Prediction of pork supply via the calculation of pig population based on population prediction model

Zhang, Fan; Wang, Fulin

doi:10.25165/j.ijabe.20201302.5303

Cited by 6 publications

(4 citation statements)

References 9 publications

(10 reference statements)

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“…In this context, the estimation of financial projections has become a useful tool for assessing economic and financial viability of livestock systems. However, models must consider the conditions which prevail in the studied regions in order to reduce variability [ 28 ].…”

Section: Resultsmentioning

confidence: 99%

Economic and financial viability of a pig farm in central semi-tropical Mexico: 2022–2026 prospective

Martínez-Castañeda,

Callejas-Juárez,

Cuevas-Reyes

et al. 2024

PLoS ONE

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To estimate the economic and financial viability of a pig farm in central sub-tropical Mexico within a 5-year planning horizon, a Monte Carlo simulation model was utilized. Net returns were projected using simulated values for the distribution of input and product processes, establishing 2021 as base scenario. A stochastic modelling approach was employed to determine the economic and financial outlook. The findings reveal a panorama of economic and financial viability. Net income increased by 555%, return on assets rose from 3.36% in 2022 to 11.34% in 2026, and the probability of decapitalization dropped from 58% to 13%, respectively in the aforesaid periods. Similarly, the probability of obtaining negative net income decreased from 40% in 2022 to 18% in 2026. The technological, productive, and economic management of the production unit allowed for a favorable scenario within the planning horizon. There is a growing interest in predicting the economic sectors worth investing in and supporting, considering their economic and development performance. This research offers both methodological and scientific evidence to demonstrate the feasibility of establishing a planning schedule and validating the suitability of the pork sector for public investment and support.

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Section: Resultsmentioning

confidence: 99%

Economic and financial viability of a pig farm in central semi-tropical Mexico: 2022–2026 prospective

Martínez-Castañeda,

Callejas-Juárez,

Cuevas-Reyes

et al. 2024

PLoS ONE

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“…(1) During the initial phase, the areas affected by the epidemic are small and pig mortality is low. The state introduces timely measures to prevent and control the epidemics, including culling sick pigs in infected areas [ 25 ], leading to a reduction in the pig stock and the number of pigs slaughtered, with a light impact.…”

Section: Microscopic Mechanism Analysismentioning

confidence: 99%

The Threshold Effect of Swine Epidemics on the Pig Supply in China

Jia

Sun

et al. 2022

Animals

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The pig industry is the pillar industry of animal husbandry in China, and epidemics can lead to drastic changes in pig supply, affecting the healthy development of the pig industry and residents’ quality of life. This study analyzed the mechanism of the effect of swine epidemics on nonlinear shocks to pig supply, and monthly data on pig supply from January 2012 to June 2020 were applied to study the threshold effect of swine epidemics on pig stock and slaughter in China empirically, using the index of swine epidemics’ width (ISEW) as the threshold variable. The results of this study were as follows: (1) The influence of the ISEW over 7 months on pig stock in China was divided into two ranges, and the pig stock did not change significantly when the ISEW was less than 0.25. Swine epidemics had a significantly negative impact on the pig stock when the ISEW was larger than 0.25. (2) The influence of the ISEW over 8 months on pig slaughter was also divided into two ranges. When the ISEW was less than 0.33, epidemics had a positive and significant effect on pig slaughter, while epidemics had a marked negative impact on pig slaughter when the ISEW was greater than 0.33. Based on these conclusions, this study proposed relevant measures for the prevention and control of swine epidemics.

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“…e neural network contains many neuron nodes, which are interconnected to form an operation model, and each neuron node represents a specific output function. e connection between two nodes represents the weight of the connection signal [27]. e internal connection mode of neural network determines the output result of the network, which can be divided into forward network and feedback network according to the characteristics of network topology.…”

Section: Prediction Model Of Pig Price and Yield Based On Lstmmentioning

confidence: 99%

Production Efficiency Prediction of Pig Breeding Industry by Optimized LSTM Computer Algorithm under Environmental Regulation

Jia

Zhao-hui

et al. 2021

Scientific Programming

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The study aims to improve the economic income of pig breeding industry under environmental regulation and control the environmental pollution caused by pig breeding. Long short-term memory (LSTM) neural network combined with environmental regulation is proposed to forecast the price of live pigs, to reduce the cost of environmental pollution control and improve the production efficiency of pig breeding. Primarily, analyses are made on the industrial structure and pollution of pigs in China, and studies are carried out on the inevitability of large-scale and intensive pig breeding. Then, pig breeding and environmental pollution are coordinated under the environmental regulation. From the perspective of green total factor productivity, calculation is made on the profit of pig breeding and the cost of environmental pollution control. Next, the LSTM neural network is used to predict the price of live pigs, thus effectively controlling the scale of pig breeding and making timely decisions that conform to market rules. The results show that with the increase of feed and land prices, the advantages of large-scale pig breeding gradually become prominent, which leads to the small- and medium-sized scale farmers withdrawing from the market. Compared with other similar models, the designed model can better simulate the future trend of hog price, of which the prediction accuracy is over 80%. When combined with environmental regulations, the prediction accuracy of the model for different data sets reaches 83%, so the designed model can better predict the changing trend of the price of live pigs, thus improving the production efficiency of large-scale pig farmers.

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Prediction of pork supply via the calculation of pig population based on population prediction model

Cited by 6 publications

References 9 publications

Economic and financial viability of a pig farm in central semi-tropical Mexico: 2022–2026 prospective

Economic and financial viability of a pig farm in central semi-tropical Mexico: 2022–2026 prospective

The Threshold Effect of Swine Epidemics on the Pig Supply in China

Production Efficiency Prediction of Pig Breeding Industry by Optimized LSTM Computer Algorithm under Environmental Regulation

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