Breeding risk simulation and evaluation method of laying hen type breeding system based on risk control engine

Abstract

The application provides a risk assessment method of a laying hen breeding system based on a risk control engine, and relates to the technical field of risk assessment of laying hen breeding. The method comprises the following steps: collecting historical breeding data of laying hens, and performing risk factor analysis on output quality based on breeding cost to form a breeding output risk control model; collecting market breeding price data of the laying hens, performing price trend analysis on breeding output, and forming egg hen output price trend change information; obtaining breeding output requirement information, collecting real-time breeding data, performing risk identification on breeding output, and forming breeding output risk identification data; and performing breeding risk disposal according to the breeding output risk identification data to form breeding risk disposal result data. The method establishes a reasonable risk simulation evaluation mode based on risk factors affecting the breeding of laying hens to realize reasonable prediction of the return on breeding of laying hens, and effectively reduces the loss risk of breeding of laying hens.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of laying hen breeding risk assessment, in particular to a breeding risk simulation evaluation method of a laying hen breeding system based on a risk control engine. BACKGROUND

[0002] Laying hen breeding belongs to the industry form of investment first and return later, so there are subjective and objective factors in the investment process, which causes certain risks in laying hen breeding. In order to ensure that laying hen breeding can realize reasonable return, reasonable investment return evaluation should be carried out when investing in the early stage, so as to avoid the loss caused by blind investment.

[0003] The risk control engine mainly collects, identifies and processes the risk factors of the risk system with risk factors, so as to realize the risk control of the risk system and effectively reduce the damage caused by the risk to the system. Reasonable risk control of laying hen breeding can effectively guarantee the investment return benefit of laying hen breeding. At present, the risk assessment based on the risk engine of laying hen breeding is not mature, and how to reasonably evaluate and process the risk of laying hen breeding is worth considering.

[0004] Therefore, a breeding risk simulation evaluation method of a laying hen breeding system based on a risk control engine is designed, which establishes a reasonable risk simulation evaluation method based on the risk factors affecting laying hen breeding, so as to realize the reasonable prediction of the return of laying hen breeding and effectively reduce the loss risk of laying hen breeding, which is the problem to be solved at present. SUMMARY

[0005] The present application relates to the technical field of laying hen breeding risk assessment, in particular to a breeding risk simulation evaluation method of a laying hen breeding system based on a risk control engine.

[0006] In a first aspect, the present application provides a breeding risk simulation evaluation method for a laying hen breeding system based on a risk control engine, including collecting historical breeding data of laying hens, and performing risk factor analysis of output quality based on breeding cost to form a breeding output risk control model; collecting market breeding price data of laying hens, and combining the breeding output risk control model to perform price trend analysis of breeding output to form egg output price trend change information; obtaining breeding output requirement information, collecting real-time breeding data, combining the breeding output risk control model and the egg output price trend change information to perform risk identification of breeding output to form breeding output risk identification data; and performing breeding risk disposal according to the breeding output risk identification data to form breeding risk disposal result data.

[0007] In the present application, the method establishes a risk factor relative output quality and output yield risk influence model by performing risk factor analysis of the historical breeding data of laying hens on the output quality and output yield. Meanwhile, the risk influence model is used to perform risk identification of the output cost and sales price based on the breeding output requirements, so as to ensure that the possible risk size of return profit can be reasonably identified before breeding investment is performed, and then reasonable risk processing is performed for the breeding to be invested, and the loss of breeding is effectively avoided.

[0008] As a possible implementation manner, the historical breeding data of laying hens is collected, and the risk factor analysis of the output quality based on the breeding cost is performed to form the breeding output risk control model, including: taking the output of a single item as a breeding analysis period, extracting the breeding quality control factors affecting the egg quality grade in the historical breeding data of laying hens to form output quality control factor data; taking the output of a single item as a breeding analysis period, extracting the breeding yield control factors affecting the number of eggs in the historical breeding data of laying hens to form output yield control factor data; and performing risk control analysis based on the influence of egg grade quantity to the output quality control factor data and the output yield control factor data to form the breeding output risk control model.

[0009] In the present application, the breeding output risk control model is established based on the historical breeding data of laying hens. The fundamental of risk control is to determine whether the return of breeding is stable and acceptable. Therefore, the establishment of the control model considers two aspects that affect the return of breeding. One is the risk control factors that affect the quality of egg output, and the other is the risk control factors that affect the quantity of egg output. After all, the quality of egg quality determines the unit price of egg, the output of egg determines the sales volume of egg, and the unit price of egg and the sales volume of egg jointly affect the return of breeding output, i.e. the profit of breeding output. Combined with the risk factor information affecting the quality of egg output and the risk factor information affecting the quantity of egg output, the risk control model affecting the return of egg breeding output is established, which provides an important analysis basis for subsequent risk identification and risk processing.

[0010] As a possible implementation manner, the output quality control factor data and the output quantity control factor data are subjected to risk control analysis based on the influence of egg grade quantity, forming a breeding output risk control model, including: according to the output quality control factor data, determining all output quality risk factors affecting the quality of egg output, and performing influence quantity analysis of different output quality risk factors on the influence of egg grade, forming output quality risk factor influence relationship information; according to the output quantity control factor data, performing multi-factor change analysis on the output quantity risk factors affecting the change of egg quantity, forming output quantity risk factor influence relationship information; combining the output quality risk factor influence relationship information and the output quantity risk factor influence relationship information, forming the breeding output risk control model.

[0011] In the present application, the establishment of the breeding output risk control model is realized by respectively performing risk factor influence relationship analysis affecting the output quality and risk factor relationship analysis affecting the output quantity. Only by accurately determining the risk control factors affecting the output quality and the influence relationship between these risk control factors and the output quality, and the risk control factors affecting the output quantity and the influence relationship between these risk control factors and the output quantity, can a reasonable breeding output risk control model be established.

[0012] As a possible implementation manner, according to the output quality control factor data, all output quality risk factors affecting the quality of egg output are determined, and influence quantity analysis of different output quality risk factors on the influence of egg grade is performed, forming output quality risk factor influence relationship information, including: taking the breeding analysis period as the data extraction basis, establishing the high-grade egg quantity percentage and the high-grade quality influence relationship of different output quality risk factor parameter quantity under each breeding analysis period , wherein: n represents the number of different output quality risk factors affecting the output of high-grade eggs, a high-level quality impact relationship an impact coefficient of the output quality risk factor numbered n, a constant term in the high-level quality impact relationship , a percentage of high-level egg quantity; based on a breeding analysis period for data extraction, a high-level quality impact relationship between the percentage of high-level egg quantity and the number of different output quality risk factor parameters in each breeding analysis period is established , wherein: m represents the number of different output quality risk factors affecting the output of high-level eggs, a high-level quality impact relationship an impact coefficient of the output quality risk factor numbered m in the high-level quality impact relationship a constant term in the high-level quality impact relationship , a low-level quality impact relationship between the percentage of low-level egg quantity and the number of different output quality risk factor parameters in each breeding analysis period is established , wherein: k represents the number of different output quality risk factors affecting the output of low-level eggs, a low-level quality impact relationship an impact coefficient of the output quality risk factor numbered k in the low-level quality impact relationship a constant term in the low-level quality impact relationship , , there are .

