Agricultural material information management platform based on data analysis

Abstract

The invention relates to the technical field of agricultural material information management, in particular to an agricultural material information management platform based on data analysis. According to the invention, demand data of a single type of agricultural material products at a historical time node is acquired based on a demand data acquisition unit, and the acquired demand data is screened by using a mutual information method; meanwhile, a prediction model is utilized to predict the demands of the single type of agricultural material products at the next time node according to the screened demand data and the obtained environment data, and the demand data at the next time node can be predicted more accurately according to the data; whether agricultural material information management is qualified or not is judged based on the ratio of the predicted demand to the actual demand, and a corresponding processing mode is generated when the agricultural material information management is unqualified, so that whether prediction is accurate or not can be quickly judged, whether agricultural material information management is qualified or not is determined, and adjustment is more accurate when the agricultural material information management is unqualified. Therefore, the demand data of the agricultural material can be predicted more accurately, and the efficiency of agricultural material supply is further improved.

Description

Technical Field

[0001] The present invention relates to the technical field of agricultural resource information management, and in particular to an agricultural resource information management platform based on data analysis. Background Art

[0002] The agricultural inputs information management platform is an information technology tool for the agricultural sector, mainly used to integrate, monitor and optimize the full life cycle management of agricultural production materials (seeds, fertilizers, pesticides, agricultural machinery, etc.). However, there is currently a lack of data-driven decision-making support, resulting in resource waste or insufficient supply.

[0003] Chinese Patent Publication No.: CN118096025B discloses a cloud warehouse data analysis system and method for agricultural supplies in a cloud logistics environment. The data analysis system provided by the application includes a real-time cloud acquisition module, a historical cloud storage module, a data analysis module, an agricultural supply cloud adjustment module and an analysis and correction module. The data analysis module determines the inventory forecast value of each agricultural supply in the corresponding agricultural supply warehouse within a first preset time based on the warehouse data and the transportation data, and determines whether the inventory quantity of the corresponding agricultural supply needs to be adjusted based on each inventory forecast value; the agricultural supply cloud adjustment module determines the inventory adjustment strategy based on the transportation input quantity of a single agricultural supply within a second preset time, and determines the adjustment strategy for planning the transportation route based on the historical transportation data.

[0004] It can be seen that the following problems exist in the existing technology: no adjustments are made when agricultural input information management is unqualified, resulting in inaccurate prediction results of agricultural input demand data, and thus low efficiency in supplying agricultural inputs based on the prediction results. Summary of the Invention

[0005] To this end, the present invention provides an agricultural input information management platform based on data analysis to overcome the problem in the prior art that no adjustments are made when agricultural input information management is unqualified, resulting in inaccurate prediction results of agricultural input demand data, and thus low efficiency in supplying agricultural inputs based on the prediction results.

[0006] To achieve the above objectives, the present invention provides an agricultural input information management platform based on data analysis, comprising: An environmental data acquisition unit, which is used to acquire environmental data of any area at the next time node, wherein the environmental data includes temperature and humidity; A demand data acquisition unit, which is used to obtain demand data of a single type of agricultural product in the region at a historical time node; a data preprocessing unit connected to the demand data acquisition unit and configured to screen the demand data using a mutual information method; a prediction unit, connected to the environmental data acquisition unit and the data preprocessing unit, respectively, for predicting the demand for a single type of agricultural product at the next time point using a prediction model based on the filtered demand data and the environmental data to obtain a predicted demand; An inventory acquisition unit, which is used to calculate the actual demand for a single type of agricultural product at the next time point based on the dynamic changes in dealer inventory; an analysis unit, connected to the prediction unit and the inventory acquisition unit, respectively, for determining whether the agricultural input information management is qualified based on the ratio of the predicted demand to the actual demand of a single type of agricultural input product, and generating a corresponding treatment method based on the reason for the failure if the agricultural input information management is unqualified, wherein the treatment method includes adjusting the screening criteria, adjusting the preset ratio, issuing a notification to adjust the number of training iterations of the prediction model, and adjusting the demand data of historical time nodes; A control unit is connected to the analysis unit and is used to make adjustments based on the processing method.

