Cattle herd benefit measurement and calculation process evaluation method oriented to cattle herd raw material proportioning task

Abstract

The invention discloses a cattle herd benefit measurement and calculation process evaluation method oriented to a cattle herd raw material matching task, and relates to the technical field of cattle herd benefit measurement and calculation management. The method is realized through the following steps: quantifying the real-time demand condition of cattle feeding data measurement and calculation to reflect the transmission condition of cattle feeding related information, and determining cattle benefit information and an optimal cattle raw material ratio according to the real-time demand of cattle feeding data measurement and calculation.

Description

Technical Field

[0001] This invention relates to the field of cattle herd benefit measurement and management technology, and in particular to a method for evaluating the cattle herd benefit measurement process for cattle herd feed ratio tasks. Background Technology

[0002] Cattle farming requires scientific, precise, cost-effective, and feasible raw material formulation decision-making solutions. To achieve the comprehensive goals of controllable farming costs, precise nutrient supply, optimal farming efficiency, and sufficient decision-making basis, existing technologies approach the issue through the following process: First, multi-source data (feeding data and market raw material price data, etc.) are simultaneously collected and integrated to obtain the data to be calculated, covering individual cattle production performance, precise nutritional components of feed ingredients, and real-time market prices. Based on this, the nutritional-cost cost-effectiveness of each ingredient is calculated, laying the data foundation for optimizing the formulation. Next, the core formulation model is constructed and solved. Using mathematical optimization techniques such as linear programming, with the objective function of minimizing total cost or maximizing benefits, the theoretically optimal raw material formulation is calculated under strict constraints such as meeting the herd's nutritional needs, raw material supply limitations, and formula structure. Finally, a comprehensive quantitative evaluation of the benefits is conducted based on the obtained optimal formula. This includes not only calculating direct economic benefits (such as pasture raw material costs and input-output ratio), but also comprehensively evaluating the benefits to the herd. Specifically, this is reflected in the expected performance of key health and production indicators such as weight gain efficiency, nutrient digestibility, milk yield, and milk quality. This provides a multi-dimensional basis for decision-making regarding the feasibility and superiority of the formula, achieving a closed loop from data to decision.

[0003] For example, Chinese invention patent CN112418607B discloses a method for optimizing a multi-component compound pelleted feed formulation, which includes: constructing a system model and calculating flow calculation models, starch gelatinization calculation models, nutrient composition calculation models, water and heat exchange calculation models, conditioned powder forming mechanics models, and relative nutrient composition calculation models of digested fecal products; determining information on raw material components and feed nutrient requirements; using an evolutionary genetic algorithm to optimize the feed formulation design; and using an optimization solution model to solve for the optimal pelleted feed component formulation.

[0004] For example, Chinese invention patent application CN117273265A discloses a beef cattle breeding analysis platform, which includes: a breeding analysis platform with eight modules: custom dashboards, herd structure management, basic information management, growth and development, reproduction management, calf management, breeding analysis, and custom analysis. The breeding analysis module is the core of the platform, containing functions such as conformation and appearance assessment, bull management analysis, genetic evaluation, and beef cattle selection index. This platform can retrieve pedigree data for each cow from three generations or more, data on various traits and growth and development at each stage, conformation and appearance assessment, reproduction, and bull information. Using this data, it calculates the genetic parameters and breeding values ​​of each trait at each stage of the cattle's life. Combining the marginal benefit weights of each trait, it constructs a beef cattle selection index, calculates the comprehensive breeding value of the cows, and selects cattle with high breeding values ​​to enter the core herd.

[0005] The above-mentioned technology has at least the following technical problems:

[0006] During the synchronous collection and integration of multi-source data, although the on-site ranch terminals (such as feeding terminals) have edge caching and breakpoint resume capabilities, the 5G / LoRa link may experience latency exceeding limits in environments such as high temperature and humidity, metal feed trough obstruction, and livestock collisions. For example, the shielding effect of the metal feed trough combined with the location obstruction may cause the link signal strength to fall below the base station's receiving limit. This results in the data to be measured not being able to be uploaded to the cloud in real time and having to be temporarily stored locally on the device. The data can only be synchronized after the fault is repaired and the link is restored. If the cached data to be measured falls outside the window, in the existing technology, due to the inadequacy of the caching mechanism in terms of timing compensation and backtracking calculation, it may only perform batch storage without triggering backtracking recalculation. At this stage, the data upload time may exceed the real-time window period threshold for benefit measurement, causing the data to be measured to be out of sync with the measurement process, forming a data breakpoint at the measurement level. This results in the data to be measured not being fed back to the measurement stage in real time, and the measurement may still be based on the original formula data for cattle benefit measurement, leading to the problem of low timeliness of the evaluation data in the cattle benefit measurement process for cattle herd raw material ratio tasks. Summary of the Invention

[0007] To address the technical problem of low timeliness in the evaluation data of cattle herd benefit calculation process for cattle herd feed ratio tasks in existing technologies, this invention provides an evaluation method for the cattle herd benefit calculation process for cattle herd feed ratio tasks. The technical solution is as follows:

[0008] This paper provides an evaluation method for the cattle herd benefit calculation process for cattle feed ratio tasks. The method includes: performing real-time analysis of cattle feeding data to output analysis results quantifying the real-time requirements for cattle feeding data calculation; determining whether to verify successful data upload based on the analysis results to reflect the qualified status of the uploaded data; if not, sending a prompt indicating that the real-time requirement for calculation is not met, and re-analyzing the real-time cattle feeding data calculation; if successful data upload verification, determining whether to conduct a pasture delay impact assessment based on the verification results to output assessment results reflecting pasture link delay; if a pasture delay impact assessment is conducted, determining whether to perform link stability verification based on the output assessment results to check for breakpoints in the data to be calculated; if successful, re-uploading cattle feeding data and automatically updating cattle benefit information and the optimal cattle feed ratio to maximize cattle benefit after successful verification; otherwise, directly performing calculation feedback to obtain cattle benefit information and the optimal cattle feed ratio.

[0009] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following:

[0010] 1. By conducting real-time analysis of cattle feeding data and determining whether to verify the successful upload of the data based on the analysis results, it helps to achieve pre-screening of data real-time performance, avoiding invalid calculations at the source and ensuring that all data entering the calculation stage meets the timeliness baseline. If the successful upload verification of the data to be calculated is not performed, a prompt indicating that the real-time calculation requirement is not met is sent, and the real-time analysis of cattle feeding data is re-performed. If the successful upload verification of the data to be calculated is performed, after the verification is completed, it is determined whether to conduct a pasture delay impact assessment based on the verification results. This helps to achieve layered verification of data validity, ensuring progressive protection at each level. The reliability assessment method involves determining whether to perform link stability verification based on the output assessment results if a pasture delay impact assessment is conducted. Otherwise, the assessment feedback is directly performed to obtain herd benefit information reflecting the herd's profitability. This helps to achieve dynamic closed-loop optimization of the assessment process, improve data timeliness management efficiency, and realize accurate and real-time decision-making for herd feed ratios. This provides data support for scientific farming and improves the timeliness of assessment data for herd benefit assessment in herd feed ratio tasks. This solves the problem of low timeliness of assessment data for herd benefit assessment in herd feed ratio tasks in existing technologies.