[0013] ​In the present application, the analysis of risk control factors affecting the quality of the output obtains the influence relationship information of the risk control factors affecting the quality of the output by analyzing the probability of the output of eggs of different grades. It can be understood that for different grades of eggs, from low grade to high grade, the proportion of low grade eggs in each output period is controlled by basic breeding parameters, and for medium grade and high grade eggs, other independent risk control factors are added on the basis of the risk control factors corresponding to low grade eggs to expand the single output proportion. Thus, for the risk control factors corresponding to low grade quality, the risk control factors corresponding to medium grade quality and the risk control factors corresponding to high grade quality, these risk control factors are relatively independent and only affect the corresponding egg grade. Of course, for the risk control factors affecting the quality of the same grade of eggs, since the quality of the eggs is affected by many factors, when determining the grade influence relationship, a reasonable influence relationship is established by using big data to analyze the influence of multiple factors. In addition, it should be noted that the risk control factors affecting the quality of low grade eggs are also necessary factors for the subsequent production of medium grade and high grade quality eggs, but the control and adjustment of these necessary factors cannot increase the output proportion of medium grade and high grade quality eggs, that is, the adjustment of these necessary factors only causes whether eggs can be produced or low grade eggs are produced, and on the basis of producing eggs or low grade eggs, more reasonable influence relationships are formed by analyzing and determining the risk control factors affecting the production of medium grade and high grade eggs.

[0014] As a possible implementation manner, according to the output yield control factor data, a multi-factor change analysis is performed on the output yield risk factors affecting the change of the number of eggs to form the influence relationship information of the output yield risk factors, including: taking the breeding analysis period as the data extraction basis, establishing the yield influence relationship of the number of eggs and different output yield risk factor parameters in each breeding analysis period , wherein: i represents the number of different output yield risk factors, represents the influence coefficient of the output yield risk factor numbered i in the yield influence relationship , and represents the constant term in the yield influence relationship , Q represents the total number of eggs; according to different yield influence relationships , all influence coefficients and constant terms in the yield influence relationship are determined.

[0015] In the present application, the determination of the influence relationship of the risk control factors affecting the output yield and the output yield is based on the multi-factor analysis of the risk control factors affecting the output yield based on historical big data. It should be noted that for the influence relationship of the output quality and the corresponding risk control factors or the influence relationship of the output yield and the corresponding risk control factors, since the amount of big data is huge, there are redundant data in determining the corresponding influence coefficient and constant term, therefore, the relationship can be established by grouping to determine the corresponding influence coefficient and constant term after averaging fitting, or the data can be reasonably screened to establish the relationship to determine the corresponding influence coefficient and constant term.

[0016] As a possible implementation manner, the breeding output risk control model is formed by combining the output quality risk factor influence relationship information and the output yield risk factor influence relationship information, including: determining the low-grade breeding output risk control model according to the low-grade quality influence relationship and the yield influence relationship : wherein, represents the total amount of low-grade breeding output; determining the medium-grade breeding output risk control model according to the medium-grade quality influence relationship and the yield influence relationship : wherein, represents the total amount of medium-grade breeding output; determining the high-grade breeding output risk control model according to the high-grade quality influence relationship and the yield influence relationship : wherein, represents the total amount of high-grade breeding output.

[0017] In the present application, the breeding output risk control model comprehensively considers the influence relationship affecting the output quality and the influence relationship affecting the output yield, and the influence relationship of the output yield is established based on different grade egg information, so that the breeding risk control model is established based on different grades to ensure the rationality of the model establishment and provide more reasonable basic data for subsequent risk analysis of different grade egg demand.

[0018] ​​​As a possible implementation manner, market breeding price data of the laying hen breeding is collected, and a breeding output price trend analysis is performed in combination with the breeding output risk control model to form the laying hen output price trend change information, including: according to the market breeding price data, determining the change trend of the cost amount of different output quality risk factors of different grades in the time dimension, and periodically fitting to form the unit cost periodic change trend of the output quality risk factors , wherein e takes n, m, k; according to the market breeding price data, determining the change trend of the cost amount of different output yield risk factors in the time dimension, and periodically fitting to form the unit cost periodic change trend of the output yield risk factors ; according to the market breeding price data, determining the change trend of the price of different grades of eggs in the time dimension, and periodically fitting to form the unit price periodic change trend of the output grades , wherein g takes low, middle and high.

[0019] In the present application, the risk control model only establishes the relationship between the risk control factors and the output quality and output yield, and for the laying hen breeding, the risk is ultimately reflected in the investment return, so it is more intuitive to perform the risk assessment of the investment return, and it is necessary to perform the economic analysis on the factors affecting the investment return. Here, for all the risk control factors in the breeding process, including all the risk control factors affecting the output quality and output yield, the change trend in the time dimension is determined, of course, it is also necessary to analyze the change trend in the time dimension of the price of different grades of eggs, which determines the total sales and is an important parameter affecting the return profit. It should be noted that the cost of the risk control factors affecting the output quality and output yield and the price of different grades of eggs are all part of the market behavior of breeding, and therefore the change trend in the time dimension also has market characteristics. Based on the supply and demand characteristics of the market, the change of these cost prices has regularity, and the fitting of the change trend of the same factors in different periods based on the breeding period can reasonably and accurately form the prediction of the cost change rule of the factors in the periodic breeding.