[0007] Furthermore, the analysis unit is also used to determine whether the agricultural input information management is qualified based on the ratio of the predicted demand to the actual demand and the preset demand ratio, and to adjust the screening benchmark based on the difference between the ratio and the preset demand ratio, or to determine whether the agricultural input information management is qualified based on the variance of the historical ratio or the difference between the ratio and the preset demand ratio, or to adjust the screening benchmark based on the difference between the actual demand and the preset demand; wherein the historical ratio is the ratio of the historical predicted demand and the corresponding historical actual demand at different time nodes in historical moments.

[0008] Furthermore, the analysis unit is further configured to increase the screening benchmark based on a difference between the ratio and the preset required ratio, and the difference is proportional to an increase in the screening benchmark.

[0009] Furthermore, the analysis unit is also used to generate a corresponding processing method based on the comparison result of the variance of the historical ratio and the preset variance, including adjusting the screening benchmark based on the difference between the ratio and the preset demand ratio, or determining whether the agricultural input information management is qualified based on the difference between the integral of the drawn time-forecast demand curve and the integral of the drawn time-actual demand curve.

[0010] Furthermore, the analysis unit is also used to generate corresponding processing results based on the comparison result of the difference between the integral of the drawn time-forecast demand curve and the integral of the drawn time-actual demand curve and the preset integral difference, including adjusting the preset demand ratio based on the ratio of the difference and the preset integral difference, or determining whether the agricultural inputs information management is qualified.

[0011] Furthermore, the analysis unit is further configured to increase the preset demand ratio based on a ratio of the difference value to a preset integral difference value, and the ratio is proportional to an increase in the preset demand ratio.

[0012] Furthermore, the analysis unit is also used to generate a corresponding processing method based on the comparison result of the difference between the ratio and the preset demand ratio and the preset difference, including issuing a notification to adjust the number of training iterations of the prediction model, or determining whether the agricultural input information management is qualified based on the proportion of the number of expired products in the actual demand, or adjusting the screening benchmark based on the difference between the actual demand and the preset demand.

[0013] Furthermore, the analysis unit is also used to generate a corresponding processing method based on the comparison result between the proportion and the preset proportion, including determining whether the agricultural information management is qualified, or adjusting the screening benchmark based on the difference between the actual demand and the preset demand.

[0014] Furthermore, the analysis unit is further configured to lower the screening benchmark based on a difference between the actual demand and the preset demand, and the difference is proportional to a reduction extent of the screening benchmark.

[0015] Furthermore, the analysis unit is also used to increase the demand data of a single type of agricultural products at a historical time node based on the screening benchmark, and the screening benchmark is proportional to the increase in the demand data.

[0016] Compared with the prior art, the beneficial effect of the present invention lies in that the invention obtains the demand data of a single type of agricultural products at a historical time node based on a demand data acquisition unit, and uses the mutual information method to filter the obtained demand data, and at the same time uses the prediction model to predict the demand for a single type of agricultural products at the next time node based on the filtered demand data and the obtained environmental data, and can more accurately predict the demand data of the next time node based on the above data; and based on the ratio of predicted demand to actual demand, it determines whether the agricultural information management is qualified, and generates a corresponding processing method when it is unqualified, which can quickly determine whether the prediction is accurate, thereby determining whether the agricultural information management is qualified, and more accurately adjust it when it is unqualified, so that the demand data for agricultural products can be more accurately predicted, thereby further improving the efficiency of agricultural supply.

[0017] Furthermore, the present invention can quickly determine whether the agricultural input information management is qualified based on the ratio of predicted demand to actual demand and the ratio of preset demand, thereby improving the efficiency of determining the agricultural input information management, and further improving the efficiency of supplying agricultural inputs according to the prediction results.

[0018] Furthermore, the present invention increases the screening benchmark based on the difference between the ratio and the preset demand ratio, which can adjust the screening benchmark more accurately, thereby reducing the occurrence of unqualified data not being screened out due to a low screening benchmark, thereby making subsequent predictions based on the screened data more accurate, and further improving the efficiency of supplying agricultural materials based on the prediction results.

