Data processing method and device, computer equipment and readable storage medium

Abstract

The invention relates to a data processing method and device, computer equipment and a readable storage medium. The method comprises the following steps: acquiring a tobacco leaf environment parameter set, a scoring factor and an index threshold value in a current time period; the scoring factor is determined according to a historical tobacco leaf environment parameter set and an environment evaluation algorithm; the index threshold value is determined according to a threshold value determination strategy and a historical tobacco leaf environment parameter set; determining the evaluation grade of each index value in the tobacco leaf environment parameter set according to the index threshold value; and determining a comprehensive score based on the scoring factor, the environment evaluation rule under each evaluation grade and the tobacco leaf environment parameter set. By adopting the method, the accuracy of the data processing method can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of data processing, and particularly to a data processing method, apparatus, computer device, computer-readable storage medium, and computer program product. Background Art

[0002] In the production process of cigarettes, it is necessary to store tobacco leaves in a warehouse for 12 to 30 months to allow the tobacco leaves to naturally age, thereby improving the smoking quality of the tobacco leaves. To ensure the quality of the tobacco leaves, it is necessary to regularly implement clean storage management of the tobacco leaf raw materials in the warehouse.

[0003] In traditional technology, the tobacco leaf industry has formulated a guideline for clean storage management of tobacco leaf raw materials, which stipulates the main operation processes and basic requirements for clean storage of tobacco leaf raw materials. Warehouse management personnel clean and manage the warehouse according to the guideline for clean storage management of tobacco leaf raw materials. Then, the management personnel subjectively evaluate the cleaned and managed warehouse to obtain a comprehensive score of the warehouse. This comprehensive score reflects the effect of clean storage management of tobacco leaf raw materials.

[0004] However, in traditional technology, only the subjective evaluation of the management personnel is used to determine the comprehensive score of the warehouse, and the proportion of subjective factors is too large. Therefore, the accuracy of the current data processing method is relatively low. Summary of the Invention

[0005] Based on this, in view of the above technical problems, it is necessary to provide a data processing method, apparatus, computer device, computer-readable storage medium, and computer program product.

[0006] In a first aspect, the present application provides a data processing method, including:

[0007] Obtain a set of tobacco leaf environmental parameters, a scoring factor, and an index threshold within a current time period; the scoring factor is determined according to a historical set of tobacco leaf environmental parameters and an environmental evaluation algorithm; the index threshold is determined according to a threshold determination strategy and the historical set of tobacco leaf environmental parameters;

[0008] Determine the evaluation grade where each index value in the set of tobacco leaf environmental parameters is located according to the index threshold;

[0009] Determine a comprehensive score based on the scoring factor, the environmental evaluation rules under each evaluation grade, and the set of tobacco leaf environmental parameters.

[0010] In one of the embodiments, before obtaining the set of tobacco leaf environmental parameters, the scoring factor, and the index threshold within the current time period, the method further includes:

[0011] Obtain a historical set of tobacco leaf environmental parameters, and determine the historical index value extreme values of each tobacco leaf environmental index in the historical set of tobacco leaf environmental parameters;

[0012] Based on the index threshold determination strategy and the extreme values of each historical index value, determine the index threshold of each tobacco leaf environmental index;

[0013] Determine the historical index scores of each item according to the historical tobacco leaf environmental parameter set and the environmental evaluation algorithm, and determine the scoring factors among the historical index scores of each item.

[0014] In one embodiment, the step of determining the index threshold of each tobacco leaf environmental index based on the index threshold determination strategy and the extreme values of each historical index value includes:

[0015] For each tobacco leaf environmental index, determine whether the extreme value of the historical index value of the tobacco leaf environmental index is lower than a preset initial index threshold;

[0016] If the extreme value of the historical index value is lower than the initial index threshold, determine the extreme value of the historical index value as the index threshold of the tobacco leaf environmental index;

[0017] If the extreme value of the historical index value is not lower than the initial index threshold, determine the initial index threshold as the index threshold of the tobacco leaf environmental index.

[0018] In one embodiment, the step of determining the historical index scores of each item according to the historical tobacco leaf environmental parameter set and the environmental evaluation algorithm, and determining the scoring factors among the historical index scores of each item includes:

[0019] Perform data processing on the historical tobacco leaf environmental parameter set based on the environmental evaluation algorithm to obtain the historical index scores of each tobacco leaf environmental index;

[0020] For each tobacco leaf environmental index, determine the lowest historical index score of the tobacco leaf environmental index among the historical index scores of the tobacco leaf environmental index;

[0021] Update the scoring factor of the tobacco leaf environmental index according to the lowest historical index score and the environmental evaluation algorithm.

[0022] In one embodiment, the index threshold includes a highest index threshold and a lowest index threshold. The step of determining the evaluation level where each index value in the tobacco leaf environmental parameter set is located according to the index threshold includes:

[0023] For each index value in the tobacco leaf environmental parameter set, if the index value is less than or equal to the lowest index threshold, determine that the evaluation level where the index value is located is the first evaluation level;

[0024] If the index value is greater than the lowest index threshold and less than the highest index threshold, determine that the evaluation level where the index value is located is the second evaluation level;

[0025] If the index value is greater than or equal to the highest index threshold, determine that the evaluation level where the index value is located is the third evaluation level.

[0026] In one embodiment, the determining of the comprehensive score based on the scoring factor, the environmental evaluation rules under each evaluation level, and the set of tobacco leaf environmental parameters includes:

[0027] Determine the environmental evaluation rule corresponding to the index value according to the evaluation level of each index value;

[0028] Determine the index score of the tobacco leaf environmental index where the index value is located according to the environmental evaluation rule, the index value, and the scoring factor;

[0029] Perform weighted processing on the index scores of each tobacco leaf environmental index to obtain a comprehensive score.

[0030] In one embodiment, the determining of the index score of the tobacco leaf environmental index where the index value is located according to the environmental evaluation rule, the index value, and the scoring factor includes:

[0031] If the environmental evaluation rule is the first environmental evaluation rule, determine the preset first index score as the index score of the tobacco leaf environmental index where the index value is located;

[0032] If the environmental evaluation rule is the second environmental evaluation rule, perform data processing on the index value, the index threshold, and the scoring factor according to the second environmental evaluation algorithm to obtain the index score of the tobacco leaf environmental index where the index value is located;

[0033] If the environmental evaluation rule is the third environmental evaluation rule, determine the preset second index score as the index score of the tobacco leaf environmental index where the index value is located.

[0034] In a second aspect, the present application further provides a data processing device, including:

[0035] A first acquisition module, configured to acquire a set of tobacco leaf environmental parameters, a scoring factor, and an index threshold within a current time period; the scoring factor is determined according to a historical set of tobacco leaf environmental parameters and an environmental evaluation algorithm; the index threshold is determined according to a threshold determination strategy and the historical set of tobacco leaf environmental parameters;

[0036] A first determination module, configured to determine the evaluation level where each index value in the set of tobacco leaf environmental parameters is located according to the index threshold;

[0037] A second determination module, configured to determine a comprehensive score based on the scoring factor, the environmental evaluation rules for each evaluation level, and the tobacco leaf environmental parameter set.

[0038] In a third aspect, the present application further provides a computer device, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0039] Obtain a tobacco leaf environmental parameter set, a scoring factor, and an index threshold within a current time period; the scoring factor is determined according to a historical tobacco leaf environmental parameter set and an environmental evaluation algorithm; the index threshold is determined according to a threshold determination strategy and the historical tobacco leaf environmental parameter set;

[0040] Determine the evaluation level where each index value in the tobacco leaf environmental parameter set is located according to the index threshold;

[0041] Determine a comprehensive score based on the scoring factor, the environmental evaluation rules for each evaluation level, and the tobacco leaf environmental parameter set.