[0020] As a possible implementation manner, the breeding output requirement information is acquired, the breeding output risk identification is performed in combination with the breeding output risk control model and the laying hen output price trend change information, and the breeding output risk identification data is formed, including: according to the breeding output requirement information, respectively determining the required number of high-grade eggs and the corresponding high-grade output demand proportion , the required number of medium-grade eggs and the corresponding medium-grade output demand proportion , and the required number of low-grade eggs and the corresponding low-level output demand ratio and the demand deadline; with the high-level output demand ratio and the medium-level output demand ratio For reference, the corresponding output quality risk factor parameter quantity control adjustment is made, and the following analysis and judgment are made: if the parameter quantity control adjustment of different output quality risk factors achieves the high-level output demand ratio and the medium-level output demand ratio , then according to the demand deadline and the different output quality risk factor unit cost period change trend , the output quality estimated total cost of the cost minimum value combination in the value combination of different output quality risk factors is determined , and according to the high-level egg demand quantity , the medium-level egg demand quantity , and the low-level egg demand quantity , and the yield influence relationship , combined with the different output yield risk factor unit cost period change trend and the different output level unit price period change trend , the output quantity estimated total cost and the output estimated sales total , according to the output quality estimated total cost , the output quantity estimated total cost and the output estimated sales total , the output estimated profit is determined , wherein: ; if the parameter quantity control adjustment of different output quality risk factors cannot achieve the high-level output demand ratio and the medium-level output demand ratio , then the quality and quantity guaranteed output quantity adjustment estimation is made, and the output estimated profit is determined ; the profit acceptance rate threshold is set , according to the output estimated profit obtained , the output quality estimated total cost and the output quantity estimated total cost , the following risk identification analysis is made: when , the controllable profit risk identification information is formed; when , the non-controllable profit risk identification information is formed; when , the loss risk identification information is formed.

[0021] In the present application, the requirements of laying hen breeding are the conditions that need to be met, based on which risk identification analysis is carried out in combination with risk control model and price trend change information of laying hens, so as to accurately determine whether there is a return risk for the investment return of the breeding requirements. It can be understood that in the risk identification, the best state is to adjust the risk control factors to realize the satisfaction of the output quality and quantity demand. In this case, the number of eggs just meets the demand without excess, after all, although the excess eggs have market price, the influence of the cost of risk control factors is extensive and large. For the case that cannot be satisfied by adjusting the risk control factors, reasonable estimation is carried out according to the principle of minimum cost consumption, so as to realize the risk identification of this case. Of course, after obtaining the estimated profit, it is not considered to be risk-free as long as there is profit, it is necessary to consider the uncertainty of the risk assessment and the actual possible sudden impact on the output, so the reasonable judgment is carried out based on the threshold height boundary of the estimated profit in the risk identification, and the profit acceptance threshold can be set according to the actual situation, or it can be determined based on big data analysis.

[0022] As a possible implementation manner, if the parameter quantity control adjustment of different output quality risk factors cannot realize the high-level output demand proportion and the medium-level output demand proportion , the quality and quantity of output are adjusted and estimated, and the output estimated profit is determined, including: taking the medium-level output demand proportion as a reference, determining the maximum allowed high-level output demand proportion under the condition of meeting the medium-level output demand proportion , and according to the high-level egg demand quantity , combining the medium-level breeding output risk control model , the high-level breeding output risk control model , the medium-level output demand proportion and the maximum allowed high-level output demand proportion , determining the necessary number of medium-level eggs and the necessary number of low-level eggs that meet the high-level egg demand quantity ; according to the medium-level output demand proportion and the maximum allowed high-level output demand proportion , combining the demand deadline and the unit cost period change trend of different output quality risk factors , determining the output quality estimated total cost of the cost minimum value combination of the value combination of different output quality risk factors , and according to the high-level egg demand quantity the necessary quantity of medium-grade eggs and the necessary quantity of low-grade eggs and the influence relationship of the yield combined with the unit cost period change trend of different output yield risk factor and the unit price period change trend of different output grade determining the total cost of output quantity estimation and the total sales of output estimation according to the total cost of output quality estimation the total cost of output quantity estimation and the total sales of output estimation determining the estimated profit of output wherein: .

[0023] In the present application, when there is no way to meet the output quality and output demand by adjusting the risk control factors, the risk identification estimation is estimated by considering adjusting the output yield and ensuring that the number of high-grade eggs just meets the required number. After all, the cost impact caused by the increase in the number of high-grade eggs is greater than the cost impact caused by the increase in the number of medium-grade eggs. The higher the grade of the eggs, the higher the cost consumed by the output. The gap between this cost and the corresponding market price will be smaller than that of low-grade eggs, so the profit will be relatively reduced. Therefore, the adjustment is made with reference to the requirement of just meeting the number of high-grade eggs.

[0024] As a possible implementation manner, according to the breeding output risk identification data, the breeding risk disposal is carried out to form breeding risk disposal result data, including: when the risk identification result shows controllable profit risk identification information, outputting no disposal information; when the risk identification result shows non-controllable profit risk identification information, outputting profit risk warning information and warning profit rate ; when the risk identification result shows loss risk identification information, outputting production loss warning information and loss rate .

[0025] In the present application, after completing the risk identification, the identified risk needs to be processed and warned. For controllable profit risk identification information, the profit is controllable, and there is a stable return condition, so it is a positive breeding investment signal. For non-controllable profit risk identification information, although there is a condition to obtain profit, the actual profit obtainment is greatly affected, and needs to be carefully considered. For loss risk identification information, it can be sure that the investment to meet the breeding requirements this time is loss.

[0026] The breeding risk simulation evaluation method of the egg chicken breeding system based on the risk control engine provided by the present application has the following advantages:

[0027] The method establishes a risk influence model of risk factors relative to output quality and output quantity by analyzing the risk factors influencing the output quality and output quantity of the laying hen historical breeding data. Meanwhile, the risk influence model is used to identify the risks influencing the output cost and sales price based on the breeding output requirements, so as to reasonably identify the risk size of the return profit before the breeding investment is made, and then reasonably process the breeding investment in time, thereby effectively avoiding the breeding loss. BRIEF DESCRIPTION OF DRAWINGS

[0028] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments of the present application will be briefly introduced as follows. It should be understood that the following drawings only show some embodiments of the present application, and therefore should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can also be obtained without creative labor on the basis of these drawings.

[0029] Figure 1 The step diagram of the breeding risk simulation and evaluation method of the laying hen breeding system based on the risk control engine provided by the embodiments of the present application. DETAILED DESCRIPTION

[0030] The technical solutions in the embodiments of the present application will be described below in combination with the drawings in the embodiments of the present application.

[0031] Laying hen breeding belongs to an industry form of first investment and then return, and therefore there are subjective and objective factors in the investment process, which causes certain risks in the laying hen breeding. In order to ensure that the laying hen breeding can achieve reasonable return, reasonable investment return evaluation should be performed when the investment is made in the early stage, so as to avoid the loss caused by blind investment.

[0032] The risk control engine mainly collects, identifies and processes the risk factors of the risk system with risk factors, so as to realize the risk control of the risk system and effectively reduce the damage caused by the risk to the system. Reasonable risk control of the laying hen breeding can effectively ensure the investment return benefit of the laying hen breeding. At present, the risk assessment based on the risk control engine for the laying hen breeding is not mature, and how to reasonably assess and process the risk of the laying hen breeding is worth considering.

