A Prediction Method of Temperature Extremes in Greenhouse
A prediction method and technology in the greenhouse, applied in the field of agriculture, can solve problems such as insufficient accuracy of extreme temperature values, and achieve efficient prediction results
Active Publication Date: 2017-12-19
CHINA AGRI UNIV +1
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Problems solved by technology
[0005] The technical problem to be solved by the present invention is the problem that the accuracy of the existing method for predicting the temperature extremum in the greenhouse is not enough
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[0056] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are the Some, but not all, embodiments are invented. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.
[0057] The embodiment of the present invention proposes a method for predicting the extreme temperature in the greenhouse, such as figure 1 As shown, the method includes:
[0058] S1. Collect environmental data of the greenhouse within a predetermined period of time;
[0059] S2. Normalize the obtained environmental data to obtain a sample set;
[0060] S3. Use the u...
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The invention discloses a method for predicting a temperature extreme value in a greenhouse. The method comprises: S1, acquiring environment data within a preset time period; S2, performing nominalization processing on the obtained environment data, and obtaining a sample set; S3, randomly generating N width coefficients sigma<2> and N punishment coefficients lambda of a radial basis function of a least square support vector machine regression model LS_SVM by use of a uniform distribution algorithm; S4, selecting a training sample set from the sample set and training the LS_SVM; S5, initializing the particle swarm of a particle swarm optimization (PSO) algorithm to be a two-dimensional coordinate point composed of the sigma<2> and the lambda; S6, optimizing the sigma<2> and the lambda by use of the PSO; S7, selecting a test sample set from the sample set, testing the LS_SVM of an optimization parameter, and obtaining an optimization LS_SVM; and S8, acquiring the environment data of the greenhouse in real time on line, inputting the data to the optimization LS_SVM, and obtaining the prediction value of the temperature extreme value in the greenhouse.
Description
technical field [0001] The invention relates to the field of agricultural technology, in particular to a method for predicting temperature extremes in a greenhouse. Background technique [0002] Temperature is one of the main factors to be regulated in the greenhouse, and it is also one of the main factors that determine whether the crops in the greenhouse can grow normally. If the temperature in the greenhouse is too low or too high, it will bring serious harm to the plants. Therefore, the extreme value of the temperature in the greenhouse can be predicted quickly and accurately, and preventive measures can be taken before the temperature in the greenhouse reaches the extreme value to reduce the damage caused by low temperature or high temperature to crops. , which plays a very important role in increasing the yield of greenhouse crops. [0003] At present, the methods for predicting the temperature extremes in the greenhouse are time series analysis method, mathematical s...
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IPC IPC(8): G06N3/00
Inventor 陈英义于辉辉李道亮郭承坤阮怀军封文杰
Owner CHINA AGRI UNIV