[0042] In a fourth aspect, the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0043] Obtain a tobacco leaf environmental parameter set, a scoring factor, and an index threshold within a current time period; the scoring factor is determined according to a historical tobacco leaf environmental parameter set and an environmental evaluation algorithm; the index threshold is determined according to a threshold determination strategy and the historical tobacco leaf environmental parameter set;

[0044] Determine the evaluation level where each index value in the tobacco leaf environmental parameter set is located according to the index threshold;

[0045] Determine a comprehensive score based on the scoring factor, the environmental evaluation rules for each evaluation level, and the tobacco leaf environmental parameter set.

[0046] In a fifth aspect, the present application further provides a computer program product, including a computer program. When the computer program is executed by a processor, the following steps are implemented:

[0047] Obtain a tobacco leaf environmental parameter set, a scoring factor, and an index threshold within a current time period; the scoring factor is determined according to a historical tobacco leaf environmental parameter set and an environmental evaluation algorithm; the index threshold is determined according to a threshold determination strategy and the historical tobacco leaf environmental parameter set;

[0048] Determine the evaluation level where each index value in the tobacco leaf environmental parameter set is located according to the index threshold;

[0049] Determine a comprehensive score based on the scoring factor, the environmental evaluation rules for each evaluation level, and the tobacco leaf environmental parameter set.

[0050] The above data processing method, device, computer device, computer-readable storage medium, and computer program product obtain a tobacco leaf environmental parameter set, a scoring factor, and an index threshold within a current time period; the scoring factor is determined according to a historical tobacco leaf environmental parameter set and an environmental evaluation algorithm; the index threshold is determined according to a threshold determination strategy and the historical tobacco leaf environmental parameter set; determine the evaluation level where each index value in the tobacco leaf environmental parameter set is located according to the index threshold; determine a comprehensive score based on the scoring factor, the environmental evaluation rules for each evaluation level, and the tobacco leaf environmental parameter set. By using this method, through the index threshold, determine the evaluation level of each index value in the tobacco leaf environmental parameter set, and according to the scoring factor, the environmental evaluation rules for each evaluation level, and the tobacco leaf environmental parameter set, determine the comprehensive score, avoiding manual participation, realizing an objective evaluation of the effect of clean storage of tobacco leaf raw materials, establishing an evaluation standard for the effect of a clean warehouse for tobacco leaf raw materials, and improving the accuracy of the data processing method. Description of the Drawings

[0051] To more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following will briefly introduce the drawings required for use in the description of the embodiments of the present application or related technologies. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other related drawings can also be obtained based on these drawings.

[0052] Figure 1 It is a flowchart of the data processing method in an embodiment;

[0053] Figure 2 It is a flowchart of determining the scoring factor and the index threshold in an embodiment;

[0054] Figure 3 It is a flowchart of determining the index threshold in an embodiment;

[0055] Figure 4 It is a flowchart of updating the scoring factor in an embodiment;

[0056] Figure 5 It is a flowchart of determining the evaluation level in an embodiment;

[0057] Figure 6 It is a flowchart of determining the comprehensive score in an embodiment;

[0058] Figure 7 It is a flowchart of determining the index score in an embodiment;

[0059] Figure 8 is a structural block diagram of a data processing device in an embodiment;

[0060] Figure 9 is an internal structure diagram of a computer device in an embodiment. Detailed implementation manners

[0061] In order to make the objectives, technical solutions and advantages of the present application clearer and more understandable, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0062] During the production process of cigarettes, tobacco leaves need to be naturally aged for 12 to 30 months to improve the smoking quality of tobacco leaves. During the aging of tobacco leaves, due to the strong hygroscopicity of tobacco leaves and the nutrients required for the growth of microorganisms, the molds on their surfaces multiply under suitable environmental conditions, resulting in the mildew of tobacco leaves. At the same time, tobacco leaves are often damaged by storage pests during the aging period. Tobacco beetles and tobacco moths are the main storage pests. To reduce the losses caused by mildew and insect damage during the aging of tobacco leaves, it is necessary to regularly implement clean storage management of tobacco leaf raw materials in the tobacco leaf warehouse.

[0063] In the traditional technology, the tobacco leaf industry has formulated a guide for clean storage management of tobacco leaf raw materials. This guide for clean storage management of tobacco leaf raw materials stipulates the main operation processes, basic requirements, requirements for warehousing of tobacco leaf raw materials, requirements for clean storage in the warehouse of tobacco leaf raw materials, requirements for outbound of tobacco leaf raw materials, and requirements for clean transportation. At the same time, this guide for clean storage management of tobacco leaf raw materials clearly stipulates the cleaning requirements for each area of the tobacco leaf warehouse, the handling operation area and the office and living area in terms of cleaning items, cleaning requirements, and frequencies, and clarifies the main operation processes for clean storage of tobacco leaf raw materials and pest control, providing good guidance for the clean storage of tobacco leaf raw materials.

[0064] Warehouse management personnel clean and manage the warehouse according to the guide for clean storage management of tobacco leaf raw materials. Then, the management personnel subjectively evaluate the cleaned and managed warehouse to obtain the comprehensive score of the warehouse. This comprehensive score reflects the effect of the clean storage management of tobacco leaf raw materials.

[0065] However, in the traditional technology, only the subjective evaluation of the management personnel is used to determine the comprehensive score of the warehouse, and the proportion of subjective factors is too large. Therefore, the accuracy of the current data processing method is relatively low.

[0066] In one embodiment, as Figure 1 shown, a data processing method is provided. In the embodiments of the present application, this method is described by taking its application to a computer device as an example. The embodiments of the present application do not limit the execution device for data processing, and include the following steps 102 to step 106:

[0067] Step 102: Obtain the tobacco leaf environmental parameter set, scoring factors, and index thresholds within the current time period.

[0068] Among them, the scoring factors are determined based on the historical tobacco leaf environmental parameter set and the environmental evaluation algorithm; the index thresholds are determined based on the threshold determination strategy and the historical tobacco leaf environmental parameter set. The tobacco leaf environmental parameter set contains the index values of each tobacco leaf environmental index.

[0069] In implementation, the computer device obtains the historical tobacco leaf environmental parameter set input by the target user. Then, the computer device obtains the corresponding scoring factors and index thresholds for the current time period from the database.

[0070] Specifically, each tobacco leaf environmental index is the insect situation index, the colony density index, and the pollution degree index. The computer device obtains the tobacco leaf environmental parameter template from the database. The tobacco leaf environmental parameter template contains an insect situation index input box, a colony density input box, and a pollution degree input box. The target user inputs the insect situation index value of the insect situation index based on the insect situation index input box, and inputs the colony index value of the colony density index through the colony density index. At the same time, the target user inputs the pollution index value of the pollution degree index according to the pollution degree input box. The computer device obtains the insect situation index value, the colony index value, and the pollution index value input by the target user.