[0011] 2. By verifying the successful upload of the data to be measured, the system obtains the upload verification result. When the upload verification result is not greater than the preset qualified upload result, the system initiates the upload and measurement failure interference judgment and determines whether to optimize the farm's delayed upload based on the judgment result. Compared with existing technologies that can only judge the success or failure of the upload and cannot quantify the upload quality, this system helps to achieve accurate attribution and hierarchical processing of data upload failures. This helps to strengthen the stability of the data upload link and ensure the reliability of cattle herd benefit measurement, supporting the dynamic adjustment and precise management of cattle herd feed ratios.

[0012] 3. When the average impact value of non-compliant uploads meets the upload qualification conditions and the cattle feeding data calculation requirement value meets the feeding data calculation qualification conditions, a pasture delay impact assessment is performed. Based on the pasture delay impact assessment results, it is determined whether to perform link stability verification. Compared with existing technologies that often have problems with ambiguous trigger conditions or over-verification, this mechanism helps to achieve accurate triggering of pasture delay impact assessment through "dual-condition collaborative judgment", avoids the waste of ineffective verification resources, and realizes the pre-emptive risk screening of pasture delay impact, reducing the probability of measurement result deviation.

[0013] 4. When there are small-batch retransmissions of data, such as livestock briefly colliding with the pasture terminal or metal feed troughs temporarily obstructing the pasture, the impact of pasture delay is assessed by monitoring the qualified entry value of the window. When the qualified entry value of the window is within the preset qualified entry range, the link stability is verified. Compared with the existing technology that over-processes and ignores the potential link instability hidden by frequent small-batch retransmissions, this mechanism achieves scenario-based judgment by monitoring the qualified entry value of the window. This helps to achieve accurate scenario identification of small-batch retransmission scenarios, avoids over-processing or risk omission, and ensures the continuity of the calculation process.

[0014] 5. By verifying the stability of the feed chain, and when the quantitative value of the feed chain stability deviation is within the preset acceptable range of feed chain stability deviation, calculation feedback is performed to obtain the optimal feed ratio and feed chain benefit information for cattle. Compared with the existing technology, which has vague stability judgment and calculation feedback that is disconnected from the feed chain status, this mechanism helps to achieve quantitative assessment of feed chain stability, ensures that the calculation feedback process is based on "stable feed chain data", and thus ensures the reliability of feed chain ratio decisions for cattle and the stability of feed chain benefits. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a flowchart of the cattle herd benefit calculation and evaluation method provided in this embodiment of the invention for cattle herd raw material ratio tasks;

[0017] Figure 2 This is a general overview diagram of the cattle herd benefit calculation process evaluation method for cattle herd raw material ratio tasks provided in the embodiments of the present invention;

[0018] Figure 3 This is a schematic diagram of the farm delay upload optimization of the cattle herd benefit calculation process evaluation method for cattle herd raw material ratio task provided in the embodiments of the present invention;

[0019] Figure 4 This is a schematic diagram of the farm delay upload anomaly assessment in the cattle herd benefit calculation process evaluation method for cattle herd raw material ratio tasks provided in this embodiment of the invention;

[0020] Figure 5 This is a diagram of the ranch benefit assessment interface of the cattle herd benefit calculation process evaluation method for cattle herd raw material ratio tasks provided in this embodiment of the invention. Detailed Implementation

[0021] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0022] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0023] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning.

[0024] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0025] This invention provides an evaluation method for the process of calculating cattle herd benefits for tasks related to feed formulation. For example... Figure 1The flowchart shown illustrates the evaluation method for calculating cattle herd benefits for the task of feed formulation. The processing flow of this method may include the following steps:

[0026] S01 Real-time Demand Monitoring: During the cattle herd benefit calculation process, real-time analysis of cattle feeding data is performed to output analysis results that quantify the real-time demand for cattle feeding data calculation. Based on the analysis results, it is determined whether the data to be calculated has been successfully uploaded, reflecting the qualified status of the uploaded data. By conducting real-time demand monitoring, it is helpful to accurately define the timeliness baseline of cattle feeding data calculation and intercept risks in advance, avoiding the input of lagging data into subsequent processes, intercepting the risk of "using expired data for invalid calculations" from the source, and laying the first layer of protection for the timeliness of the calculation results.

[0027] S02 Upload Success Verification Monitoring: If the upload success verification of the data to be measured is not performed, a prompt indicating that the real-time measurement requirement is not met will be sent, and the real-time analysis of the cattle feeding data will be re-performed. If the upload success verification of the data to be measured is performed, after the verification is completed, a determination will be made based on the verification results to determine whether to conduct a pasture delay impact assessment, so as to output an assessment result reflecting the pasture link delay situation. By performing upload success verification monitoring, it is helpful to fully confirm the physical validity of the data to be measured and accurately locate the upload problem, avoid blindly re-uploading, improve the efficiency of problem solving, and lay a second layer of protection for the validity of the measurement results.

[0028] S03 Link Stability Verification and Monitoring: If a pasture delay impact assessment is conducted, the link stability verification is determined based on the output assessment results to check for breakpoints in the data to be measured. If the verification is successful, the herd feeding data is retransmitted and the herd benefit information reflecting the herd's profitability and the optimal herd feed ratio reflecting the maximization of herd benefits are automatically updated. Otherwise, the calculation feedback is directly performed to obtain herd benefit information and the optimal herd feed ratio. By conducting link stability verification and monitoring, it is helpful to achieve in-depth investigation of hidden risks in pasture data transmission links and ensure data continuity, ensuring that the data is "continuous and distortion-free," laying a third layer of protection for the reliability of the calculation results.

[0029] It should be added that, prior to the design of the cattle herd benefit calculation process evaluation method for cattle herd feed ratio task provided in this application, a database for storing various set data was established. The database includes, but is not limited to, preset cattle herd feeding data calculation requirements and preset data upload time.

[0030] The various numerical values ​​are directly set by technicians. These data are key parameters in the cattle herd benefit calculation process. Each value is set directly by technicians based on their professional knowledge, practical breeding experience, and the specific conditions of the cattle herd, ensuring the accuracy and relevance of the data. This database uses a relational database management system (such as MySQL or Oracle) to store different types of data according to a pre-designed table structure. The database is equipped with a dynamic calibration model based on ranch size, cattle herd type, and geographical environment. This model uses the basic parameters set by technicians as a benchmark, combined with ranch size (such as...) The algorithm dynamically adjusts and calibrates basic parameters based on the differentiated characteristics of cattle, including large-scale ranches, small and medium-sized individual ranches, cattle stock range, and the level of supporting facilities; cattle herd type (e.g., dairy cattle, different breeds, different growth or lactation stages); and regional environment (e.g., north-south climate differences, temperature, humidity or altitude characteristics of the breeding area, and the types and supply capacity of local forage resources). For example, for fattening beef cattle in cold northern regions, the algorithm automatically increases the calculated demand values ​​of energy-related feeding data; for lactating dairy cows in hot and humid southern regions, the algorithm adapts and adjusts the calculation benchmarks of micronutrients and heat-prevention nutritional parameters.