[0019] Furthermore, the present invention generates a corresponding processing method based on the comparison result of the variance of the historical ratio and the preset variance, which can more accurately determine whether the agricultural input information management is qualified according to the historical situation, thereby improving the efficiency of determining the agricultural input information management, and further improving the efficiency of supplying agricultural inputs according to the prediction results.

[0020] Furthermore, the present invention determines whether the agricultural input information management is qualified based on the comparison result of the difference between the integral of the drawn time-forecast demand curve and the integral of the drawn time-actual demand curve and the preset integral difference. It can more accurately determine whether the agricultural input information management is qualified based on the relationship between the predicted demand and the actual demand, thereby improving the efficiency of determining the agricultural input information management, and further improving the efficiency of supplying agricultural inputs according to the prediction results.

[0021] Furthermore, the present invention adjusts the preset demand ratio based on the ratio of the difference to the preset integral difference, and can adjust the preset demand ratio when the current agricultural product is in a low-demand stage, so as to more accurately determine whether the agricultural information management is qualified, thereby improving the efficiency of determining the agricultural information management, and further improving the efficiency of supplying agricultural materials according to the prediction results.

[0022] Furthermore, the present invention generates a corresponding processing method based on the comparison result of the difference between the ratio and the preset demand ratio and the preset difference, which can more accurately determine whether the agricultural input information management is qualified, thereby improving the efficiency of determining the agricultural input information management, and further improving the efficiency of supplying agricultural inputs according to the prediction results.

[0023] Furthermore, the present invention generates a corresponding processing method based on the comparison result of the proportion of the number of expired products in actual demand and the preset proportion, which can eliminate the misjudgment caused by confusion between products output due to expiration and products output due to demand. Therefore, by statistics on expired products to eliminate misjudgment, the result of determining whether the agricultural information management is qualified is made more accurate, thereby improving the efficiency of determining the agricultural information management, and further improving the efficiency of supplying agricultural materials according to the prediction results.

[0024] Furthermore, the present invention adjusts the screening benchmark based on the difference between actual demand and preset demand, which can eliminate the situation where the actual demand increases significantly due to an emergency, resulting in the ratio of preset demand to actual demand being lower than the preset demand ratio. Therefore, by adjusting the screening benchmark, it is possible to more accurately determine whether the agricultural input information management is qualified, thereby improving the efficiency of determining the agricultural input information management, and further improving the efficiency of supplying agricultural inputs according to the prediction results.

[0025] Furthermore, the present invention adjusts the demand data of a single type of agricultural products at a historical time node based on the screening benchmark, and can increase the demand data of a single type of agricultural products at a historical time node after lowering the screening benchmark. It can make the prediction results more accurate by increasing the amount of historical data, thereby making the result of determining whether the agricultural information management is qualified more accurate, thereby improving the efficiency of determining the agricultural information management, and further improving the efficiency of supplying agricultural products according to the prediction results. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 This is a schematic diagram of the structure of an agricultural input information management platform based on data analysis according to an embodiment of the present invention; Figure 2 A flowchart of the steps for implementing an agricultural input information management platform based on data analysis according to an embodiment of the present invention; Figure 3 A flowchart of the steps for determining the result of comparing the ratio of the predicted demand to the actual demand with the preset demand ratio according to an embodiment of the present invention; Figure 4 This is a flowchart of the steps for determining the result of comparing the difference between the ratio of the predicted demand to the actual demand and the preset demand ratio and the preset difference according to an embodiment of the present invention. DETAILED DESCRIPTION

[0027] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are merely used to explain the present invention and are not intended to limit the present invention.

[0028] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0029] It should be noted that, in the description of the present invention, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed connections, detachable connections, or integral connections; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; and internal connections between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0030] See also Figure 1 As shown, it is a structural diagram of the agricultural information management platform based on data analysis in an embodiment of the present invention.

[0031] The structure includes an environment data acquisition unit, a demand data acquisition unit, a data preprocessing unit, a prediction unit, an inventory acquisition unit, an analysis unit and a control unit.

