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Genetic BP neural network-based solar greenhouse temperature prediction method

A BP neural network, solar greenhouse technology, applied in the field of solar greenhouse temperature prediction, to achieve the effect of simulation stability

Inactive Publication Date: 2018-04-13
NORTHWEST A & F UNIV
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AI Technical Summary

Problems solved by technology

Li Yongbo et al. proposed the uniformity control of greenhouse temperature field and the multi-index GA optimization control method based on the CFD steady-state simulation model. Qu Yi et al. combined the radial basis function neural network and the PID control law to form a neural network RBF-PID controller to realize Greenhouse temperature control, Zuo Zhiyu et al. proposed to use the time series analysis method to establish a temperature prediction model, but only considered a single factor affecting indoor temperature

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  • Genetic BP neural network-based solar greenhouse temperature prediction method
  • Genetic BP neural network-based solar greenhouse temperature prediction method
  • Genetic BP neural network-based solar greenhouse temperature prediction method

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Embodiment Construction

[0021] The technical solution of the present invention will be described in further detail below in conjunction with the accompanying drawings and specific embodiments.

[0022] 1. Greenhouse temperature prediction model based on BP neural network

[0023] 1.1 BP neural network

[0024] Artificial neural network (ANN, Artifieial Neural Networks) is established by simulating the human brain nervous system. According to the different connection methods, its structure can be roughly divided into two categories: hierarchical and mesh. BP neural network is a kind of feed-forward network, and it is also the most widely used network at present. It uses the error backpropagation algorithm. The input information is processed through the input layer and the hidden layer to calculate the actual output value of each unit. If the expected output value cannot be obtained in the output layer, the actual output and the expected output are recursively calculated layer by layer. The differen...

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Abstract

The invention discloses a genetic BP neural network-based solar greenhouse temperature prediction method. According to the method, on the basis of analysis on main factors affecting the microclimate environment of a greenhouse, with the temperature and light in the greenhouse and the difference of temperature inside and outside the greenhouse adopted as model input, a BP neural network-based greenhouse temperature prediction model is constructed; and the BP neural network algorithm is improved by using the genetic algorithm to optimize the weight and threshold of the network, and therefore, agenetic BP neural network-based greenhouse temperature prediction model is constructed. A simulation result shows that the prediction effect of the genetic algorithm optimized BP neural network has fewer errors and higher prediction than the prediction effect of the BP neural network, and can realize effective prediction of the temperature of the solar greenhouse.

Description

technical field [0001] The invention relates to a method for predicting the temperature of a solar greenhouse, in particular to a method for predicting the temperature of a solar greenhouse based on a genetic BP neural network. Background technique [0002] Facility horticulture is an environment-controlled industry that improves the local environment through modern agricultural engineering, mechanical technology and management technology, and can provide crops with microclimate environments such as temperature, light, water, gas, and fertilizer that are suitable for their growth. my country's protected vegetable cultivation area accounts for more than 90% of the world's total area, and has become an important part of my country's modern agriculture. The solar greenhouse is the main body of facility production. It relies on the natural heating of sunlight during the day and the heat preservation equipment at night to create the required indoor temperature. It can produce off...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/08
CPCG06N3/084G06N3/086
Inventor 王丽娜魏谦琛
Owner NORTHWEST A & F UNIV
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