[0031] like Figure 2 The diagram shown is an overall overview of the cattle herd benefit calculation and evaluation method for cattle herd feed ratio tasks provided in this application embodiment. Figure 2 It can be seen that: by performing real-time analysis of cattle feeding data, the required value for cattle feeding data calculation is obtained. When the monitored required value for cattle feeding data calculation does not meet the qualified conditions for feeding data calculation, a prompt indicating that the real-time calculation requirement is not met is sent. Otherwise, the successful upload verification of the data to be calculated is performed to obtain the verification result of the data upload. When the monitored verification result of the data upload is greater than the preset qualified upload result, calculation feedback is performed. Otherwise, the interference of upload and calculation failure is judged and it is determined whether to optimize the farm delay upload. If the farm delay upload is not optimized, calculation feedback is performed. Otherwise, after the farm delay upload optimization is completed, the farm delay impact assessment is performed. After the farm delay impact assessment is qualified (the average link delay impact characterization value is not greater than the preset link delay impact characterization value), the link stability verification and calculation feedback are performed.

[0032] In this embodiment, the combined and interconnected functions of real-time demand monitoring, upload success verification monitoring, and link stability verification monitoring help to achieve a three-dimensional risk control closed loop across the entire data chain for cattle herd benefit calculation. Real-time demand monitoring filters "timely and compliant data" for upload success verification monitoring, avoiding invalid data from occupying verification resources. Upload success verification monitoring filters "physically valid data" for link stability verification monitoring, thereby ensuring the accuracy of cattle herd benefit calculation results and the feasibility of optimal cattle herd feed ratios. This is conducive to improving the efficiency of breeding decisions and the level of refined farm management for cattle herd feed ratio tasks.

[0033] It should be further explained that, in order to achieve raw material value assessment, one approach is to replace feed ingredients, and another is to reduce raw material costs and thus improve feeding efficiency by regrouping cattle. For example, under the condition of consistent nutritional parameters, by replacing feed ingredients, such as replacing soybean meal with cottonseed meal in the formula adjustment, the key nutritional parameters of cottonseed meal feed, such as crude protein, lysine, and digestibility, can be on par with soybean meal. This meets the physiological needs of the cattle while improving the feeding efficiency. In other words, by selecting more cost-effective alternative raw materials, while ensuring that key nutritional indicators such as crude protein, lysine, and digestibility are not lower than the original formula, the unit feed cost can be directly reduced, while meeting the nutritional needs of cattle (such as lactating cows and fattening cows) at different physiological stages, ultimately improving feeding efficiency.

[0034] On the other hand, by transferring cattle herds, "on-demand supply of raw materials" can be achieved. This means that based on the differences in nutritional needs of different growth stages (such as calves, growing cattle, lactating cattle, and dry dairy cattle) or production status (such as high-producing cattle and low-producing cattle), the cattle herds are precisely divided into corresponding feeding units, and each unit is equipped with a dedicated raw material formula.

[0035] To provide a data foundation for raw material value assessment, a comprehensive data quality assurance system can be built, encompassing real-time demand monitoring, successful upload verification monitoring, and link stability verification monitoring. This system ensures data quality from timeliness and physical validity to reliable transmission, providing accurate, effective, and continuous underlying support for core data required for raw material value assessment (such as cattle feeding volume, raw material consumption costs, nutritional parameter matching degree, and cattle production efficiency). This ensures that the data used in the assessment is synchronized with the actual feeding scenario and is authentic and traceable, while also guaranteeing the integrity of the data chain without any breaks. Ultimately, this provides reliable data for core tasks such as "raw material replacement benefit calculation" and "cattle herd transfer cost optimization assessment," achieving accuracy and credibility in the raw material value assessment results.

[0036] Furthermore, the specific process for real-time analysis of cattle feeding data is as follows: Based on the amount of cattle feeding data generated by the ranch terminal, the cattle feeding data calculation demand value is obtained to reflect the real-time demand for cattle feeding data calculation; the amount of cattle feeding data generated by the ranch terminal and the total amount of data generated by the ranch terminal are monitored by a network traffic monitor within the preset feeding data calculation period, and the result of the ratio calculation is expressed as the cattle feeding data calculation demand value; it is determined whether the cattle feeding data calculation demand value meets the feeding data calculation qualification conditions. If it does, a real-time calculation demand compliance prompt is sent, and the corresponding data to be calculated is obtained for successful upload verification; otherwise, a real-time calculation demand non-compliance prompt is sent, and the real-time analysis of cattle feeding data calculation is performed again; the feeding data calculation qualification condition indicates that the cattle feeding data calculation demand value is greater than the preset cattle feeding data calculation demand value, where the preset cattle feeding data calculation demand value is represented by the average value of the cattle feeding data calculation demand values ​​over historical time periods.

[0037] It should be added that the specific process for verifying the successful upload of the data to be tested is as follows: The upload qualification of the data to be tested is evaluated based on the acquired upload time and the preset upload time, and the corresponding upload verification result is output. The upload qualification of the data to be tested is verified based on the upload verification result. If the upload verification result is greater than the preset qualified upload result, the corresponding data to be tested is marked as qualified data and a calculation feedback is provided. Conversely, the corresponding upload verification result is marked as unqualified, and an upload and calculation unqualified interference judgment is triggered to reflect the impact of the unqualified upload verification result on the upload qualification level. The upload verification result is represented by the difference between the preset upload time and the actual upload time. The upload time is monitored by a timer, and the time from the time the data to be tested is generated at the ranch terminal to the time it is successfully uploaded to the cloud server is used as the upload time. The preset upload time is represented by the average upload time of the data to be tested over a historical period.

[0038] In this embodiment, the required value for cattle feeding data calculation is obtained through real-time analysis of cattle feeding data. The larger the required value, the greater the effective proportion of cattle feeding data. Under the condition that the required value meets the qualified conditions for feeding data calculation, the upload of the data to be calculated is verified to obtain the upload verification result. From the two dimensions of data quality (effective proportion) and data accessibility (successful upload), a reliable data foundation is laid for subsequent calculations, avoiding invalid uploads. If the upload verification result of the data to be calculated is not greater than the preset qualified upload result, further judgment on upload and calculation failures is performed. This helps to accurately attribute the reasons for upload failures and solve differentiated problems, accurately locating the source of interference rather than blindly re-uploading. This improves problem-solving efficiency and avoids the recurrence of similar problems, achieving an upgrade from "passive processing to proactive prevention." The connection between the real-time analysis of cattle feeding data calculation and the successful upload verification of the data to be calculated helps to achieve a closed loop from data screening to upload verification and optimize resource allocation, ultimately improving the overall efficiency of the calculation process.

