典型文献
Real-time Prediction Model of Amount of Manure in Winter Pig Pen Based on Backpropagation Neural Network
文献摘要：
The automatic control of cleaning need to be based on the total amount of manure in the house. Therefore, this article established a prediction model for the total amount of manure in a pig house and took the number of pigs in the house, age, feed intake, feeding time, the time when the ammonia concentration increased the fastest and the daily fixed cleaning time as variable factors for modelling, so that the model could obtain the current manure output according to the real-time input of time. A Backpropagation (BP) neural network was used for training. The cross-validation method was used to select the best hyperparameters, and the genetic algorithm (GA), particle swarm optimization (PSO) algorithm and mind evolutionary algorithm (MEA) were selected to optimize the initial network weights. The results showed that the model could predict the amount of manure in real-time according to the model input. After the cross-validation method determined the hyperparameters, the GA, PSO and MEA were used to optimize the manure prediction model. The GA had the best average performance.
文献关键词：
中图分类号：
作者姓名：
Hu Zhen-nan;Sun Hong-min;Li Xiao-ming;Dai Bai-sheng;Gao Yue;Wang Yu-han
作者机构：
College of Electrical and Information,Northeast Agricultural University,Harbin 150030,China;Ministry of Agriculture and Rural Affairs,Key Laboratory of Pig Breeding Facilities Engineering,Harbin 150030,China
文献出处：
引用格式：
[1]Hu Zhen-nan;Sun Hong-min;Li Xiao-ming;Dai Bai-sheng;Gao Yue;Wang Yu-han-.Real-time Prediction Model of Amount of Manure in Winter Pig Pen Based on Backpropagation Neural Network)[J].东北农业大学学报（英文版）,2022(04):77-90
A类：
Amount
B类：
Real,Prediction,Model,Manure,Winter,Pig,Pen,Based,Backpropagation,Neural,Network,automatic,control,cleaning,need,total,amount,manure,house,Therefore,this,established,prediction,took,number,pigs,intake,feeding,when,ammonia,concentration,increased,fastest,daily,fixed,variable,factors,modelling,so,that,could,obtain,current,output,according,real,input,neural,network,was,used,training,cross,validation,method,best,hyperparameters,genetic,algorithm,GA,particle,swarm,optimization,PSO,mind,evolutionary,MEA,were,selected,optimize,initial,weights,results,showed,After,determined,had,average,performance
AB值：
0.496347
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