Livestock physiological status prediction method and system based on a multivariate logistic regression model
A logistic regression model and physiological state technology, applied in the field of machine learning, can solve problems such as not being able to know the physiological state of livestock in time, and achieve the effect of reducing losses and costs
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[0036] The following specific embodiments of the present invention are set forth to further illustrate the starting point of the present invention and corresponding technical solutions.
[0037] figure 1 It is a flow chart of a method for predicting the physiological state of domestic animals based on a multiple logistic regression model provided by an embodiment of the present invention, as shown in figure 1 As shown, the method includes the following four steps:
[0038] Step 1, collect physiological information and environmental information of livestock with sensors;
[0039] Step 2, preprocessing the collected data;
[0040] Step 3, using the preprocessed data, adopting cross-validation method and grid search to train multiple logistic regression model;
[0041] Step 4, use the optimal multiple logistic regression model to predict the physiological state of livestock according to the real-time physiological and environmental data of livestock.
[0042] figure 2 It is...
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