[0039] Furthermore, the specific process for determining the upload and measurement non-compliance interference is as follows: The non-compliance upload verification result and the required value for the cattle feeding data to be processed are input into a preset link stability impact table, outputting the impact value of the non-compliance upload level; the required value for the cattle feeding data to be processed represents the required value for the cattle feeding data that meets the feeding data measurement qualification conditions; a judgment is made based on the average impact value of the non-compliance upload level: if the average impact value of the non-compliance upload level meets the measurement upload qualification conditions, the corresponding data to be measured is marked as qualified measurement data, and measurement feedback is performed; otherwise, the corresponding data to be measured is marked as... Unqualified calculation data will be uploaded to the next adjacent preset pasture during the next preset pasture upload time period to optimize the pasture upload delay and avoid data interruptions caused by unqualified data uploads. The qualified upload condition means that the average impact value of unqualified uploads is within the preset unqualified upload impact range. The average unqualified upload impact value means the average of the unqualified upload impact values ​​obtained after performing a preset number of uploads and judging the interference of unqualified calculations. The preset pasture upload time period means the preset time period corresponding to the successful upload verification of the data to be calculated. The preset unqualified upload impact range is set in advance by preset personnel.

[0040] It should be explained that, in the embodiments of this application, preset data such as the preset link stability impact table, preset pasture power correlation table, preset calculated data retransmission matching table, preset beacon interval cycle correlation table, and preset secondary beacon interval cycle correlation table retrieved from the database are shown. These data contain dynamic mapping relationships. These mapping relationships are flexible, enabling both one-to-one mapping between single parameters and many-to-one mapping between multiple parameters and single parameters. The specific operation process is as follows: First, the combination of the unqualified upload verification results collected by preset personnel within the historical time period, the combination of the required value of the cattle feeding data to be processed, the combination of the required value of the cattle feeding data and the channel attenuation rate of the pasture terminal, the total number of unqualified first-level delay uploads, the combination of the required value of the cattle feeding data to be processed and the data loss rate to be calculated, the link delay impact characterization value, the combination of the required value of the cattle feeding data to be processed and the beacon frame of the pasture terminal, the link delay optimization verification value, and the combination of the required value of the cattle feeding data to be processed and the beacon frame of the pasture terminal are input into a machine learning model (such as a decision tree model) used to reflect the importance of features. By leveraging the model's feature splitting function, corresponding weights or data can be obtained, including the impact value of unqualified uploads, the incremental increase in transmit power, the number of retransmissions of the data to be measured, the preset beacon interval period decrease value, and the preset secondary beacon interval period decrease value. Then, the data from historical time periods are associated and paired with the corresponding weights or data to generate preset link stability impact tables, preset ranch power correlation tables, preset measured data retransmission matching tables, preset beacon interval period correlation tables, and preset secondary beacon interval period correlation tables, etc. Finally, the information collected in real time, including the combination of the non-compliant upload verification results and the required value of the cattle feeding data to be processed, the combination of the required value of the cattle feeding data and the channel attenuation rate of the pasture terminal, the total number of non-compliant first-level delay uploads, the combination of the required value of the cattle feeding data to be processed and the data loss rate to be calculated, the link delay impact characterization value, the combination of the required value of the cattle feeding data to be processed and the beacon frame of the pasture terminal, the link delay optimization verification value, and the combination of the required value of the cattle feeding data to be processed and the beacon frame of the pasture terminal, is input into the corresponding preset link stability impact table, preset pasture power correlation table, preset calculated data retransmission matching table, preset beacon interval period correlation table, and preset second-level beacon interval period correlation table. According to the preset mapping relationship, the output data includes the non-compliant upload impact value, the incremental value of the transmission power, the number of data retransmissions to be calculated, the incremental value of the preset beacon interval period, and the incremental value of the preset second-level beacon interval period, all within the range of 0-1.

[0041] like Figure 3The diagram shown illustrates the optimization of farm delay upload in the evaluation method for cattle herd benefit calculation process for cattle feed ratio tasks provided in this application embodiment. Figure 3 It can be seen that after prioritizing the cattle feeding data, the farm link strength is optimized for the farm terminals according to the sequence order corresponding to the incremental calculation demand value sequence. Based on the obtained incremental value of transmission power, the transmission power of the initial farm terminal is incremented. When the transmission power of the monitored farm terminal reaches the preset maximum transmission power, the impact value of the unqualified upload degree still does not meet the calculation upload qualification conditions, and the farm delay upload anomaly assessment is performed.

[0042] Specifically, the ranch delay upload optimization includes sequential priority sorting of cattle feeding data to prioritize core ranch terminals when link optimization resources are limited, and ranch link strength optimization to enhance ranch link signal strength. This helps to achieve accurate allocation of link resources and improve transmission efficiency, ensuring that link resources are tilted towards high-value data and guaranteeing the reliability of core data upload. Cattle feeding data priority sorting means sorting the cattle feeding data calculation demand values ​​to be processed in an ascending order to obtain an ascending calculation demand value sequence, which helps to achieve efficient utilization of link optimization resources and avoid indiscriminate investment.

[0043] The specific process of optimizing the pasture link strength is as follows: Following the sequence order corresponding to the incrementally calculated demand value sequence (the incrementally calculated demand value sequence increases sequentially from smallest to largest, prioritizing the pasture terminal corresponding to the largest cattle feeding data demand value), the pasture link strength of the pasture terminal is optimized. The cattle feeding data demand value and the channel attenuation rate of the pasture terminal monitored by the vector network analyzer are input into a preset pasture power correlation table. The incremental value of the pasture terminal's transmit power is queried. Within the preset range of the pasture terminal's transmit power, the incremental value of the pasture terminal's transmit power is used as an adjustment amount, and incremental operations are performed based on the initial transmit power of the pasture terminal. This helps to achieve fine-tuning of the terminal's transmit power, balance transmission stability and energy consumption, reduce data loss and delay caused by link fluctuations, and thus improve the transmission stability and data reliability of the pasture link.

[0044] When the impact value of the unqualified upload level meets the calculated upload qualification conditions, the farm delay upload optimization is stopped and a farm delay impact assessment is conducted to quantify the farm link delay. If the transmission power of the farm terminal reaches the preset maximum transmission power set in advance by preset personnel, and the impact value of the unqualified upload level still does not meet the calculated upload qualification conditions, a farm delay upload anomaly assessment is conducted to reflect the abnormal situation of farm delay upload optimization.

