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

Inactive Publication Date: 2019-06-11
CHONGQING UNIV OF POSTS & TELECOMM
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Problems solved by technology

[0004] In order to solve the problem that the physiological state of domestic animals cannot be known in time in the traditional method, the present invention proposes a method and system for predicting the physiological state of domestic animals based on a multiple logistic regression model

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  • Livestock physiological status prediction method and system based on a multivariate logistic regression model
  • Livestock physiological status prediction method and system based on a multivariate logistic regression model
  • Livestock physiological status prediction method and system based on a multivariate logistic regression model

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Embodiment Construction

[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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Abstract

The invention provides a livestock physiological status prediction method and system based on a multivariate logic regression model. The method comprises the steps that physiological information and environment information of livestock are collected through a sensor, the collected relevant data are preprocessed, a cross validation method and grid searching are adopted for training, a multivariatelogistic regression model is obtained, and the optimal multivariate logistic regression model is used for predicting the physiological state of the livestock according to the real-time physiological data of the livestock; According to the method, the physiological condition of the livestock can be judged in time, whether the livestock is normal at the moment or is in common diseases at the momentis predicted, farmers are reminded according to the judgment result, and a user can find the abnormal condition of the livestock in time.

Description

technical field [0001] The invention relates to the field of machine learning, in particular to a method and system for predicting the physiological state of domestic animals using multiple logistic regression. Background technique [0002] Pork has always been a favorite meat in China and even in the world. According to relevant data, 80% of Chinese meat consumption was once pork. Even in 2014, the national pork output was 56.71 million tons, accounting for 65% of the total meat output, four times more than the combined output of beef and mutton. The biggest problem faced in the breeding process is the physiological state of the livestock. A little negligence in the breeding process may cause an irresistible epidemic. Infectious diseases are a relatively typical type of diseases, which are extremely harmful to livestock. If the prevention and control is not good, it will easily lead to the collapse of the entire farm. Pig diseases include swine fever, pseudorabies, foot-a...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/02
Inventor 雷大江龙彪涂潇引李雅琴杜聪刘俐杏李玥霖牛晓诚牛奥林
Owner CHONGQING UNIV OF POSTS & TELECOMM
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