[0071] In an exemplary embodiment, the target user determines the pest index parameters of a warehouse (tobacco warehouse) through tobacco pest sex pheromone traps. Specifically, the target user hangs a tobacco pest sex pheromone trap in each 200-square-meter warehouse compartment and uses the trap to catch pests. Then, the target user counts the number of pests on the trap once a week and totals the number of pests once a month to obtain the pest index value. The pest index value is the total number of pests per month. At the same time, the target user measures the spatial mold colony density of the warehouse once a month by the natural sedimentation method to obtain the colony index value. Specifically, due to gravity, microbial aerosol particles in the measured area (warehouse) gradually settle into a petri dish with a culture medium (a sterile petri dish with a diameter of 90 mm (millimeters)) within a certain time (usually one hour). The target user determines the content of bacteria or molds in the warehouse air based on the number of colonies in the petri dish and determines the colony index value. The colony index value is the spatial mold colony density of the warehouse storing tobacco leaves each month. The target user inputs the pest index value and the colony index value into a computer device. At the same time, the computer device obtains the pollution index value through a PM2.5 (fine particulate matter) detector. Specifically, fine particulate matter in the air can remain suspended in the air for a long time. The higher its concentration in the air, the more serious the air pollution. The PM2.5 detector collects the PM2.5 concentration in the air of the warehouse and transmits the PM2.5 concentration to the computer device. The computer device performs a mean value process on the PM2.5 concentration within a month to obtain the pollution index value. The pollution index value is the average spatial PM2.5 per month. It should be noted that when the target user determines the pest index value or the colony index value, the same set of measurement standards should be maintained.

[0072] For example, the current time period is one month, i.e., February 2025. During February 2025, the target user hangs a tobacco pest sex pheromone trap in each 200-square-meter warehouse compartment and uses the trap to catch pests. Then, the target user counts the number of pests on the trap once a week within February 2025 and totals the number of pests in February 2025 to obtain the pest index value for February 2025. At the same time, the target user measures the spatial mold colony density of the warehouse once in February 2025 by the natural sedimentation method to obtain the colony index value. Then, the target user inputs the pest index value and the colony index value into the computer device, enabling the computer device to obtain the pest index value and the colony index value for February 2025. The computer device receives the PM2.5 concentration collected by the PM2.5 detector and stores the PM2.5 concentration in the database. The computer device retrieves the PM2.5 concentrations for February 2025 from the database and performs a mean value process on the PM2.5 concentrations to obtain the pollution index value.

[0073] In an alternative embodiment, the target user inputs the tobacco leaf environmental parameter table into a computer device. The computer device acquires the tobacco leaf environmental parameter table and parses the tobacco leaf environmental parameter table to obtain the pest index value corresponding to the pest index, the colony index value corresponding to the colony density index, and the pollution index value corresponding to the pollution degree index.

[0074] Step 104: Determine the evaluation grade where each index value in the tobacco leaf environmental parameter set is located according to the index threshold.

[0075] In implementation, for each index value in the tobacco leaf environmental parameter set, the computer device determines the evaluation grade where the index value is located according to the magnitude relationship between the index threshold and the index value.

[0076] Specifically, each evaluation grade is pre-set in the computer device, and the index threshold includes the highest index threshold and the lowest index threshold. For each tobacco leaf environmental index in the tobacco leaf environmental parameter set, the computer device determines the highest index threshold and the lowest index threshold corresponding to the tobacco leaf environmental index. Then, the computer device determines the evaluation grade where the index value is located among the evaluation grades according to the magnitude relationship between the highest index threshold, the index value of the tobacco leaf environmental index, and the lowest index threshold.

[0077] Step 106: Determine the comprehensive score based on the scoring factor, the environmental evaluation rules under each evaluation grade, and the tobacco leaf environmental parameter set.

[0078] Among them, the scoring factor represents the evaluation criterion. The larger the scoring factor, the stricter the evaluation criterion is represented. The smaller the scoring factor, the looser the evaluation criterion is represented.

[0079] In implementation, for each index value in the tobacco leaf environmental parameter set, the computer device determines the environmental evaluation rule corresponding to the index value according to the evaluation grade of the index value. Then, the computer device determines the index score corresponding to the index value according to the index value, the environmental evaluation rule corresponding to the index value, the scoring factor, and the index threshold. The computer device determines the comprehensive score for the current time period according to each index score.

[0080] In an alternative embodiment, the computer device determines whether the comprehensive score for the current time period is greater than the comprehensive score for the previous time period of the current time period. If the comprehensive score for the current time period is greater than the comprehensive score for the previous time period, the computer device determines that the cleanliness level of the tobacco warehouse has decreased and displays the information that the cleanliness level of the tobacco warehouse has decreased.

[0081] In an alternative embodiment, the computer device determines the comprehensive score for each month in the current year and the historical comprehensive score for each month in the previous year of the current year based on the data processing method. The computer device compares the comprehensive score and the historical comprehensive score for the same month to obtain a comparison result. The computer device outputs optimization suggestions for the clean storage management guide of tobacco leaf raw materials based on the comparison result.

[0082] In the above data processing method, through the index threshold, the evaluation level of each index value in the tobacco leaf environmental parameter set is determined, and based on the scoring factor, the environmental evaluation rules under each evaluation level, and the tobacco leaf environmental parameter set, the comprehensive score is determined, avoiding manual participation, realizing an objective evaluation of the effect of clean storage of tobacco leaf raw materials, establishing an evaluation standard for the effect of clean warehouses of tobacco leaf raw materials, and improving the accuracy of the data processing method.

[0083] In an exemplary embodiment, before obtaining the scoring factor and the index threshold from the database, it is necessary to first determine the index threshold and the scoring factor. As Figure 2 shown, before step 102 is executed, the execution process of the data processing method further includes steps 202 to 206. Among them:

[0084] Step 202, obtain the historical tobacco leaf environmental parameter set, and determine the historical index value extreme values of each tobacco leaf environmental index in the historical tobacco leaf environmental parameter set.

[0085] Among them, each historical time period corresponding to the current time period is each historical month in the previous year of the year where the current time period is located.

[0086] In implementation, the computer device obtains the historical tobacco leaf environmental parameter sets of each historical time period corresponding to the current time period from the database. The historical tobacco leaf environmental parameter set contains each tobacco leaf environmental index. Each tobacco leaf environmental index corresponds to each historical index value. The computer device determines the historical index value extreme value for each tobacco leaf environmental index among the historical index values corresponding to the tobacco leaf environmental index.

[0087] Specifically, the historical index value extreme value includes the maximum historical index value and the minimum historical index value. The computer device determines the maximum historical index value and the minimum historical index value of each tobacco leaf environmental index among the historical index values corresponding to the tobacco leaf environmental index.

[0088] In an exemplary embodiment, each tobacco leaf environmental index is an insect situation index, a colony density index, and a pollution degree index. The computer device determines the maximum historical insect situation index value and the minimum historical insect situation index value among the respective historical insect situation index values corresponding to the insect situation index. The computer device determines the maximum historical colony index value and the minimum historical colony index value among the respective historical colony index values corresponding to the colony density index. The computer device determines the maximum historical pollution index value and the minimum historical pollution index value among the respective historical pollution index values corresponding to the pollution degree index. Table 1 provides the maximum historical index values and the minimum historical index values of each tobacco leaf environmental index in an exemplary embodiment.

[0089] Table 1

[0090]

[0091] In Table 1 above, the maximum historical index value of the insect situation index is 30, and the minimum historical index value is 0. The maximum historical index value of the colony density index is 90, and the minimum historical index value is 0. The maximum historical index value of the pollution degree index is 35, and the minimum historical index value is 8.

[0092] Step 204: Based on the index threshold determination strategy and the extreme values of the respective historical index values, determine the index thresholds of each tobacco leaf environmental index.

[0093] In implementation, the computer device is pre-set with the initial index thresholds of each tobacco leaf environmental index. For each tobacco leaf environmental index, the computer device determines the index threshold of the tobacco leaf environmental index according to the size relationship between the initial index threshold of the tobacco leaf environmental index and the extreme values of the historical index values and the index threshold determination strategy.

[0094] Specifically, for each tobacco leaf environmental index, the computer device determines whether the extreme values of the historical index values of the tobacco leaf environmental index are lower than the initial index threshold of the tobacco leaf environmental index, and obtains a first determination result. Then, the computer device determines the index threshold of the tobacco leaf environmental index according to the first determination result and the index threshold determination strategy.