[0033] REFERENCE Figure 1The embodiment of the present application provides a breeding risk simulation evaluation method of a laying hen breeding system based on a risk control engine, which analyzes risk factors affecting output quality and output quantity of historical breeding data of laying hens, establishes a risk influence model of risk factors relative to output quality and output quantity. Meanwhile, based on the breeding output requirements, the risk influence model is used to identify the risks affecting the output cost and the sales price, so as to reasonably identify the possible risk size of the return profit before breeding investment, and then timely take reasonable risk treatment for the breeding investment, and effectively avoid the breeding loss.

[0034] The breeding risk simulation evaluation method of the laying hen breeding system based on the risk control engine specifically includes the following steps:

[0035] S1: Collect historical breeding data of laying hens, and perform risk factor analysis of output quality based on breeding cost to form a breeding output risk control model.

[0036] The historical breeding data of laying hens are collected, and the risk factor analysis of output quality based on breeding cost is performed to form a breeding output risk control model, including: taking the output of a single item as the breeding analysis period, extracting the breeding quality control factors affecting the egg quality grade in the historical breeding data of laying hens to form output quality control factor data; taking the output of a single item as the breeding analysis period, extracting the breeding yield control factors affecting the number of eggs in the historical breeding data of laying hens to form output yield control factor data; performing risk control analysis based on the influence of egg grade quantity to form a breeding output risk control model.

[0037] The breeding output risk control model is established based on the historical breeding data of laying hens. The fundamental of risk control is to determine whether the breeding return is stable and acceptable, so the establishment of the control model considers two aspects of affecting the breeding return. One is the risk control factor affecting the output quality of eggs, and the other is the risk control factor affecting the output quantity of eggs. After all, the quality of eggs determines the unit price of eggs, the output quantity of eggs determines the sales quantity of eggs, and the unit price of eggs and the sales quantity of eggs jointly affect the return of breeding output, that is, the profit of breeding output. Combined with the risk factor information affecting the output quality of eggs and the risk factor information affecting the output quantity of eggs, a risk control model affecting the return of egg breeding output is established, which provides an important analysis basis for subsequent risk identification and risk treatment.

[0038] The risk control analysis based on the influence of egg grade quantity is performed on the output quality control factor data and the output yield control factor data, and a breeding output risk control model is formed, including: determining all output quality risk factors influencing the egg output quality according to the output quality control factor data, and performing influence quantity analysis of the influence of different output quality risk factors on the egg grade to form output quality risk factor influence relationship information; performing multi-factor change analysis of output yield risk factors influencing the change of egg quantity according to the output yield control factor data to form output yield risk factor influence relationship information; combining the output quality risk factor influence relationship information and the output yield risk factor influence relationship information to form the breeding output risk control model.

[0039] The establishment of the breeding output risk control model is realized by respectively performing risk factor influence relationship analysis influencing the output quality and risk factor relationship analysis influencing the output yield. Only by accurately determining the risk control factors respectively influencing the output quality and the influence relationship of these risk control factors with the output quality and the risk control factors influencing the output yield and the influence relationship of these risk control factors with the output yield, can a reasonable breeding output risk control model be established.

[0040] According to the output quality control factor data, all output quality risk factors influencing the egg output quality are determined, and influence quantity analysis of the influence of different output quality risk factors on the egg grade is performed to form output quality risk factor influence relationship information, including: taking the breeding analysis period as the data extraction basis, establishing the high-grade egg quantity percentage and the high-grade quality influence relationship of different output quality risk factor parameter quantities under each breeding analysis period , wherein: n represents the number of different output quality risk factors influencing the high-grade egg output, represents the influence coefficient of the output quality risk factor corresponding to the number n in the high-grade quality influence relationship , represents the constant term in the high-grade quality influence relationship , represents the percentage of high-grade egg quantity; taking the breeding analysis period as the data extraction basis, establishing the medium-grade egg quantity percentage and the medium-grade quality influence relationship of different output quality risk factor parameter quantities under each breeding analysis period , wherein: m represents the number of different output quality risk factors influencing the medium-grade egg output, represents the medium-grade quality influence relationship , represents the influence coefficient of the output quality risk factor corresponding to the number m in the medium-grade quality influence relationship a constant term in the low-grade quality impact relationship; the low-grade egg quantity percentage and the different output quality risk factor parameter quantity in each breeding analysis period are extracted as data, and a low-grade quality impact relationship is established wherein: k represents the number of different output quality risk factors affecting the production of low-grade eggs, represents the impact coefficient of the output quality risk factor numbered k in the low-grade quality impact relationship in the low-grade quality impact relationship represents the impact coefficient of the output quality risk factor numbered k in the low-grade quality impact relationship a constant term in the low-grade quality impact relationship; wherein, for the low-grade quality impact relationship the medium-grade quality impact relationship and the high-grade quality impact relationship , there are in the same breeding analysis period.

[0041] The analysis of the risk control factors affecting the output quality obtains the impact relationship information of the risk control factors affecting the output quality. It can be understood that for different grades of eggs, from low-grade to high-grade, the proportion of low-grade eggs in each output period is controlled by basic breeding parameters, and for medium-grade and high-grade eggs, independent other risk control factors are added on the basis of the risk control factors corresponding to low-grade eggs to expand the single output proportion. Therefore, for the risk control factors corresponding to low-grade quality, the risk control factors corresponding to medium-grade quality and the risk control factors corresponding to high-grade quality, these risk control factors are relatively independent, and only affect the corresponding egg grade. Of course, for the risk control factors affecting the same grade of egg quality, since the egg quality is based on multiple factors, when determining the grade impact relationship, a reasonable impact relationship is established by using big data to analyze the impact of multiple factors. In addition, it should be noted that the risk control factors affecting the quality of low-grade eggs are also necessary factors for the subsequent production of medium-grade and high-grade quality eggs, but the control and adjustment of these necessary factors cannot increase the output proportion of medium-grade and high-grade quality eggs, that is, the adjustment of these necessary factors only causes whether to lay eggs or to produce low-grade eggs, and on the basis of laying eggs or producing low-grade eggs, more reasonable impact relationships are formed by analyzing and determining the risk control factors affecting the production of medium-grade and high-grade eggs.

[0042] According to the output yield control factor data, multi-factor change analysis is performed on the output yield risk factors affecting the change of the number of eggs to form output yield risk factor influence relationship information, including: taking the breeding analysis period as the data extraction basis, establishing the yield influence relationship between the number of eggs and different output yield risk factor parameter quantities in each breeding analysis period , wherein: i represents the number of different output yield risk factors, represents the influence coefficient of the output yield risk factor numbered i in the yield influence relationship , and represents the constant term in the yield influence relationship , and Q represents the total number of eggs; according to different yield influence relationships , all influence coefficients and constant terms in the yield influence relationship are determined.