[0045] It should be added that long-term high-power operation may increase energy consumption. In order to improve the strength of the ranch link and optimize the power dynamically while meeting the transmission requirements, and balance stability and energy consumption, the preset range of the ranch terminal's transmission power can be dynamically adjusted and set by preset personnel based on the specific conditions of the ranch size, cattle herd type, and regional environment over a historical period.

[0046] like Figure 4 The diagram shown illustrates the farm delay upload anomaly assessment in the cattle herd benefit calculation process evaluation method for cattle herd feed ratio tasks provided in this application embodiment. Figure 4 It can be seen that: when the total number of delayed upload failures is not greater than the preset maximum number of delayed upload failures, the farm delay impact assessment is carried out; otherwise, the retransmission strategy matching of the data to be tested is carried out, that is, the number of retransmissions of the data to be tested is obtained, and the link retransmits the data to be tested according to the corresponding number of retransmissions of the data to be tested.

[0047] The specific process for assessing farm delay upload anomalies is as follows: Monitor the total number of unqualified delay uploads to reflect the degree of non-compliance in farm delay upload optimization; if the total number of unqualified delay uploads monitored is not greater than the preset maximum number of unqualified uploads set by pre-defined personnel, send a farm delay upload anomaly notification and conduct a farm delay impact assessment; otherwise, mark the corresponding total number of unqualified delay uploads as Level 1 unqualified delay uploads and perform retransmission strategy matching for the data to be measured; the total number of unqualified delay uploads represents the total number of times the impact value of the unqualified upload degree monitored by the counter does not meet the conditions for qualified upload after a preset number of farm delay upload optimizations; the retransmission strategy matching for the data to be measured indicates that the Level 1 unqualified delay uploads will be... The total number of qualified feedings, the required value of cattle feeding data to be processed, and the data loss rate to be calculated are input into the preset data retransmission matching table. The output is the number of data retransmissions to be calculated. The link retransmits the data to be calculated according to the corresponding number of data retransmissions. The retransmission operation actively retransmits the data to be calculated that is temporarily stored in the terminal. This helps to prevent data from being discarded because it exceeds the "real-time window threshold for benefit calculation". It ensures that key data that was temporarily stored due to link failure (such as the feed ratio of a single feeding and the feeding time of cattle) can be re-entered into the calculation process. This allows the cattle benefit assessment (such as feed conversion rate and the cost associated with the daily weight gain of a single cow) to be combined with the latest retransmitted actual data, which significantly improves the timeliness and accuracy of the assessment results and provides real data support for subsequent feed ratio adjustments.

[0048] After retransmitting the data to be measured, the process also includes: re-analyzing the real-time performance of cattle feeding data to reassess the real-time requirements for cattle feeding data measurement. If the average impact value of the re-acquired non-compliant upload meets the upload qualification conditions, and the cattle feeding data measurement requirement value meets the feeding data measurement qualification conditions, the farm delay impact assessment continues; otherwise, a farm terminal data maintenance prompt is issued. By matching the retransmission strategy for the data to be measured when the total number of non-compliant uploads exceeds the preset maximum number of non-compliant uploads, it helps to achieve differentiated fallback handling for upload failures and avoids the inefficiency caused by a single retransmission. If a single strategy is used, it is easy to cause retransmission to still fail or waste resources. The link retransmits the data to be measured according to the corresponding number of retransmissions, which helps to achieve orderly control of the retransmission process and ensure data integrity and measurement continuity.

[0049] As a supplementary condition for assessing the abnormality of farm delay uploads, when "occasional anomalies" (such as a single livestock collision causing upload failure) and "frequent anomalies" (such as a terminal failure in a farm causing continuous upload failures) are detected, an early warning will be triggered directly and feedback will be sent to the preset personnel, without triggering the matching of the retransmission strategy for the data to be measured.

[0050] In this embodiment, the average impact value of non-compliant uploads is obtained by performing upload and measurement non-compliant interference judgment. Measurement feedback is only performed when the average impact value of non-compliant uploads meets the measurement upload compliance conditions; otherwise, ranch delay upload optimization is performed. This helps to achieve hierarchical processing of non-compliant uploads and control of hidden risks, without wasting resources or ignoring risks, and ensuring the basic reliability of data uploads. When the ranch delay upload optimization limit is detected (when the transmission power of the ranch terminal reaches the preset maximum transmission power), if the impact value of non-compliant uploads still does not meet the measurement upload compliance conditions, a ranch delay upload anomaly assessment is performed. This helps to achieve a fallback investigation and root cause solution for upload optimization failure scenarios, further ensuring the comprehensiveness of data upload problem handling and avoiding long-term risk accumulation.

[0051] As one embodiment, the specific process of pasture delay impact assessment is as follows: A link delay impact characterization value is obtained to represent the pasture link delay situation; the link delay impact characterization value is represented by the total time taken for the pasture terminal monitored by the timer to upload the cached data to be measured during the fault period to the cloud in batches; the degree of deviation is judged based on the average link delay impact characterization value and the preset link delay impact characterization value; if the average link delay impact characterization value is greater than the preset link delay impact characterization value, pasture link delay optimization is performed in the next adjacent preset pasture link assessment time period to improve the connection stability and response speed of the link signal; otherwise, link stability verification is performed; the average link delay impact characterization value represents the average value of the link delay impact characterization values ​​obtained after performing a preset number of pasture delay impact assessments; pasture link delay optimization is used to accelerate the recovery of pasture link connections, thereby improving the connection stability and response speed of the link signal; the preset pasture link assessment time period represents the preset time period corresponding to the pasture delay impact assessment, wherein the preset link delay impact characterization value is represented by the average value of the link delay impact characterization values ​​of historical time periods.

[0052] Specifically, the process of optimizing pasture link latency is as follows: The link latency impact characterization value, the required value calculated from the cattle feeding data to be processed, and the pasture terminal beacon frames are input into a table related to the preset beacon interval period. The preset beacon interval period decrement value is then retrieved. Within the preset range corresponding to the pasture terminal's beacon interval period, based on the initial beacon interval period, the preset beacon interval period decrement value is used as an adjustment variable to perform a decrement operation. This helps to achieve initial adaptation of the pasture terminal's beacon interval period, balancing link connection stability and terminal energy consumption. By gradually shortening the beacon interval period, energy waste caused by blindly shortening the period can be avoided while ensuring the stability of the basic link connection. Each time a decrement operation is performed, the link latency impact characterization value is re-acquired. If the detected link latency impact characterization value is not greater than the preset link latency impact characterization value, pasture link latency optimization is stopped, and a pasture link latency optimization test is performed to verify the pass rate. If the corresponding number of decrement operations reaches the pass rate... If, after decreasing the maximum beacon interval period pre-set by personnel a certain number of times, the link delay impact characterization value is still greater than the preset link delay impact characterization value, a ranch link delay optimization anomaly alert is sent. The ranch link delay optimization verification process is as follows: Based on the link delay impact characterization values ​​at the initial and final states of ranch link delay optimization, a link delay optimization verification value reflecting the pass / fail status of the ranch link delay optimization is obtained. A judgment is made based on this verification value. If the verification value is greater than the preset verification value, a ranch delay impact assessment is performed; otherwise, a ranch link delay optimization anomaly alert is sent, and secondary ranch link delay optimization is performed. Secondary ranch link delay optimization is used to provide secondary remediation for ranch link delay optimization, thereby improving the data window completion rate. The link delay optimization verification value is represented by the difference between the link delay impact characterization values ​​at the initial and final states of ranch link delay optimization.