[0095] In an exemplary embodiment, the index threshold determination strategy is to determine the lowest value among the two data as the index threshold. Therefore, if the first determination result is that the extreme values of the historical index values are lower than the initial index threshold, the computer device determines the extreme values of the historical index values as the index threshold. If the first determination result is that the extreme values of the historical index values are greater than or equal to the initial index threshold, the computer device determines the initial index threshold as the index threshold.

[0096] Step 206: Determine the respective historical index scores according to the historical tobacco leaf environmental parameter set and the environmental evaluation algorithm, and determine the scoring factors among the respective historical index scores.

[0097] In implementation, initial scoring factors are preset in the computer device. The computer device processes the historical indicator values in the historical tobacco leaf environment parameter set according to the environmental evaluation algorithm to obtain the historical indicator scores. Then, the computer device determines the lowest historical indicator score among the historical indicator scores, and updates the initial scoring factors of the tobacco leaf environment indicators according to the lowest historical indicator score and the environmental evaluation algorithm to obtain the updated scoring factors.

[0098] Specifically, the historical tobacco leaf environment parameter set contains each tobacco leaf environment indicator. The computer device processes the historical indicator values of each tobacco leaf environment indicator in the historical tobacco leaf environment parameter set according to the environmental evaluation algorithm to obtain the historical indicator scores. For each tobacco leaf environment indicator, the computer device determines the lowest historical indicator score of the tobacco leaf environment indicator among the historical indicator scores of the tobacco leaf environment indicator. The computer device updates the initial scoring factors of the tobacco leaf environment indicators according to the lowest historical indicator score and the environmental evaluation algorithm to obtain the updated scoring factors.

[0099] In this embodiment, the index threshold is determined through the threshold determination strategy and the historical tobacco leaf environment parameter set, and the scoring factors are determined through the historical tobacco leaf environment parameter set and the environmental evaluation algorithm, thereby determining the evaluation criteria for the tobacco leaf environment parameter set, which is convenient for subsequent processing of the tobacco leaf environment parameter set.

[0100] In an exemplary embodiment, as Figure 3 shown, the specific processing process of step 204 includes steps 302 to 306. Among them:

[0101] Step 302, for each tobacco leaf environment indicator, determine whether the extreme value of the historical indicator value of the tobacco leaf environment indicator is lower than the preset initial index threshold.

[0102] Among them, the extreme value of the historical indicator value includes the maximum historical indicator value (the highest historical indicator value) and the minimum historical indicator value (the lowest historical indicator value). The initial index threshold includes the maximum initial index threshold and the minimum initial index threshold.

[0103] In implementation, for each tobacco leaf environment indicator in the historical tobacco leaf environment parameter set, the computer device determines whether the maximum historical indicator value of the tobacco leaf environment indicator is lower than the preset maximum initial index threshold to obtain a second judgment result. At the same time, the computer device determines whether the minimum historical indicator value of the tobacco leaf environment indicator is less than the preset minimum initial index threshold to obtain a third judgment result.

[0104] In an exemplary embodiment, the tobacco leaf environmental indicators include an insect situation index indicator, a colony density indicator, and a pollution degree indicator. The computer device determines whether the maximum historical insect situation index value of the insect situation index indicator is lower than the maximum insect situation index threshold. At the same time, the computer device determines whether the minimum historical insect situation index value of the insect situation index indicator is lower than the minimum insect situation index threshold. The computer device determines whether the maximum historical colony index value of the colony density indicator is lower than the maximum colony index threshold. At the same time, the computer device determines whether the minimum historical colony index value of the colony density indicator is lower than the minimum colony index threshold. The computer device determines whether the maximum historical pollution index value of the pollution degree indicator is lower than the maximum pollution index threshold. At the same time, the computer device determines whether the minimum historical pollution index value of the pollution degree indicator is lower than the minimum pollution index threshold.

[0105] Step 304, if the extreme value of the historical index value is lower than the initial index threshold, determine the extreme value of the historical index value as the index threshold of the tobacco leaf environmental indicator.

[0106] In implementation, if the second judgment result is that the maximum historical index value is lower than the maximum initial index threshold, the computer device determines the maximum historical index value as the maximum index threshold. If the third judgment result is that the minimum historical index value is lower than the minimum initial index threshold, the computer device determines the minimum historical index value as the minimum index threshold.

[0107] In an exemplary embodiment, if the maximum historical insect situation index value of the insect situation index indicator is lower than the maximum initial insect situation index threshold, the computer device determines the maximum historical insect situation index value as the maximum index threshold of the insect situation index indicator. If the minimum historical insect situation index value of the insect situation index indicator is lower than the minimum initial insect situation index threshold, the computer device determines the minimum historical insect situation index value as the minimum index threshold of the insect situation index indicator. If the maximum historical colony index value of the colony density indicator is lower than the maximum initial colony index threshold, the computer device determines the maximum historical colony index value as the maximum index threshold of the colony density indicator. If the minimum historical colony index value of the colony density indicator is lower than the minimum initial colony index threshold, the computer device determines the minimum historical colony index value as the minimum index threshold of the colony density indicator. If the maximum historical pollution index value of the pollution degree indicator is lower than the maximum initial pollution index threshold, the computer device determines the maximum historical pollution index value as the maximum index threshold of the pollution degree indicator. If the minimum historical pollution index value of the pollution degree indicator is lower than the minimum initial pollution index threshold, the computer device determines the minimum historical pollution index value as the minimum index threshold of the pollution degree indicator.

[0108] Step 306, if the extreme value of the historical index value is not lower than the initial index threshold, determine the initial index threshold as the index threshold of the tobacco leaf environmental indicator.

[0109] In implementation, if the second judgment result is that the maximum historical index value is not lower than the maximum initial index threshold, that is, the maximum historical index value is greater than or equal to the maximum initial index threshold, the computer device determines the maximum initial index threshold as the maximum index threshold. If the third judgment result is that the minimum historical index value is not lower than the minimum initial index threshold, that is, the minimum historical index value is greater than or equal to the minimum initial index threshold, the computer device determines the minimum initial index threshold as the minimum index threshold.

[0110] In an exemplary embodiment, if the maximum historical pest index value of the pest index is not lower than the maximum initial pest index threshold, the computer device determines the maximum initial pest index threshold as the maximum index threshold of the pest index. If the minimum historical pest index value of the pest index is not lower than the minimum initial pest index threshold, the computer device determines the minimum initial pest index threshold as the minimum index threshold of the pest index. If the maximum historical colony index value of the colony density index is not lower than the maximum initial colony index threshold, the computer device determines the maximum initial colony index threshold as the maximum index threshold of the colony density index. If the minimum historical colony index value of the colony density index is not lower than the minimum initial colony index threshold, the computer device determines the minimum initial colony index threshold as the minimum index threshold of the colony density index. If the maximum historical pollution index value of the pollution degree index is not lower than the maximum initial pollution index threshold, the computer device determines the maximum initial pollution index threshold as the maximum index threshold of the pollution degree index. If the minimum historical pollution index value of the pollution degree index is not lower than the minimum initial pollution index threshold, the computer device determines the minimum initial pollution index threshold as the minimum index threshold of the pollution degree index.

[0111] In an exemplary embodiment, Table 2 shows the index thresholds of each tobacco leaf environment index in an exemplary embodiment.

[0112] Table 2

[0113]

[0114] In Table 1 above, the maximum index threshold of the pest index is 20, and the minimum index threshold is 0. The maximum index threshold of the colony density index is 25, and the minimum index threshold is 0. The maximum index threshold of the pollution degree index is 19.5, and the minimum index threshold is 8.