[0043] The determination of the influence relationship between the risk control factors affecting the output yield and the output yield is based on the multi-factor analysis of the risk control factors affecting the output yield based on historical big data. It should be noted that for both the influence relationship between the output quality and the corresponding risk control factors and the influence relationship between the output yield and the corresponding risk control factors, since the amount of big data is huge, there are redundant data when determining the corresponding influence coefficients and constant terms, so the corresponding influence coefficients and constant terms can be determined by grouping and establishing a relationship respectively and then averaged fitting, or the data can be reasonably screened to establish a relationship to determine the corresponding influence coefficients and constant terms.

[0044] As a possible implementation, the output quality risk factor influence relationship information and the output yield risk factor influence relationship information are combined to form a breeding output risk control model, including: according to the low-grade quality influence relationship and the yield influence relationship , a low-grade breeding output risk control model is determined: , wherein represents the total amount of low-grade breeding output; according to the medium-grade quality influence relationship and the yield influence relationship , a medium-grade breeding output risk control model is determined: , wherein represents the total amount of medium-grade breeding output; according to the high-grade quality influence relationship and the yield influence relationship , a high-grade breeding output risk control model is determined: , wherein Indicates the total amount of high-grade farming output.

[0045] The farming output risk control model is established based on different grades to ensure the rationality of the model and provide more reasonable basic data for subsequent risk analysis of different grade egg demand.

[0046] S2: Collect market farming price data of laying hens, and analyze the price trend of farming output by combining the farming output risk control model to form the information of the price trend change of egg output.

[0047] Collect market farming price data of laying hens, and analyze the price trend of farming output by combining the farming output risk control model to form the information of the price trend change of egg output, including: determining the change trend of the cost of different output quality risk factors of different grades in the time dimension according to the market farming price data, and periodically fitting to form the unit cost periodic change trend of output quality risk factors , wherein e takes n, m, k; determining the change trend of the cost of different output quantity risk factors in the time dimension according to the market farming price data, and periodically fitting to form the unit cost periodic change trend of output quantity risk factors ; determining the change trend of the price of different grade eggs in the time dimension according to the market farming price data, and periodically fitting to form the unit price periodic change trend of output grade , wherein g takes low, middle, and high.

[0048] The risk control model is only to establish the relationship between the risk control factors and the output quality and output quantity, and for the breeding of laying hens, the risk ultimately reflects on the return on investment, so it is more intuitive to evaluate the risk of investment return, and it is necessary to analyze the economic factors affecting the investment return. Here, all risk control factors in the breeding process, including all risk control factors affecting output quality and output quantity, are determined based on the change trend in time dimension. Of course, it is also necessary to analyze the change trend in time dimension of the price of different grades of eggs, which determines the total sales and is an important parameter affecting the return profit. It should be noted that whether the cost of the risk control factors affecting the output quality and output quantity or the price of different grades of eggs belongs to the part of the market behavior of breeding, and the change trend in time dimension also has market characteristics. Based on the characteristics of supply and demand in the market, the change of these cost prices has regularity. The fitting of the change trend of the same factors in different periods based on the breeding cycle can reasonably and accurately form the prediction of the change rule of the factor cost in the period breeding.

[0049] S3: Obtain breeding output requirement information and collect real-time breeding data, combine the breeding output risk control model and the egg output price trend change information, and perform risk identification of breeding output to form breeding output risk identification data.

[0050] Obtain breeding output requirement information, combine the breeding output risk control model and the egg output price trend change information, and perform risk identification of breeding output to form breeding output risk identification data, including: determining the required number of high-grade eggs and the corresponding high-grade output demand ratio , the required number of medium-grade eggs and the corresponding medium-grade output demand ratio , the required number of low-grade eggs and the corresponding low-grade output demand ratio , and the demand deadline according to the breeding output requirement information; taking the high-grade output demand ratio and the medium-grade output demand ratio as a reference, performing parameter quantity control adjustment of the corresponding output quality risk factors, and performing the following analysis and judgment: if the parameter quantity control adjustment of different output quality risk factors achieves the high-grade output demand ratio and the medium-grade output demand ratio , then according to the demand deadline and the change trend of the unit cost of different output quality risk factors , determine the output quality estimated total cost of the cost minimum value combination of the value combination of different output quality risk factors , and according to the required number of high-grade eggs the number of medium-grade eggs required and the number of low-grade eggs required and the yield impact relationship in combination with the different output yield risk factor unit cost periodic change trend and the different output grade unit price periodic change trend determines the total estimated cost of the output quantity and the total estimated sales of the output determines the total estimated cost of the output quality the total estimated cost of the output quantity and the total estimated sales of the output determines the estimated profit of the output wherein: if the parameter quantity control adjustment for different output quality risk factors cannot achieve the high-grade output demand proportion and the medium-grade output demand proportion , then the quality and quantity of the output are adjusted to estimate the estimated profit of the output ; a profit acceptance rate threshold is set , and based on the estimated profit of the output obtained , the total estimated cost of the output quality and the total estimated cost of the output quantity , the following risk identification analysis is performed: when , the controllable profit risk identification information is formed; when , the non-controllable profit risk identification information is formed; when , the loss risk identification information is formed.

[0051] The requirements of egg production are the conditions that need to be met, based on these conditions combined with risk control model and egg price trend information for risk identification analysis, can accurately determine the return on investment for breeding requirements whether there is a return on risk. It can be understood that in the risk identification, the best state is to adjust the risk control factors, so as to realize the satisfaction of output quality and output quantity demand. In this case, the number of eggs just meets the demand without excess, after all, although there are market prices for excess eggs, the cost of risk control factors has a wide and large impact. For the case that cannot be satisfied by adjusting the risk control factors, the minimum cost consumption principle is considered for reasonable estimation, which can realize the risk identification of this case. Of course, after obtaining the corresponding estimated profit, it is not considered as no risk as long as there is profit, it is necessary to consider the uncertainty of risk assessment and consider the actual possible sudden impact on output, so the risk identification is based on the estimated profit to make a reasonable judgment within a certain threshold height boundary, and the profit acceptance threshold can be set according to the actual situation, or it can be determined based on big data analysis.