[0053] The specific process of optimizing the secondary pasture link latency is as follows: The link latency optimization test value, the required value calculated from the cattle feeding data to be processed, and the pasture terminal beacon frames are input into a table related to the preset secondary beacon interval period. The preset secondary beacon interval period decrement value is then queried. Based on the beacon interval period of the pasture terminal obtained at the end of the pasture link latency optimization, the preset secondary beacon interval period decrement value is used as an adjustment variable to perform a decrement operation. This helps to achieve advanced and refined adaptation of the pasture terminal beacon interval period, matching the high link requirements after secondary latency optimization. This ensures that the beacon interval can accurately match the link performance requirements after secondary optimization, avoiding regression of the optimization effect due to period mismatch, and ultimately achieving a balance between high link performance and low energy consumption, ensuring the long-term stable operation of the pasture link. Each decrement operation obtains the corresponding... Secondary link delay optimization check value; if the detected secondary link delay optimization check value is greater than the preset secondary link delay optimization check value, secondary ranch link delay optimization is stopped, and link stability verification is performed. If the number of corresponding reduction operations reaches the maximum number of reduction operations per secondary beacon interval set in advance by the preset personnel, and the secondary link delay optimization check value is still not greater than the preset secondary link delay optimization check value, a ranch link delay optimization anomaly prompt is sent. The secondary link delay optimization check value is represented by the difference between the link delay impact characterization value obtained at the end of the reduction operation and the link delay impact characterization value obtained at the beginning of the reduction operation when performing the corresponding reduction operation for secondary ranch link delay optimization. The preset secondary link delay optimization check value is represented by the average value of secondary link delay optimization check values ​​over a historical time period.

[0054] In this embodiment, by obtaining the average link delay impact characterization value through pasture delay impact assessment, and optimizing pasture link delay when the average link delay impact characterization value is greater than the preset link delay impact characterization value, it helps to accurately identify and quickly intervene in the explicit delay risk of pasture links. This ensures that the transmission delay of cattle feeding data (such as real-time feeding amount and milk production of lactating cows) is controlled within the basic threshold allowed by the calculation, avoiding data timeliness failure due to significant delay, and providing basic timeliness data support for subsequent cattle feed ratio calculation. When the average link delay impact characterization value is not greater than the preset link delay impact characterization value, pasture link delay optimization test is performed to obtain the link delay impact characterization value. When the link delay optimization test value is not greater than the preset link delay optimization test value, secondary pasture link delay optimization is performed. This helps to deeply explore and further optimize the implicit delay risk of pasture links, laying a more solid link foundation for accurately calculating cattle benefits (such as real-time weight gain efficiency and milk quality).

[0055] As another embodiment, the specific process of assessing the impact of ranch delay is as follows: monitoring the window qualification value to reflect the data to be measured falling within the window; making a judgment based on the window qualification value; if the window qualification value is not within the preset qualified window falling range, sending a prompt to preset personnel for backtracking and recalculation, otherwise verifying link stability; monitoring the amount of data successfully within the measurement window period and the total amount of data uploaded by the ranch terminal in real time through a network traffic monitor, and expressing the ratio of the two as the window qualification value, wherein the preset qualified window falling range is set in advance by preset personnel.

[0056] In this embodiment, when there are small-batch data retransmissions, such as livestock briefly colliding with the pasture terminal or metal feed troughs temporarily obstructing the pasture, a qualified window value is obtained by assessing the impact of pasture delay. When the qualified window value falls within the preset qualified window range, link stability is verified. This helps to accurately define the delay risk and proactively identify hidden problems in small-batch retransmission scenarios, improve the continuity of data transmission and the reliability of cattle benefit calculation in small-batch retransmission scenarios, enhance the refinement of pasture link management and resource utilization efficiency, and achieve refined link management.

[0057] Further, the specific process for verifying link stability is as follows: An assessment of breakpoints in the data to be tested is performed to output a qualified value for pasture link stability; the total number of data breakpoints occurring during the data upload process is monitored using a counter and used as the qualified value for pasture link stability; the degree of deviation is quantified (i.e., a ratio calculation) based on the qualified value for pasture link stability and a preset qualified value for pasture link stability to output a quantified value for pasture link stability deviation, where the preset qualified value for pasture link stability is represented by the average value of qualified values ​​for pasture link stability over a historical period; a judgment is made based on the quantified value for pasture link stability deviation; if the quantified value for pasture link stability deviation is within the preset qualified range for pasture stability deviation, the corresponding data to be tested is marked as qualified data, and testing feedback is provided (and the corresponding cattle feeding data is re-uploaded and automatically updated); otherwise, the corresponding data to be tested is marked as unqualified data, and a testing risk warning is sent; the testing feedback includes a ratio output for obtaining the optimal cattle feed ratio and a benefit output for obtaining cattle benefit information; the optimal cattle feed ratio represents the feed combination scheme for maximizing cattle benefit, where the preset qualified range for pasture stability deviation is pre-set by preset personnel.

[0058] Among them, the ratio output means that qualified data to be measured is input into the preset cattle herd feed ratio related set, and the optimal cattle herd feed ratio is output; the benefit output means that qualified data to be measured is input into the preset cattle herd benefit related set, and the cattle herd benefit information is output.

[0059] It needs to be explained that the demonstration displays preset sets of cattle herd feed ratios and cattle herd benefits retrieved from the database, containing dynamic mapping relationships. These mapping relationships are flexible, supporting both one-to-one mappings between single parameters and many-to-one mappings between multiple parameters and single parameters. The specific operation process is as follows: First, qualified data to be measured collected by preset personnel over historical time periods are input into a machine learning model (such as a decision tree model) that reflects the importance of features. Using the model's feature splitting function, corresponding weights, data, or data combinations are obtained, namely, the optimal cattle herd feed ratio and cattle herd benefit information. Then, the data from the historical time periods are associated and paired with the corresponding weights or data to generate preset sets of cattle herd feed ratios and cattle herd benefits. Finally, qualified data to be measured collected in real time are input into the corresponding preset sets of cattle herd feed ratios and cattle herd benefits, and based on the pre-set mapping relationships, the optimal cattle herd feed ratio and cattle herd benefit information are output.