[0032] The environmental data acquisition unit is used to acquire environmental data of any area at the next time point, wherein the environmental data includes temperature and humidity; The demand data acquisition unit is used to acquire demand data of a single type of agricultural product in the region at a historical time node; The data pre-processing unit is connected to the demand data acquisition unit and is used to screen the demand data using a mutual information method; The prediction unit is connected to the environmental data acquisition unit and the data preprocessing unit respectively, and is used to predict the demand for a single type of agricultural product at the next time node based on the filtered demand data and the environmental data using a prediction model to obtain a predicted demand; The inventory acquisition unit is used to calculate the actual demand for a single type of agricultural product at the next time point based on the dynamic changes in dealer inventory; The analysis unit is connected to the prediction unit and the inventory acquisition unit respectively, and is used to determine whether the agricultural input information management is qualified based on the ratio of the predicted demand to the actual demand of a single type of agricultural input product, and generate a corresponding processing method according to the reason for the failure if it is unqualified, wherein the processing method includes adjusting the screening criteria, adjusting the preset ratio, issuing a notification to adjust the number of training iterations of the prediction model, and adjusting the demand data of historical time nodes; The control unit is connected to the analysis unit and is configured to make adjustments based on the processing method.

[0033] Specifically, in this embodiment, the mutual information method is a feature selection method based on information theory, used to measure the correlation between features and target variables. For discrete features and targets, the joint probability distribution is directly calculated, while for continuous features and targets, non-parametric estimation (such as the k-nearest neighbor method or kernel density estimation) is used. The output of this step is the correlation score for each feature. All features are then ranked from high to low in correlation score. Finally, features with correlation scores exceeding the screening threshold are selected. The required data corresponding to the retained features are used in the following steps.

[0034] See also Figure 2 As shown, it is a flowchart of the steps of implementing the agricultural information management platform based on data analysis in an embodiment of the present invention.

[0035] The steps in the actual operation process of the platform described in the embodiment of the present invention include: S1, obtaining environmental data of any region at a next time point through the environmental data obtaining unit, wherein the environmental data includes temperature and humidity; S2, obtaining, by the demand data acquisition unit, demand data of a single type of agricultural product in the region at a historical time node; S3, screening the demand data by using a mutual information method through the data preprocessing unit connected to the demand data acquisition unit; S4, using a prediction model to predict the demand for a single type of agricultural input product at a next time point based on the filtered demand data and the environmental data by a prediction unit connected to the environmental data acquisition unit and the data preprocessing unit, to obtain a predicted demand; S5, calculating the actual demand for a single type of agricultural input product at the next time point based on the dynamic changes in dealer inventory through the inventory acquisition unit; S6, determining whether the agricultural input information management is qualified based on the ratio of the predicted demand to the actual demand of a single type of agricultural input product by an analysis unit respectively connected to the prediction unit and the inventory acquisition unit, and generating a corresponding processing method according to the reason for the failure if the agricultural input information management is unqualified, wherein the processing method includes adjusting the screening criteria, adjusting the preset ratio, issuing a notification to adjust the number of training iterations of the prediction model, and adjusting the demand data of historical time nodes; S7 , performing adjustment based on the processing method by a control unit connected to the analysis unit.

[0036] See also Figure 3As shown, it is a flowchart of the steps of determining the results of the comparison of the ratio of predicted demand to actual demand and the preset demand ratio according to an embodiment of the present invention. The analysis unit of the embodiment of the present invention is further configured to determine whether the agricultural input information management is qualified based on the ratio of the predicted demand to actual demand and the preset demand ratio, and to adjust the screening benchmark based on the difference between the ratio and the preset demand ratio, or to determine whether the agricultural input information management is qualified based on the variance of the historical ratio or the difference between the ratio and the preset demand ratio, or to adjust the screening benchmark based on the difference between the actual demand and the preset demand; wherein the historical ratio is the ratio of the historical predicted demand to the corresponding historical actual demand at different time points in the history.