[0052] If the parameter quantity control adjustment of different output quality risk factors cannot achieve high level output demand ratio and medium level output demand ratio , the quality and quantity of output adjustment estimation is carried out to determine the output estimated profit , including: taking the medium level output demand ratio as the reference to determine the corresponding maximum allowed high level output demand ratio under the condition of meeting the medium level output demand ratio , and according to the high level egg demand quantity , combined with the medium level breeding output risk control model , high level breeding output risk control model , medium level output demand ratio and maximum allowed high level output demand ratio , the necessary quantity of medium level eggs and the necessary quantity of low level eggs to meet the high level egg demand quantity are determined; according to the medium level output demand ratio and the maximum allowed high level output demand ratio , combined with the demand cutoff time and the unit cost period trend of different output quality risk factors , the output quality estimated total cost of the cost minimum value combination of the value combination of different output quality risk factors is determined , and according to the high level egg demand quantity The relationship between the necessary quantity of medium-grade eggs and the necessary quantity of low-grade eggs and the yield impact , combined with different output yield risk factor unit cost period trend and different output grade unit price period trend , determine the total cost of output quantity estimation and the total sales of output estimation , according to the total cost of output quality estimation , the total cost of output quantity estimation and the total sales of output estimation , determine the estimated profit of output , wherein: .

[0053] When there is no way to meet the output quality and output demand by adjusting the risk control factors, the risk identification estimate is estimated by considering adjusting the output yield and ensuring that the number of high-grade eggs just meets the required number. After all, the cost impact caused by the increase in the number of high-grade eggs is greater than the cost impact caused by the increase in the number of medium-grade eggs. The higher the grade of the eggs, the higher the cost consumed by the output, and the gap between this cost and the corresponding market price will be smaller than that of low-grade eggs, so the profit will be relatively reduced. Therefore, the adjustment is made with reference to the requirement of just meeting the number of high-grade eggs.

[0054] S4: According to the breeding output risk identification data, the breeding risk disposal is carried out, and the breeding risk disposal result data is formed.

[0055] According to the breeding output risk identification data, the breeding risk disposal is carried out, and the breeding risk disposal result data is formed, including: when the risk identification result shows controllable profit risk identification information, output not disposal information; when the risk identification result shows non-controllable profit risk identification information, output profit risk warning information and warning profit rate ; when the risk identification result shows loss risk identification information, output production loss warning information and loss rate .

[0056] After completing the risk identification, the identified risks need to be processed and warned. For controllable profit risk identification information, the profit is controllable, there is a stable return condition, so it is a positive breeding investment signal. For non-controllable profit risk identification information, although there are conditions to obtain profit, the actual profit may be affected to a large extent, and it needs to be treated with caution. For loss risk identification information, it can be sure that the investment to meet the breeding requirements this time is loss-making.

[0057] In summary, the breeding risk simulation and evaluation method of the laying hen breeding system based on the risk control engine provided by the embodiment of the application has the following beneficial effects:

[0058] The method analyzes risk factors affecting output quality and output quantity based on historical breeding data of laying hens, and establishes a risk influence model of risk factors relative to output quality and output quantity. Meanwhile, risk identification affecting output cost and sales price is performed based on the risk influence model and breeding output requirements, so that the risk size of possible return profit can be reasonably identified before breeding investment is made, and reasonable risk treatment is taken in a timely manner for the breeding investment, thereby effectively avoiding breeding losses.

[0059] In the embodiments of the present application, "indication" can include direct indication and indirect indication, and can also include explicit indication and implicit indication. The information indicated by a certain information is referred to as to-be-indicated information, and in the specific implementation process, there are many ways to indicate the to-be-indicated information, for example but not limited to, the to-be-indicated information can be directly indicated, such as the to-be-indicated information itself or an index of the to-be-indicated information. The to-be-indicated information can also be indirectly indicated by indicating other information, where the other information and the to-be-indicated information have an association relationship. The to-be-indicated information can also be indicated only in part, and the other part of the to-be-indicated information is known or agreed in advance. For example, the indication of a specific information can also be achieved by means of the arrangement order of various information agreed in advance (for example, a protocol), thereby reducing the indication overhead to a certain extent. At the same time, the common part of various information can be identified and indicated uniformly, so as to reduce the indication overhead caused by separately indicating the same information.

[0060] In addition, the specific indication method can also be various existing indication methods, for example but not limited to, the above-mentioned indication methods and various combinations thereof. The specific details of various indication methods can refer to the prior art, and will not be described herein. As described above, when multiple information of the same type needs to be indicated, the indication methods of different information can be different. In the specific implementation process, the required indication method can be selected according to the specific needs, and the selected indication method is not limited in the embodiments of the present application, so that the indication method involved in the embodiments of the present application should be understood as covering various methods that can enable the to-be-indicated party to know the to-be-indicated information.

[0061] It should be understood that the to-be-indicated information can be sent as a whole or sent separately in multiple sub-information, and the transmission period and / or transmission opportunity of the sub-information can be the same or different. The specific transmission method is not limited in the embodiments of the present application. The transmission period and / or transmission opportunity of the sub-information can be pre-defined, for example, pre-defined according to a protocol, or configured by the sending end device by sending configuration information to the receiving end device.

[0062] "predefined" or "preconfigured" can be implemented by pre-storing corresponding codes, tables or other means for indicating relevant information in the device, and embodiments of the present application do not limit the specific implementation manner. The "storing" can mean storing in one or more memories. The one or more memories can be separately arranged or integrated in the encoder or decoder, processor or communication device. The one or more memories can be partially separately arranged and partially integrated in the decoder, processor or communication device. The type of the memory can be any form of storage medium, and embodiments of the present application do not limit this.

[0063] The "protocol" involved in embodiments of the present application can refer to a protocol family in the communication field, a standard protocol similar to the protocol family frame structure, or a related protocol applied to a future communication system, and embodiments of the present application do not limit this.

[0064] In embodiments of the present application, "when", "in the case of", "if" and the like all refer to that the device will make corresponding processing under certain objective conditions, and are not limited in time, and do not require the device to have a judgment action when implemented, nor mean that there are other limitations.

[0065] In the description of the embodiments of the present application, unless otherwise specified, " / " represents that the objects before and after the " / " are in an "or" relationship, for example, A / B can represent A or B; "and / or" in the embodiments of the present application is only a description of the association relationship of the associated objects, which means that there can be three relationships, for example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone, wherein A and B can be singular or plural. In addition, in the description of the embodiments of the present application, unless otherwise specified, "multiple" means two or more than two. "At least one of the following" or the like means any combination of the items, including any combination of single item or multiple items. For example, at least one of a, b or c can represent: a, b, c, a-b, a-c, b-c, or a-b-c, wherein a, b, and c can be single or multiple. In addition, in order to clearly describe the technical solutions of the embodiments of the present application, in the embodiments of the present application, "first", "second", and the like are used to distinguish the same items or similar items with basically the same function and role. Those skilled in the art can understand that "first", "second", and the like do not limit the quantity and execution order, and "first", "second", and the like do not necessarily mean different. At the same time, in the embodiments of the present application, "exemplary" or "for example" means to serve as an example, illustration or description. Any embodiment or design scheme described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as more preferred or more advantageous than other embodiments or design schemes. Rather, "exemplary" or "for example" is used to present the relevant concept in a specific manner, for understanding.