[0060] In this embodiment, the stability deviation of the pasture link is obtained by verifying the link stability. When the stability deviation is within the preset acceptable range, calculation feedback is performed. This helps to achieve accurate calculation of cattle herd benefits and output of optimal feed ratios based on "stable link data," thereby ensuring the scientific nature and feasibility of cattle herd feed ratio decisions, as well as the stability and controllability of pasture breeding benefits. When the stability deviation is within the preset acceptable range, the corresponding data to be calculated is marked as unqualified calculation data, and a calculation risk warning is sent. This helps to achieve accurate early warning and calculation risk management of hidden data risks under the appearance of acceptable link stability, thereby ensuring the absolute reliability of cattle herd benefit calculation results.

[0061] like Figure 5 The diagram shown is a farm benefit assessment interface for the cattle herd benefit calculation process evaluation method provided in this embodiment of the invention, which is oriented towards cattle herd feed ratio tasks. Figure 5 It is known that the cloud ERP system provided in this application includes the following modules: system management, precision nutrition, machinery management, and feed order management; among them, the precision nutrition module includes a sub-module for ranch benefit assessment, which displays the number of cattle, cost per kilogram of milk, total expenditure, total income, and comprehensive benefits; it also displays the corresponding number of cattle and feeding cost per head for different cattle stages.

[0062] In summary, this application's embodiments, by performing real-time analysis of cattle feeding data and determining whether to verify the successful upload of the data to be calculated based on the analysis results, help to achieve pre-screening of data real-time performance, avoid invalid calculations from the source, and ensure that all data entering the calculation stage meets the timeliness baseline. If the successful upload verification of the data to be calculated is not performed, a prompt indicating that the real-time calculation requirement is not met is sent, and the real-time analysis of the cattle feeding data is re-performed. If the successful upload verification of the data to be calculated is performed, after the verification is completed, a determination is made based on the verification results as to whether to conduct a pasture delay impact assessment. This helps to achieve layered verification of data validity, with each layer progressing sequentially. To ensure the reliability of the calculation, if a pasture delay impact assessment is conducted, the output assessment results will determine whether to perform link stability verification; otherwise, the calculation feedback will be directly performed to obtain herd benefit information reflecting the herd's profitability. This helps to achieve dynamic closed-loop optimization of the calculation process, improve data timeliness management efficiency, and realize the accuracy and real-time decision-making of herd feed ratios, providing data support for scientific breeding. In turn, it improves the timeliness of the herd benefit calculation process assessment data for herd feed ratio tasks, solving the problem of low timeliness of the assessment data for herd benefit calculation process assessment for herd feed ratio tasks in existing technologies.

[0063] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for evaluating the process of cattle herd benefit calculation for cattle herd feed ratio tasks, characterized in that, The method includes: Perform real-time analysis of cattle feeding data to output analysis results that quantify the real-time requirements for cattle feeding data measurement. Based on the analysis results, determine whether to verify the successful upload of the data to be measured to reflect the qualified status of the uploaded data. If the successful upload verification of the data to be measured is not performed, a prompt indicating that the real-time measurement requirement is not met will be sent, and the real-time analysis of the cattle feeding data will be performed again. If the successful upload verification of the data to be measured is performed, after the verification is completed, it will be determined whether to conduct a pasture delay impact assessment based on the verification results, so as to output an assessment result that reflects the pasture link delay. If a pasture delay impact assessment is conducted, the output assessment results will determine whether to perform link stability verification to check for breakpoints in the data to be measured. If the verification is successful, the cattle feeding data will be retransmitted and the cattle benefit information reflecting the cattle benefit situation and the optimal cattle feed ratio reflecting the maximization of cattle benefit will be automatically updated. Otherwise, the calculation feedback will be performed directly to obtain the cattle benefit information and the optimal cattle feed ratio.

2. The method for evaluating the cattle herd benefit calculation process for the task of cattle herd feed ratio as described in claim 1, characterized in that, The specific process for real-time analysis of cattle feeding data is as follows: Based on the amount of cattle feeding data generated by the ranch terminal, obtain the cattle feeding data measurement demand value to reflect the real-time demand for cattle feeding data measurement. Determine whether the calculated feed data requirements for cattle meet the qualified conditions for feed data calculation. If they do, send a prompt that the real-time calculation requirements have been met and obtain the corresponding data to be calculated to verify the successful upload of the data to be calculated. Otherwise, send a prompt that the real-time calculation requirements have not been met and re-perform the real-time analysis of the cattle feed data calculation. The qualified condition for feeding data calculation means that the required value for cattle feeding data calculation is greater than the preset required value for cattle feeding data calculation.

3. The method for evaluating the cattle herd benefit calculation process for the task of cattle herd feed ratio as described in claim 2, characterized in that, The specific process for verifying the successful upload of the data to be measured is as follows: The upload time of the data to be tested and the preset upload time of the data to be tested are used to evaluate the pass rate of the data upload and output the corresponding data upload verification result. If the uploaded verification result of the data to be measured is greater than the preset qualified uploaded result, the corresponding data to be measured will be marked as qualified data and the measurement feedback will be provided. Otherwise, the uploaded verification result of the corresponding data to be measured will be marked as unqualified uploaded verification result, and the upload and measurement unqualified interference judgment will be triggered to reflect the effect of the unqualified uploaded verification result on the degree of upload qualification.

4. The method for evaluating the cattle herd benefit calculation process for the task of cattle herd feed ratio as described in claim 3, characterized in that, The specific process for determining the upload and measurement non-compliance interference is as follows: Input the unqualified upload verification results and the required value of the cattle feeding data to be processed into the preset link stability impact table, and output the impact value of the unqualified upload degree; The cattle feeding data calculation requirement value to be processed represents the cattle feeding data calculation requirement value that meets the qualified conditions for feeding data calculation. If the average impact value of the unqualified upload degree meets the qualified upload conditions, the corresponding data to be measured is marked as qualified data and the measurement feedback is performed. Otherwise, the corresponding data to be measured is marked as unqualified data and the farm delay upload optimization is performed in the next adjacent preset farm upload time period to avoid the data upload failure caused by the data upload failure. The calculated upload pass condition indicates that the average impact value of the failure upload level is within the preset failure upload level impact range.

