Prediction method of TMR daily ration rumen fermentation methane yield based on PSO-BP neural network

Abstract

The invention discloses a TMR daily ration rumen fermentation methane yield prediction method based on a PSO-BP neural network, and belongs to the field of methane yield prediction. The method comprises the following steps of: constructing a PSO-BP neural network, and performing normalization processing on the data of an input sample; establishing a data set; initializing the BP neural network according to the data set to obtain a weight and a threshold; after initializing a population, obtaining a particle swarm fitness value; determining an individual extreme value and a group extreme value; and updating a particle speed position, judging whether the iteration number reaches an end condition of initialization setting or not, if so, obtaining an optimal weight threshold value, calculating an updated weight threshold value, judging whether the iteration number reaches the end condition of initialization setting or not, and if so, starting simulation to obtain a prediction result. The method is used for solving the problem that the prediction error is large due to the fact that many data preprocessing is not ideal in an existing rumen fermentation methanogenesis prediction system.

Description

technical field [0001] The invention belongs to the field of prediction of methane production, and in particular relates to a prediction method of rumen fermentation methane production of TMR diet based on PSO-BP neural network. Background technique [0002] Since the beginning of this century, the phenomenon of global warming caused by greenhouse gas emissions has been attracting much attention. Methane (CH 4 ) is a greenhouse gas with a long half-life, and its warming potential is CO 2 The impact on global warming has accounted for 15%-20% of all impacts on climate warming in the past 100 years, and animal husbandry is the main contributor to the accumulation of methane in the atmosphere. Global annual CH 4 The emissions reached 5.35×108t, of which CH in ruminants 4 Average annual emissions account for the known emissions of CH to the atmosphere 4 15% of total emissions. Methane emissions from cattle (except buffalo) account for about 75% of total ruminant emissions....

AI Technical Summary

Problems solved by technology

[0005] The object of the present invention is to solve the problem that the accuracy of the existing rumen fermentation methane production results is not up to standard and the error is large for a method for predicting the methane production of rumen fermentation of TMR diet based on PSO-BP neural network. A kind of prediction method based on the TMR of PSO-BP neural network (totally mixed) ration rumen fermentation methane production, the concrete steps of described prediction method are as follows:

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