[0066] It should be understood that the processor in the embodiments of the present application can be a central processing unit (CPU), and the processor can also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor.

[0067] It should also be understood that the memory in the embodiments of the present application can be a volatile memory or a nonvolatile memory, or can include both volatile and nonvolatile memory. Among them, the nonvolatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM) or a flash memory. The volatile memory can be a random access memory (RAM) used as an external cache. By way of example, and not limitation, a number of forms of random access memory (RAM) can be used, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchlink DRAM (SLDRAM), and direct Rambus RAM (DR RAM).

[0068] The above-described embodiments can be implemented in whole or in part by software, hardware (such as a circuit), firmware, or any combination thereof. When implemented in software, the above-described embodiments can be implemented in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions described in the embodiments of the present application are wholly or partially generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center through a wired (such as infrared, wireless, microwave, etc.) manner. The computer-readable storage medium can be any available medium accessible by a computer or a data storage device such as a server, data center, etc. containing one or more available medium collections. The available medium can be a magnetic medium (such as a floppy disk, a hard disk, a magnetic tape), an optical medium (such as a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state disk.

[0069] It should be understood that the term "and / or" herein merely describes an association relationship of associated objects, which means that there can be three relationships, for example, A and / or B can represent the following three cases: A exists alone, A and B exist together, and B exists alone, where A and B can be singular or plural. In addition, the character " / " herein generally represents an "or" relationship between the associated objects before and after it, but it can also represent an "and / or" relationship, which can be understood according to the context before and after it.

[0070] In this application, "at least one" means one or more, and "multiple" means two or more. "At least one of the following" or similar expressions means any combination of these items, including any combination of single item or multiple items. For example, at least one of a, b, or c can represent a, b, c, a-b, a-c, b-c, or a-b-c, where a, b, and c can be single or multiple.

[0071] It should be understood that in various embodiments of the present application, the size of the sequence number of the above-described processes does not mean the order of execution, and the execution order of the processes should be determined according to their functions and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0072] Those skilled in the art can clearly understand that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be realized by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0073] Those skilled in the art can clearly understand that, for the convenience and brevity of the description, the specific working processes of the above-described system, device and unit can refer to the corresponding processes in the foregoing method embodiments, which will not be repeated here.

[0074] In several embodiments provided in the present application, it should be understood that the disclosed system, device and method can be implemented in other ways. For example, the above-described device embodiments are only schematic, for example, the division of the units is only a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units shown or discussed can be indirect coupling or communication connection through some interface, device or unit, and can be electrical, mechanical or other forms.

[0075] The units described as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, that is, they can be located in one place, or can be distributed on a plurality of network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.

[0076] In addition, each functional unit in each embodiment of the present application can be integrated into a processing unit, or each unit can exist physically independently, or two or more units can be integrated into one unit.

[0077] If the functions are implemented in the form of software function units and sold or used as independent products, they can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application essentially or the parts that contribute to the prior art or parts of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0078] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or replacements within the technical scope disclosed in the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for simulating and assessing the breeding risks of an egg-laying hen farming system based on a risk control engine, characterized in that, include: Collect historical data on laying hen farming and conduct risk factor analysis on output quality based on farming costs to develop a farming output risk control model: Using the output of a single item as the breeding analysis cycle, the breeding quality control factors that affect the egg quality grade are extracted from the historical breeding data of the laying hens, forming the output quality control factor data; Using the output of a single item as the breeding analysis cycle, the breeding production control factors affecting the number of eggs in the historical breeding data of laying hens are extracted to form output production control factor data; A risk control analysis based on the impact of egg grade quantity was conducted on the output quality control factor data and the output yield control factor data to form the aquaculture output risk control model: Based on the output quality control factor data, all output quality risk factors affecting egg output quality were identified, and the impact of different output quality risk factors on egg grades was analyzed to form information on the influence relationships of output quality risk factors: Based on the aforementioned breeding analysis period, a relationship was established between the percentage of high-grade eggs and the influence of different output quality risk factor parameters on high-grade quality in each breeding analysis period. ,in: , where n represents the number of the different risk factors affecting the production quality of high-grade eggs. This indicates the high-level quality influence relationship. The influence coefficient corresponding to the output quality risk factor numbered n. This indicates the high-level quality influence relationship. The constant term in This indicates the percentage of high-grade eggs. This represents the output quality risk factor parameter quantity corresponding to the output quality risk factor numbered n; Based on the aforementioned breeding analysis period, a relationship was established between the percentage of medium-grade eggs and the influence of different output quality risk factor parameters on medium-grade quality in each breeding analysis period. ,in: 'm' represents the number of the different output quality risk factors affecting the production of medium-grade eggs. This indicates the influence relationship of the intermediate quality level. The influence coefficient corresponding to the output quality risk factor numbered m. This indicates the influence relationship of the intermediate quality level. The constant term in This indicates the percentage of medium-grade eggs. This represents the output quality risk factor parameter quantity corresponding to the output quality risk factor numbered m; Based on the aforementioned breeding analysis period, a relationship was established between the percentage of low-grade eggs and the impact of different output quality risk factor parameters on low-grade quality in each breeding analysis period. ,in: 'k' represents the number of the different output quality risk factors affecting the production of low-grade eggs. This indicates the low-level quality influence relationship. The influence coefficient corresponding to the output quality risk factor numbered k in the middle. This indicates the low-level quality influence relationship. The constant term in This indicates the percentage of low-grade eggs. This represents the output quality risk factor parameter quantity corresponding to the output quality risk factor numbered k; Among them, for the low-level quality influence relationship The relationship between the medium-level quality influence and the aforementioned high-level quality influence relationship Within the same aquaculture analysis period, there are ; Based on the aforementioned output control factor data, a multi-factor change analysis was conducted on the risk factors affecting changes in egg quantity, resulting in information on the influence relationships of these risk factors: Based on the aforementioned breeding analysis period as the data extraction basis, the relationship between the number of eggs and the output risk factor parameters under different output risk factors in each breeding analysis period is established. ,in: , where i represents the number of the risk factor for different output levels. Indicates the relationship of output influence The influence coefficient corresponding to the output risk factor numbered i in the middle. Indicates the relationship of output influence The constant term in the equation, Q, represents the total number of eggs. This indicates the output quality risk factor parameter quantity corresponding to the output quality risk factor numbered i; According to different production impact relationships Determine the relationship of the impact on output. All influence coefficients and constant terms; The aquaculture output risk control model is formed by combining the information on the influence relationships of the output quality risk factors and the information on the influence relationships of the output yield risk factors. Collect market price data for egg-laying hens and combine it with the aforementioned risk control model for breeding output to analyze the price trend of breeding output and generate information on changes in egg-laying hen output price. Information on breeding output requirements is obtained, and real-time breeding data is collected. Combined with the breeding output risk control model and the information on the trend change of egg production price, the risk of breeding output is identified, and breeding output risk identification data is formed. Based on the identified aquaculture output risks, aquaculture risk management is carried out to generate aquaculture risk management result data.