5. The method for evaluating the cattle herd benefit calculation process for the task of cattle herd feed ratio as described in claim 4, characterized in that, The ranch delay upload optimization includes sequential priority sorting of cattle feeding data to prioritize core ranch terminals when link optimization resources are limited, and ranch link strength optimization to enhance ranch link signal strength. The cattle feeding data priority sorting means sorting the cattle feeding data to be processed in an ascending order to obtain an ascending sequence of calculated demand values. The specific process for optimizing the ranch link strength is as follows: According to the sequence order corresponding to the incrementally calculated demand value sequence, the ranch link strength of the ranch terminal is optimized. The demand value calculated from the cattle feeding data and the channel attenuation rate of the ranch terminal are input into the preset ranch power correlation table. The incremental value of the ranch terminal's transmission power is queried. Within the preset range of the ranch terminal's transmission power, the incremental value of the ranch terminal's transmission power is used as the adjustment amount, and the incremental operation is carried out on the basis of the initial transmission power of the ranch terminal. When the impact value of the unqualified upload level meets the calculated upload qualification conditions, the farm delay upload optimization is stopped and a farm delay impact assessment is conducted to quantify the farm link delay. If the transmission power of the farm terminal reaches the preset maximum transmission power and the impact value of the unqualified upload level still does not meet the calculated upload qualification conditions, a farm delay upload anomaly assessment is conducted to reflect the abnormal situation of the farm delay upload optimization. The specific process for assessing the anomaly in the ranch upload delay is as follows: If the total number of monitored delayed upload failures is not greater than the preset maximum number of failed uploads, a notification will be sent indicating that the number of abnormal delayed uploads in the ranch is acceptable and an assessment of the impact of ranch delays will be conducted. Otherwise, the corresponding total number of delayed upload failures will be marked as the first-level total number of delayed upload failures, and a retransmission strategy for the data to be measured will be matched. The retransmission strategy matching representation of the data to be measured means that the total number of unqualified first-level delayed uploads, the required value of cattle feeding data to be processed, and the data loss rate to be measured are input into the preset data retransmission matching table, and the number of data retransmissions to be measured is output. The link retransmits the data to be measured according to the corresponding number of data retransmissions to be measured. After retransmitting the data to be measured, the process also includes: re-analyzing the real-time performance of cattle feeding data to reassess the real-time requirements for cattle feeding data measurement. If the average impact value of the re-acquired non-compliance upload meets the upload qualification conditions and the cattle feeding data measurement requirement value meets the feeding data measurement qualification conditions, the farm delay impact assessment continues; otherwise, a farm terminal data maintenance prompt is issued.

6. The method for evaluating the cattle herd benefit calculation process for the task of cattle herd feed ratio as described in claim 5, characterized in that, The specific process for assessing the impact of pasture delays is as follows: Obtain the link delay impact characterization value used to characterize the ranch link delay situation; The link delay impact characterization value is represented by the total time taken to upload the cached data to be measured during the fault period to the cloud in batches through the ranch terminal; If the average link delay impact value is greater than the preset link delay impact value, the pasture link delay is optimized in the next adjacent preset pasture link evaluation time period to improve the connection stability and response speed of the link signal; otherwise, the link stability is verified. The average link delay impact characterization value represents the average value of the link delay impact characterization values ​​obtained after performing a preset number of ranch delay impact assessments.

7. The method for evaluating the cattle herd benefit calculation process for the task of cattle herd feed ratio as described in claim 6, characterized in that, The specific process for optimizing the ranch link latency is as follows: Input the link delay impact value, the required value of the cattle feeding data to be processed, and the pasture terminal beacon frame into the table related to the preset beacon interval period, and query the preset beacon interval period decrement value. Within the preset range corresponding to the beacon interval period of the ranch terminal, based on the initial beacon interval period, a decrease operation is performed using the preset beacon interval period decrease value as the adjustment amount; Each time a decrement operation is performed, the link delay impact characterization value is reacquired. If the detected link delay impact characterization value is not greater than the preset link delay impact characterization value, the ranch link delay optimization is stopped, and a ranch link delay optimization test is performed to verify the pass rate of the ranch link delay optimization. If the number of corresponding decrement operations reaches the maximum beacon interval period decrement number, and the link delay impact characterization value is still greater than the preset link delay impact characterization value, a ranch link delay optimization anomaly prompt is sent. The specific process of the ranch link delay optimization test is as follows: Based on the link delay impact characterization value of the initial state of ranch link delay optimization and the link delay impact characterization value of the final state of ranch link delay optimization, obtain the link delay optimization test value to reflect the qualification of ranch link delay optimization. If the link delay optimization test value is greater than the preset link delay optimization test value, ranch delay impact assessment is performed; otherwise, a ranch link delay optimization anomaly prompt is sent, and secondary ranch link delay optimization is performed. The link delay optimization test value is represented by the difference between the link delay impact characterization value of the initial state of the ranch link delay optimization and the link delay impact characterization value of the final state of the ranch link delay optimization.

8. The method for evaluating the cattle herd benefit calculation process for the task of cattle herd feed ratio as described in claim 7, characterized in that, The specific process for optimizing the link latency of the secondary pasture is as follows: Input the link delay optimization test value, the required value of the cattle feeding data to be processed, and the pasture terminal beacon frame into the table related to the preset secondary beacon interval period, and query the decrement value of the preset secondary beacon interval period. Based on the beacon interval period of the ranch terminal obtained at the end of the ranch link delay optimization, a decrease operation is performed using a preset decrease value of the secondary beacon interval period as an adjustment amount. Each time a decrease operation is performed, the corresponding secondary link delay optimization test value is obtained; If the detected value of the secondary link delay optimization test is greater than the preset value of the secondary link delay optimization test, the secondary ranch link delay optimization will be stopped and the link stability will be verified. If the number of corresponding decrement operations reaches the maximum number of decrement operations of the secondary beacon interval period, and the value of the secondary link delay optimization test is still not greater than the preset value of the secondary link delay optimization test, a ranch link delay optimization anomaly prompt will be sent. The secondary link delay optimization test value is represented by the difference between the link delay impact characterization value obtained at the end of the reduction operation and the link delay impact characterization value obtained at the beginning of the reduction operation when performing the reduction operation corresponding to the secondary ranch link delay optimization.

9. The method for evaluating the cattle herd benefit calculation process for the task of cattle herd feed ratio as described in claim 5, characterized in that, The specific process for assessing the impact of pasture delays is as follows: Monitoring is used to reflect the window's acceptable landing value, which reflects whether the data to be measured falls into the window. If the value of the window falls within the preset range of the qualified window, a prompt is sent to the preset personnel for backtracking and recalculation; otherwise, the link stability is verified. The window qualifying value is represented by the ratio of the amount of data that successfully fell within the calculation window period to the total amount of data uploaded in real time from the ranch terminal.

10. The method for evaluating the cattle herd benefit calculation process for the task of cattle herd feed ratio as described in claim 6 or 8, characterized in that, The specific process for verifying link stability is as follows: Evaluate the breakpoint conditions of the data to be measured to output a pass value for the stability of the ranch link; The ranch link stability pass value is represented by the total number of data breakpoints that occur during the data upload process to be tested. The degree of deviation is quantified based on the qualified value of pasture link stability and the preset qualified value of pasture link stability, so as to output the quantified value of pasture link stability deviation. If the quantified value of the ranch link stability deviation is within the preset ranch stability deviation acceptable range, the corresponding data to be measured is marked as qualified measurement data and measurement feedback is provided; otherwise, the corresponding data to be measured is marked as unqualified measurement data and a measurement risk warning is sent. The calculation feedback includes a ratio output for obtaining the optimal feed ratio for the cattle herd and a benefit output for obtaining cattle herd benefit information.

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