[0115] In this embodiment, by determining the index threshold through the index threshold determination strategy between the extreme values of the historical index values and the initial index threshold, the evaluation criteria of the tobacco leaf environment index are optimized, and the accuracy of the data processing method is improved.

[0116] In an exemplary embodiment, such as Figure 4As shown, the specific processing procedure of step 206 includes steps 402 to 406. Among them:

[0117] Step 402: Perform data processing on the historical tobacco leaf environmental parameter set based on the environmental evaluation algorithm to obtain the historical index scores of each tobacco leaf environmental index.

[0118] Among them, the historical tobacco leaf environmental parameter set contains each tobacco leaf environmental index, and each tobacco leaf environmental index corresponds to each historical index value.

[0119] In implementation, for each tobacco leaf environmental index in the historical tobacco leaf environmental parameter set, the computer device performs data processing on each historical index value corresponding to the tobacco leaf environmental index according to the environmental evaluation algorithm to obtain each historical index score.

[0120] Specifically, the environmental evaluation algorithm is as shown in the following formula (1):

[0121] (1)

[0122] Among them, in the above formula (1), represents the environmental evaluation algorithm, is the historical index value, is the preset initial minimum index threshold. is the preset initial maximum index threshold. is the preset initial scoring factor. The computer device determines the initial minimum index threshold, the initial maximum index threshold, and the initial scoring factor corresponding to the tobacco leaf environmental index for each tobacco leaf environmental index in the historical tobacco leaf environmental parameter set. For each historical index value corresponding to the tobacco leaf environmental index, if the historical index value is less than or equal to the initial minimum index threshold, the computer device determines that the initial historical index score of the historical index value is 100 points. If the historical index value is greater than or equal to the initial maximum index threshold, the computer device determines that the initial historical index score of the historical index value is 0 points. If the historical index value is greater than the initial minimum index threshold and less than the initial maximum index threshold, the computer device performs data processing on the initial minimum index threshold, the initial scoring factor, and the historical index value according to the environmental evaluation algorithm to obtain the initial historical index score. Then, the computer device performs weighted processing on the initial historical index scores of each tobacco leaf environmental index according to the weights of each environmental evaluation index to obtain the historical index score.

[0123] In an exemplary embodiment, the tobacco leaf environmental indicators include the pest index indicator, the colony density indicator, and the pollution degree indicator. In the historical tobacco leaf environmental parameter set, the historical indicator value corresponding to the pest index indicator is the historical pest index value, the historical indicator value corresponding to the colony density indicator is the historical colony index value, and the historical indicator value corresponding to the pollution degree indicator is the historical pollution index value. Table 3 shows the historical tobacco leaf environmental parameter set presented in tabular form in one embodiment.

[0124] Table 3

[0125]

[0126] The initial indicator thresholds and initial scoring factors preset in the computer device are shown in Table 4 below.

[0127] Table 4

[0128]

[0129] The computer device presets the weights of each environmental evaluation indicator. Specifically, the weight of the pest index indicator is 0.4, the weight of the colony density indicator is 0.4, and the weight of the pollution degree indicator is 0.4.

[0130] Taking the calculation of the historical indicator score corresponding to the historical pest index value in January as an example, since the historical pest index value in January is equal to the initial minimum indicator threshold of the pest index indicator, the computer device determines the initial historical indicator score corresponding to the historical pest index value in January as 0. The computer device performs weighted processing on the initial historical indicator score according to the weight of the pest index indicator, and obtains a historical indicator score of 0.

[0131] Taking the calculation of the historical indicator score corresponding to the historical pest index value in October as an example, since the historical pest index value in October is greater than the initial minimum indicator threshold 0 of the pest index indicator and less than the initial maximum indicator threshold 90 of the pest index indicator. Therefore, the computer device processes the data of the initial minimum indicator threshold 0, the initial scoring factor 0.010, and the historical indicator value 10 according to the environmental evaluation algorithm to obtain the initial historical indicator score, and performs weighted operation according to the initial historical indicator score and the weight of the pest index indicator, and obtains a historical indicator score of 20.

[0132] The computer device processes the historical tobacco leaf environmental parameter set in Table 3 based on the environmental evaluation algorithm to obtain the historical indicator scores of each tobacco leaf environmental indicator, as shown in Table 5 below:

[0133] Table 5

[0134]

[0135] Among them, in the above Table 5, the column of the pest index indicator is the historical indicator scores corresponding to the historical pest index values. The column of the colony density indicator is the historical indicator scores corresponding to the historical colony index values. The column of the pollution degree indicator is the historical indicator scores corresponding to the historical pollution index values.

[0136] Step 404: For each tobacco leaf environmental indicator, determine the lowest historical indicator score of the tobacco leaf environmental indicator among the historical indicator scores of the tobacco leaf environmental indicator.

[0137] In implementation, the computer device performs an addition process on the historical indicator scores of the same historical time period to obtain the historical comprehensive scores of each historical time period. The computer device determines the lowest historical comprehensive score among the historical comprehensive scores and determines the lowest score historical time period where the lowest historical comprehensive score is located. Then, for each tobacco leaf environmental indicator, the computer device determines the historical indicator score corresponding to the lowest score historical time period as the lowest historical indicator score.

[0138] In an exemplary embodiment, taking Table 5 above as an example, the computer device performs an addition process on the historical indicator scores of the same historical time period to obtain the historical comprehensive score of this historical time period. The computer device determines 19.11 as the lowest historical comprehensive score among the historical comprehensive scores and determines September as the lowest score historical time period. Then, the computer device determines 9.43 as the lowest historical indicator score of the pest index indicator and determines 4.71 as the lowest historical indicator score of the colony density indicator. At the same time, the computer device determines 4.97 as the lowest historical indicator score of the pollution degree indicator.

[0139] Step 406: Update the scoring factors of the tobacco leaf environmental indicators according to the lowest historical indicator scores and the environmental evaluation algorithm.

[0140] In implementation, the computer device is pre-set with a downward adjustment ratio. The computer device performs a downward adjustment process on the historical indicator scores according to the downward adjustment ratio to obtain the historical indicator scores after adjustment. Then, the computer device performs data processing according to the environmental evaluation algorithm, the historical indicator scores after adjustment of each tobacco leaf environmental indicator, and the pre-set initial minimum indicator threshold to obtain new scoring factors, and updates the scoring factors of the tobacco leaf environmental indicators according to the new scoring factors to obtain the updated scoring factors.

[0141] In an exemplary embodiment, the preset downward adjustment ratio in the computer device is 20%. The lowest historical index score of the pest index is 9.43, the lowest historical index score of the colony density index is 4.71, and the lowest historical index score of the pollution degree index is 4.97. The computer device reduces the lowest historical index score of the pest index by 20% to obtain the adjusted historical index score of 7.54 for the pest index. The computer device reduces the lowest historical index score of the colony density index by 20% to obtain the adjusted historical index score of 3.76 for the colony density index. The computer device reduces the lowest historical index score of the pollution degree index by 20% to obtain the adjusted historical index score of 3.97 for the pollution degree index.

[0142] Then, based on the environmental evaluation algorithm, the adjusted historical index score of 7.54 for the pest index, and the preset initial minimum index threshold of 0, the computer device determines the new scoring factor as 0.013 and updates the scoring factor of the pest index according to the new scoring factor. Based on the environmental evaluation algorithm, the adjusted historical index score of 3.76 for the colony density index, and the preset initial minimum index threshold of 0, the computer device determines the new scoring factor as 0.015 and updates the scoring factor of the colony density index according to the new scoring factor. Based on the environmental evaluation algorithm, the adjusted historical index score of 3.97 for the pollution degree index, and the preset initial minimum index threshold of 8, the computer device determines the new scoring factor as 0.033 and updates the scoring factor of the pollution degree index according to the new scoring factor. Table 6 is the evaluation factor update parameter table for each tobacco leaf environmental index.