2. The method for simulating and assessing the breeding risk of egg-laying chicken farming systems based on a risk control engine, as described in claim 1, is characterized in that... Combining the information on the influence relationships of the risk factors on output quality and the information on the influence relationships of the risk factors on output yield, the aquaculture output risk control model is formed, including: Based on the influence relationship of low-level quality and the relationship with the aforementioned output A risk control model for low-level aquaculture output was determined. : ,in, This indicates the total output of low-level aquaculture. Based on the influence of intermediate quality and the relationship with the aforementioned output A risk control model for medium-level aquaculture output was determined. : ,in, This indicates the total output of medium-grade aquaculture; Based on the influence relationship of high-level quality and the relationship with the aforementioned output A high-level aquaculture output risk control model was established. : ,in, This indicates the total output of high-level aquaculture.

3. The method for simulating and assessing the breeding risk of egg-laying chicken farming systems based on a risk control engine, as described in claim 2, is characterized in that... The process involves collecting market price data for egg-laying hens and combining it with the aforementioned risk control model for egg production to analyze price trends and generate information on changes in egg-laying hen output prices, including: Based on the market aquaculture price data, the cost trends of different output quality risk factors at different levels are determined over time, and periodic fitting is performed to form the periodic trend of unit cost changes of output quality risk factors. Where e takes the values ​​n, m, and k; Based on the market aquaculture price data, the changing trends of the costs of different output risk factors over time are determined, and periodic fitting is performed to form the periodic changing trend of the unit cost of output risk factors. ; Based on the aforementioned market breeding price data, the price trends of eggs of different grades over time are determined, and periodic fitting is performed to form a periodic trend of unit price change for each output grade. , where g represents low, middle, and high.

4. The method for simulating and assessing the breeding risk of egg-laying chicken farming systems based on a risk control engine, as described in claim 3, is characterized in that... The process involves acquiring information on livestock output requirements, combining it with the livestock output risk control model and the information on the trend changes in egg production prices, to identify risks in livestock output and generate livestock output risk identification data, including: Based on the aforementioned aquaculture output requirements, the required quantity of high-grade eggs is determined. and the corresponding high-level output demand ratio Medium-grade eggs required and the corresponding mid-level output demand ratio The demand for low-grade eggs and the corresponding low-level output demand ratio and the deadline for the request; Based on the aforementioned high-level output demand ratio and the aforementioned medium-level output demand ratio For reference, adjust the parameter control of the corresponding output quality risk factors, and conduct the following analysis and judgment: If the parameter control and adjustment of different output quality risk factors can achieve the required proportion of high-level output, then the desired output ratio can be obtained. and the aforementioned medium-level output demand ratio Then, based on the demand deadline and the cyclical change trend of unit cost for different output quality risk factors, Determine the total estimated cost of the output quality prediction combination that minimizes the cost among different combinations of output quality risk factors. And according to the required quantity of the high-grade eggs The required quantity of medium-grade eggs and the required quantity of the low-grade eggs and the aforementioned production impact relationship Combining the different output risk factors and the cyclical change trend of unit cost and the cyclical trend of unit price changes for different output levels. Determine the output quantity and estimate the total cost. and estimated total sales The total cost is estimated based on the output quality. The estimated total cost of the output quantity and the estimated total sales of the output Determine the estimated output profit ,in: ； If adjusting the parameters of different output quality risk factors cannot achieve the required proportion of high-level output, then... and the aforementioned medium-level output demand ratio Then, adjust the output quantity forecast to ensure quality and quantity, and determine the output forecast profit. ; Set a profit acceptance threshold Based on the obtained output, the estimated profit is... The estimated total cost of the output quality and the estimated total cost of the output quantity. The following risk identification analysis was conducted: when This forms information for identifying profit control risks; when This forms information for identifying uncontrollable profit risks; when This will generate information for identifying the risk of loss.

5. The method for simulating and assessing the breeding risk of egg-laying chicken farming systems based on a risk control engine, as described in claim 4, is characterized in that... If adjusting the parameters of different output quality risk factors fails to achieve the required proportion of high-level output, then... and the aforementioned medium-level output demand ratio Then, adjust the output quantity forecast to ensure quality and quantity, and determine the output forecast profit. ,include: Based on the aforementioned medium-level output demand ratio For reference, determine the proportion required to meet the intermediate-level output. The corresponding maximum allowable high-level output requirement ratio And according to the required quantity of the high-grade eggs Combined with the aforementioned medium-level aquaculture output risk control model The high-level aquaculture output risk control model The aforementioned medium-level output demand ratio and the maximum allowable high-level output requirement ratio Determine the quantity required to meet the high-grade egg demand. The required quantity of medium-grade eggs and the required quantity of low-grade eggs; Based on the aforementioned medium-level output demand ratio and the maximum allowable high-level output requirement ratio Combining demand deadlines with the cyclical changes in unit cost due to different output quality risk factors, Determine the total estimated cost of the output quality prediction combination that minimizes the cost among different combinations of output quality risk factors. And according to the required quantity of the high-grade eggs The necessary quantity of medium-grade eggs and the necessary quantity of low-grade eggs, and their impact on production. Combining the different output risk factors and the cyclical change trend of unit cost and the cyclical trend of unit price changes for different output levels. Determine the output quantity and estimate the total cost. and estimated total sales The total cost is estimated based on the output quality. The estimated total cost of the output quantity and the estimated total sales of the output Determine the estimated output profit ,in: 。 6. The method for simulating and assessing the breeding risk of an egg-laying hen breeding system based on a risk control engine, as described in claim 5, is characterized in that... The process of handling aquaculture risks based on the identified aquaculture output risks and generating aquaculture risk handling result data includes: When the risk identification result shows the controllable profit risk identification information, then no action will be taken. When the risk identification result shows the uncontrollable profit risk identification information, then the profit risk warning information and the warning profit rate are output. ; When the risk identification result shows the aforementioned loss risk identification information, then the production loss early warning information and loss rate are output. .

Images