically forming a four-element annual protection cultivation system of high-efficiency and energy-saving solar greenhouses, plastic sheds, plastic films, and sunshade nets. Eggplant belongs to the taproot eggplant with well-developed root system and strong ability to absorb fertilizer and water. Eggplant is tender and juicy, with large fruit size and high water demand. Therefore, water management has become one of the most critical technologies in eggpla...

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Problems solved by technology

[0003] The present invention provides an intelligent detection system for eggplant greenhouse environment based on wavelet neural network. The present invention effectively solves the problem that the output of the existing eggplant greenhouse does not vary according to the environmental temperature of the eggplant greenhouse, the large hysteresis and the complex temperature change of the eggplant greenhouse. The impact on the production of eggplant greenhouse, there is no prediction of the production of eggplant greenhouse and accurate detection and adjustment of the environmental temperature of the eggplant greenhouse, which greatly affects the environmental output prediction and production management of eggplant greenhouse

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