[0143] Table 6

[0144]

[0145] In this embodiment, by updating the scoring factors of each tobacco leaf environmental index through the environmental evaluation algorithm, the scoring factors are optimized, the accuracy of the scoring factors is improved, which facilitates the determination of the comprehensive score based on the optimized scoring factors, and further improves the accuracy of the data processing method.

[0146] In an exemplary embodiment, the index threshold includes the highest index threshold and the lowest index threshold. As Figure 5 shown, the specific processing process of step 104 includes steps 502 to 506. Among them:

[0147] Step 502, for each index value in the tobacco leaf environmental parameter set, if the index value is less than or equal to the lowest index threshold, determine that the evaluation level where the index value is located is the first evaluation level.

[0148] Among them, the evaluation levels include the first evaluation level, the second evaluation level, and the third evaluation level. The lowest index threshold is the minimum index threshold, and the highest index threshold is the maximum index threshold.

[0149] In implementation, for each tobacco leaf environmental index in the set of tobacco leaf environmental parameters, the computer device determines the index threshold corresponding to the tobacco leaf environmental index. The index threshold includes the lowest index threshold and the highest index threshold. The computer device determines whether the index value is less than or equal to the lowest index threshold and determines whether the index value is greater than or equal to the highest index threshold. If the index value is less than or equal to the lowest index threshold, the computer device determines the first evaluation level as the evaluation level where the index value is located.

[0150] In an exemplary embodiment, the tobacco leaf environmental indexes include the insect situation index, the colony density index, and the pollution degree index. Taking the insect situation index as an example, the computer device determines the maximum insect situation index threshold and the minimum insect situation index threshold corresponding to the insect situation index. The computer device determines whether the insect situation index value of the insect situation index is less than or equal to the minimum insect situation index threshold (the lowest insect situation index threshold) and determines whether the insect situation index value is greater than or equal to the maximum insect situation index threshold (the highest insect situation index threshold). If the insect situation index value is less than or equal to the lowest insect situation index threshold, the computer device determines the first evaluation level as the evaluation level where the insect situation index value is located.

[0151] Step 504, if the index value is greater than the lowest index threshold and less than the highest index threshold, determine that the evaluation level where the index value is located is the second evaluation level.

[0152] In implementation, if the index value is greater than the lowest index threshold and less than the highest index threshold, the computer device determines the evaluation level where the index value is located as the second evaluation level.

[0153] In an exemplary embodiment, taking the colony density index as an example, if the density index value corresponding to the colony density index is greater than the lowest density index threshold and less than the highest density index threshold, the computer device determines the second evaluation level as the level where the colony index value is located.

[0154] Step 506, if the index value is greater than or equal to the highest index threshold, determine that the evaluation level where the index value is located is the third evaluation level.

[0155] In implementation, if the index value is greater than or equal to the highest index threshold, the computer device determines the third evaluation level as the level where the index value is located.

[0156] In an exemplary embodiment, taking the pollution degree index as an example, if the pollution index value corresponding to the pollution degree index is greater than the lowest pollution index threshold and less than the highest pollution index threshold, the computer device determines the third evaluation level as the level where the pollution index value is located.

[0157] In this embodiment, by comparing the magnitude relationship between each index threshold and each index value, the evaluation level where each index value is located is determined, facilitating subsequent determination of the environmental evaluation rules for the index values based on the evaluation levels.

[0158] In an exemplary embodiment, as Figure 6 shown, the specific processing procedure of step 106 includes steps 602 to 606. Among them:

[0159] Step 602: Determine the environmental evaluation rule corresponding to the index value according to the evaluation level of each index value.

[0160] Among them, the environmental evaluation rules include the first environmental evaluation rule, the second environmental evaluation rule, and the third environmental evaluation rule.

[0161] In implementation, the corresponding relationship between each environmental evaluation rule and each evaluation level is pre-set in the computer device. For each index value, the computer device determines the environmental evaluation rule corresponding to the index value according to the evaluation level where the index value is located and the corresponding relationship between each environmental evaluation rule and each evaluation level.

[0162] Specifically, for each index value, if the evaluation level where the index value is located is the first evaluation level, the computer device determines that the environmental evaluation rule corresponding to the index value is the first environmental evaluation rule. If the evaluation level where the index value is located is the second evaluation level, the computer device determines that the environmental evaluation rule corresponding to the index value is the second environmental evaluation rule. If the evaluation level where the index value is located is the third evaluation level, the computer device determines that the environmental evaluation rule corresponding to the index value is the third environmental evaluation rule.

[0163] Step 604: Determine the index score of the tobacco leaf environmental index where the index value is located according to the environmental evaluation rule, the index value, and the scoring factor.

[0164] In implementation, the first index score and the second index score are pre-set in the computer device. The computer device determines the index score of the tobacco leaf environmental index where the index value is located based on the environmental evaluation rule, the first index score, the second index score, the index threshold, the index value, and the scoring factor.

[0165] Step 606: Perform weighted processing on the index scores of each tobacco leaf environmental index to obtain a comprehensive score.

[0166] In implementation, the weights of each tobacco leaf environmental index are pre-set in the computer device. The computer device performs weighted processing on the index scores of the tobacco leaf environmental index according to the weights of each tobacco leaf environmental index to obtain a comprehensive score.

[0167] Specifically, for each tobacco leaf environmental indicator, the computer device determines the product of the weight of the tobacco leaf environmental indicator and the indicator score. Then, the computer device performs an addition operation on the products of the tobacco leaf environmental indicators to obtain a comprehensive score.

[0168] In an exemplary embodiment, the tobacco leaf environmental indicators include a pest index indicator, a colony density indicator, and a pollution degree indicator. The computer device determines the product of the weight of the pest index indicator and the pest index score to obtain a weighted pest index score. Then, the computer device determines the product of the weight of the colony density indicator and the colony indicator score to obtain a weighted colony indicator score. The computer device determines the product of the weight of the pollution degree indicator and the pollution indicator score to obtain a weighted pollution indicator score. The computer device determines the sum of the weighted pest index score, the weighted colony indicator score, and the weighted pollution indicator score as the comprehensive score.

[0169] In an alternative embodiment, the weights of the pest index indicator, the colony density indicator, and the pollution degree indicator are determined according to the influence degrees of insects, molds, and PM2.5 on the storage quality of tobacco leaves. The pest index directly reflects the control level of tobacco insects in tobacco leaf storage. The spatial mold colony density (colony density) directly reflects the control level of tobacco leaf mildew in storage. The concentration of PM2.5 in the spatial air pollution has a greater impact on human health, and its impact on stored tobacco leaves is indirectly reflected through tobacco leaf mildew and tobacco leaf insect infestation. Therefore, the weights are determined based on the influence degrees of the three on the storage quality of tobacco leaves. The computer device sets the weights of the pest index indicator, the colony density indicator, and the pollution degree indicator as K1, K2, and K3 respectively, where K1 + K2 + K3 = 100%. Through the weighting method, for the direct influence degrees of mildew and insect infestation, generally, K1 is set to 40%, K2 is set to 40%, and K3 is set to 20%.

[0170] In this embodiment, according to the scoring factors of each tobacco leaf environmental indicator, the environmental evaluation rules under each evaluation level, and the indicator values of each tobacco leaf environmental indicator, the comprehensive score is determined, avoiding manual participation, realizing an objective evaluation of the effect of clean storage of tobacco leaf raw materials, establishing an evaluation standard for the effect of clean warehouses of tobacco leaf raw materials, and improving the accuracy of the data processing method.

[0171] In an exemplary embodiment, as Figure 7 shown, the specific processing procedure of step 604 includes steps 702 to 706. Among them:

[0172] Step 702, if the environmental evaluation rule is the first environmental evaluation rule, determine the preset first indicator score as the indicator score of the tobacco leaf environmental indicator where the indicator value is located.

[0173] In implementation, a first index score is preset in the computer device. If the environmental evaluation rule is the first environmental evaluation rule, the computer device determines that the index score of the tobacco leaf environmental index where the index value is located is the first index score.

[0174] Specifically, the first index score is 100. If the environmental evaluation rule is the first environmental evaluation rule, it indicates that the tobacco leaf environmental index where the index value is located is excellent. The computer device will determine that the index score of this tobacco leaf environmental index is full marks, that is, 100 points.

[0175] In an exemplary embodiment, taking the insect situation index as an example, the environmental evaluation rule of the insect situation index value of the insect situation index is the first environmental evaluation rule, and the computer device determines that the insect situation index score corresponding to the insect situation index is 100 points.

[0176] Step 704, if the environmental evaluation rule is the second environmental evaluation rule, perform data processing on the index value, index threshold, and scoring factor according to the second environmental evaluation algorithm to obtain the index score of the tobacco leaf environmental index where the index value is located.

[0177] Among them, the index threshold includes the lowest index threshold.

[0178] In implementation, if the environmental evaluation rule is the second environmental evaluation rule, the computer device determines the scoring factor of the tobacco leaf environmental index according to the tobacco leaf environmental index where the index value is located. Then, the computer device performs data processing on the index value, the lowest index threshold, and the scoring factor according to the second environmental evaluation algorithm to obtain the index score of the tobacco leaf environmental index.

[0179] Specifically, if the environmental evaluation rule is the second environmental evaluation rule, it indicates that the tobacco leaf environmental index where the mouse is located is medium. The second environmental evaluation algorithm is shown in the following formula (2):

[0180] (2)

[0181] In the above formula (2), is the index value, is the lowest index threshold, is the scoring factor. Taking the colony density index as an example, the environmental evaluation rule of the colony index value of the colony density index is the second environmental evaluation rule, and the computer device determines the scoring factor corresponding to the colony density index. Then, the computer device performs data processing on the colony index value, the lowest colony index threshold, and the scoring factor corresponding to the colony density index according to the second environmental evaluation algorithm to obtain the colony index score of the colony density index.

[0182] Step 706, if the environmental evaluation rule is the third environmental evaluation rule, determine the preset second index score as the index score of the tobacco leaf environmental index where the index value is located.

[0183] In implementation, a third index score is preset in the computer device. If the environmental evaluation rule is the third environmental evaluation rule, the computer device determines that the index score of the tobacco leaf environmental index where the index value is located is the second index score.

[0184] Specifically, the second index score is 0. If the environmental evaluation rule is the third environmental evaluation rule, it indicates that the tobacco leaf environmental index where the index value is located is poor. The computer device will determine that the index score of this tobacco leaf environmental index is 0 points.

[0185] In an exemplary embodiment, taking the pollution degree index as an example, the environmental evaluation rule of the pollution index value of the pollution degree index is the third environmental evaluation rule, and the computer device determines that the index score of the pest situation index corresponding to the colony density index is 0 points.

[0186] In this embodiment, the index score is determined based on the index value of each tobacco leaf environmental index and the environmental evaluation rule adapted to this tobacco leaf environmental index, which improves the accuracy of the index score, and further improves the accuracy of the data processing method.

[0187] It should be understood that although the steps in the flowcharts involved in the above-mentioned embodiments are sequentially shown according to the indication of the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear description in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same moment, but can be executed at different moments. The execution order of these steps or stages is not necessarily sequential, but can be executed alternately or alternately with at least a part of other steps or steps or stages in other steps.

[0188] Based on the same inventive concept, the embodiment of the present application also provides a data processing device for implementing the data processing method involved above. The implementation solution for solving problems provided by this device is similar to the implementation solution recorded in the above method. Therefore, the specific limitations in one or more data processing device embodiments provided below can refer to the limitations on the data processing method in the above text, and will not be repeated here.

[0189] In an exemplary embodiment, as Figure 8 shown, a data processing device 800 is provided, including: a first acquisition module 801, a first determination module 802, and a second determination module 803, where:

[0190] A first acquisition module 801 is configured to acquire a set of tobacco leaf environment parameters, a scoring factor, and an index threshold within a current time period; the scoring factor is determined according to a set of historical tobacco leaf environment parameters and an environment evaluation algorithm; the index threshold is determined according to a threshold determination strategy and a set of historical tobacco leaf environment parameters.

[0191] A first determination module 802 is configured to determine an evaluation grade where each index value in the set of tobacco leaf environment parameters is located according to the index threshold.

[0192] A second determination module 803 is configured to determine a comprehensive score based on the scoring factor, an environment evaluation rule under each evaluation grade, and the set of tobacco leaf environment parameters.

[0193] In an exemplary embodiment, the data processing device 800 further includes:

[0194] A second acquisition module is configured to acquire a set of historical tobacco leaf environment parameters and determine historical index value extremes of each tobacco leaf environment index in the set of historical tobacco leaf environment parameters.

[0195] A third determination module is configured to determine an index threshold of each tobacco leaf environment index based on a threshold determination strategy and each historical index value extreme.

[0196] A fourth determination module is configured to determine historical index scores of each historical index according to a set of historical tobacco leaf environment parameters and an environment evaluation algorithm, and determine a scoring factor among the historical index scores.

[0197] In an exemplary embodiment, the third determination module includes:

[0198] A first judgment sub-module is configured to, for each tobacco leaf environment index, judge whether a historical index value extreme of the tobacco leaf environment index is lower than a preset initial index threshold.

[0199] A first determination sub-module is configured to, if the historical index value extreme is lower than the initial index threshold, determine the historical index value extreme as the index threshold of the tobacco leaf environment index.

[0200] A second determination sub-module is configured to, if the historical index value extreme is not lower than the initial index threshold, determine the initial index threshold as the index threshold of the tobacco leaf environment index.

[0201] In an exemplary embodiment, the fourth determination module includes:

[0202] A first processing sub-module is configured to perform data processing on the set of historical tobacco leaf environment parameters based on the environment evaluation algorithm to obtain historical index scores of each tobacco leaf environment index.

[0203] A third determination sub-module is configured to, for each tobacco leaf environment index, determine the lowest historical index score of the tobacco leaf environment index among the historical index scores of the tobacco leaf environment index.

[0204] An update sub-module for updating the scoring factors of tobacco leaf environmental indicators according to the lowest historical indicator score and the environmental evaluation algorithm.

[0205] In an exemplary embodiment, the indicator threshold includes a highest indicator threshold and a lowest indicator threshold, and the second determination module includes:

[0206] A fourth determination sub-module for, for each indicator value in the tobacco leaf environmental parameter set, if the indicator value is less than or equal to the lowest indicator threshold, determining that the evaluation level where the indicator value is located is the first evaluation level.

[0207] A fifth determination sub-module for, if the indicator value is greater than the lowest indicator threshold and less than the highest indicator threshold, determining that the evaluation level where the indicator value is located is the second evaluation level.

[0208] A sixth determination sub-module for, if the indicator value is greater than or equal to the highest indicator threshold, determining that the evaluation level where the indicator value is located is the third evaluation level.

[0209] In an exemplary embodiment, the third determination module includes:

[0210] A seventh determination sub-module for determining the environmental evaluation rule corresponding to the indicator value according to the evaluation level of each indicator value.

[0211] An eighth determination sub-module for determining the indicator score of the tobacco leaf environmental indicator where the indicator value is located according to the environmental evaluation rule, the indicator value, and the scoring factor.

[0212] A ninth determination sub-module for performing a weighted process on the indicator scores of each tobacco leaf environmental indicator to obtain a comprehensive score.

[0213] In an exemplary embodiment, the eighth determination sub-module includes:

[0214] A tenth determination sub-module for, if the environmental evaluation rule is the first environmental evaluation rule, determining the preset first indicator score as the indicator score of the tobacco leaf environmental indicator where the indicator value is located.

[0215] A second processing sub-module for, if the environmental evaluation rule is the second environmental evaluation rule, performing data processing on the indicator value, the indicator threshold, and the scoring factor according to the second environmental evaluation algorithm to obtain the indicator score of the tobacco leaf environmental indicator where the indicator value is located.

[0216] An eleventh determination sub-module for, if the environmental evaluation rule is the third environmental evaluation rule, determining the preset second indicator score as the indicator score of the tobacco leaf environmental indicator where the indicator value is located.

[0217] Each module in the above data processing device can be implemented in whole or in part by software, hardware, or a combination thereof. Each of the above modules can be embedded in the processor of the computer device in hardware form or independent of the processor, or stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to each of the above modules.

[0218] In an exemplary embodiment, a computer device is provided. The computer device can be a terminal, and its internal structure diagram can be as Figure 9 shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit, and an input device. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface, the display unit, and the input device are connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals in a wired or wireless manner. The wireless manner can be implemented through WIFI, a mobile cellular network, near field communication (NFC), or other technologies. When the computer program is executed by the processor, it implements a data processing method. The display unit of the computer device is used to form a visually visible picture, which can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device can be a touch layer covering the display screen, or a button, a trackball, or a touchpad provided on the housing of the computer device, or an external keyboard, touchpad, or mouse, etc.

[0219] Those skilled in the art can understand that Figure 9 the structure shown in

[0220] is only a block diagram of some structures related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0221] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0222] In one embodiment, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0223] Those of ordinary skill in the art can understand that all or part of the processes in the above method embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the above method embodiments. Among them, any reference to a memory, database, or other medium used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in this application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in this application can be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, data processing logics based on quantum computing, artificial intelligence (AI) processors, etc., without limitation.

[0224] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope recorded in this application.

[0225] The above-described embodiments merely represent several implementation manners of this application, and the description thereof is relatively specific and detailed. However, it should not be construed as a limitation on the patent scope of this application. It should be noted that for those of ordinary skill in the art, without departing from the concept of this application, several modifications and improvements can still be made, and these all belong to the protection scope of this application. Therefore, the protection scope of this application shall be subject to the appended claims.

Claims

1. A data processing method, characterized in that, The method includes: Obtaining a set of tobacco leaf environmental parameters, a scoring factor, and an index threshold within a current time period; the scoring factor is determined according to a set of historical tobacco leaf environmental parameters and an environmental evaluation algorithm; the index threshold is determined according to a threshold determination strategy and the set of historical tobacco leaf environmental parameters; Determining the evaluation grade where each index value in the set of tobacco leaf environmental parameters is located according to the index threshold; Determining a comprehensive score based on the scoring factor, the environmental evaluation rules under each evaluation grade, and the set of tobacco leaf environmental parameters.

2. The method according to claim 1, wherein Before obtaining the set of tobacco leaf environmental parameters, the scoring factor, and the index threshold within the current time period, the method further includes: Obtaining a set of historical tobacco leaf environmental parameters and determining the extreme values of the historical index values of each tobacco leaf environmental index in the set of historical tobacco leaf environmental parameters; Determining the index threshold of each tobacco leaf environmental index based on the threshold determination strategy and the extreme values of the historical index values; Determining the historical index scores of each historical index according to the set of historical tobacco leaf environmental parameters and the environmental evaluation algorithm, and determining a scoring factor among the historical index scores.

3. The method according to claim 2, wherein The determining the index threshold of each tobacco leaf environmental index based on the threshold determination strategy and the extreme values of the historical index values includes: For each tobacco leaf environmental index, determining whether the extreme value of the historical index value of the tobacco leaf environmental index is lower than a preset initial index threshold; If the extreme value of the historical index value is lower than the initial index threshold, determining the extreme value of the historical index value as the index threshold of the tobacco leaf environmental index; If the extreme value of the historical index value is not lower than the initial index threshold, determining the initial index threshold as the index threshold of the tobacco leaf environmental index.

4. The method according to claim 2, wherein The determining the historical index scores of each historical index according to the set of historical tobacco leaf environmental parameters and the environmental evaluation algorithm, and determining a scoring factor among the historical index scores includes: Performing data processing on the set of historical tobacco leaf environmental parameters based on the environmental evaluation algorithm to obtain the historical index scores of each tobacco leaf environmental index; For each tobacco leaf environmental index, determining the lowest historical index score of the tobacco leaf environmental index among the historical index scores of the tobacco leaf environmental index; Updating the scoring factor of the tobacco leaf environmental index according to the lowest historical index score and the environmental evaluation algorithm.

5. The method according to claim 1, wherein The index threshold includes a highest index threshold and a lowest index threshold. The determining the evaluation grade where each index value in the set of tobacco leaf environmental parameters is located according to the index threshold includes: For each index value in the set of tobacco leaf environmental parameters, if the index value is less than or equal to the lowest index threshold, determining that the evaluation grade where the index value is located is the first evaluation grade; If the index value is greater than the lowest index threshold and less than the highest index threshold, determining that the evaluation grade where the index value is located is the second evaluation grade; If the index value is greater than or equal to the highest index threshold, determining that the evaluation grade where the index value is located is the third evaluation grade.

6. The method according to claim 1, characterized in that, The determining a comprehensive score based on the scoring factor, the environmental evaluation rules under each evaluation grade, and the set of tobacco leaf environmental parameters includes: Determine the environmental evaluation rules corresponding to the index values according to the evaluation levels of each of the said index values; Determine the index score of the tobacco leaf environmental index where the index value is located according to the environmental evaluation rules, the index value, and the scoring factor; Perform weighted processing on the index scores of each of the tobacco leaf environmental indexes to obtain a comprehensive score.

7. The method according to claim 6, characterized in that, The determining the index score of the tobacco leaf environmental index where the index value is located according to the environmental evaluation rules, the index value, and the scoring factor includes: If the environmental evaluation rule is the first environmental evaluation rule, determine the preset first index score as the index score of the tobacco leaf environmental index where the index value is located; If the environmental evaluation rule is the second environmental evaluation rule, perform data processing on the index value, the index threshold, and the scoring factor according to the second environmental evaluation algorithm to obtain the index score of the tobacco leaf environmental index where the index value is located; If the environmental evaluation rule is the third environmental evaluation rule, determine the preset second index score as the index score of the tobacco leaf environmental index where the index value is located.

8. A data processing device, characterized in that, The device includes: A first acquisition module, configured to acquire a set of tobacco leaf environmental parameters, a scoring factor, and an index threshold within a current time period; the scoring factor is determined according to a historical set of tobacco leaf environmental parameters and an environmental evaluation algorithm; the index threshold is determined according to a threshold determination strategy and the historical set of tobacco leaf environmental parameters; A first determination module, configured to determine the evaluation level where each index value in the set of tobacco leaf environmental parameters is located according to the index threshold; A second determination module, configured to determine a comprehensive score based on the scoring factor, the environmental evaluation rules under each of the evaluation levels, and the set of tobacco leaf environmental parameters.

9. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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