[0037] Specifically, in this embodiment, the ratio L0 can be divided into a first preset demand ratio L1, a second preset demand ratio L2, a third preset demand ratio L3 and a fourth preset demand ratio L4. In the setting ratio standard, the first preset demand ratio L1=1.57, the second preset demand ratio L2=1.05, the third preset demand ratio L3=0.95 and the fourth preset demand ratio L4=0.61. It should be noted that, in other embodiments, the values of L1, L2, L3 and L4 can also be determined according to the needs of agricultural input information management; the comparison process based on the ratio L and L1, L2, L3 and L4 is as follows: If the ratio L is greater than or equal to the first preset required ratio L1, it indicates that there is a problem with the data pre-screening standard and unqualified data has not been screened out, then the screening benchmark is adjusted based on the difference P between the ratio and the preset required ratio; If the ratio L is less than the first preset demand ratio L1 and greater than the second preset demand ratio L2, since the predicted demand may be greater than the actual demand when it is set, it means that it is impossible to determine whether there are other factors causing this result. In this case, the agricultural input information management is determined to be qualified based on the variance Q of the historical ratios; If the ratio L is less than or equal to the second preset requirement ratio L2 and greater than or equal to the third preset requirement ratio L3, it is determined that the agricultural input information management is qualified; If the ratio L is less than the third preset requirement ratio L3 and greater than the fourth preset requirement ratio L4, it means that it is impossible to determine whether other factors cause this result at this time, then the difference R between the ratio and the preset requirement ratio is used to determine whether the agricultural input information management is qualified; If the ratio L is less than or equal to the fourth preset demand ratio L4, it indicates that the actual demand may have increased significantly due to sudden weather events, and the screening benchmark is adjusted based on the difference T between the actual demand and the preset demand.

[0038] Specifically, the analysis unit in the embodiment of the present invention is further configured to increase the screening benchmark based on a difference between the ratio and the preset required ratio, and the difference is proportional to the increase in the screening benchmark.

[0039] Specifically, in this embodiment, since the predicted demand may be greater than the actual demand when it is set, it is necessary to perform a secondary judgment in combination with historical data.

[0040] Specifically, in this embodiment, the preset difference P0 between the ratio and the preset required ratio is 0.1, and the comparison process based on the difference P and the preset difference P0 is as follows: If the difference P is less than or equal to the preset difference P0, the screening benchmark is adjusted to 1.2 times the original screening benchmark; If the difference P is greater than the preset difference P0, the screening benchmark is adjusted to 1.8 times the original screening benchmark.

[0041] Specifically, the analysis unit described in the embodiment of the present invention is also used to generate a corresponding processing method based on the comparison result of the variance of the historical ratio and the preset variance, including adjusting the screening benchmark based on the difference between the ratio and the preset demand ratio, or determining whether the agricultural input information management is qualified based on the difference between the integral of the drawn time-forecast demand curve and the integral of the drawn time-actual demand curve.

[0042] Specifically, in this embodiment, the preset variance Q0 of the historical ratio is 0.98, and the comparison process based on the variance Q of the historical ratio and the preset variance Q0 is as follows: If the variance Q is less than or equal to the preset variance Q0, it indicates that the historical ratio has a low discreteness and the agricultural input information management is determined to be unqualified, and the screening benchmark is adjusted based on the difference between the ratio and the preset requirement ratio; If the variance Q is greater than the preset variance Q0, it means that the discreteness of the historical ratio is high, and a time-forecast demand curve and a time-actual demand curve are drawn. The difference U between the integral of the drawn time-forecast demand curve and the integral of the drawn time-actual demand curve is used to determine whether the agricultural inputs information management is qualified.

[0043] Specifically, the analysis unit described in the embodiment of the present invention is also used to generate corresponding processing results based on the comparison result of the difference between the integral of the drawn time-forecast demand curve and the integral of the drawn time-actual demand curve and the preset integral difference, including adjusting the preset demand ratio based on the ratio of the difference and the preset integral difference, or determining whether the agricultural inputs information management is qualified.

[0044] Specifically, in this embodiment, the next time node is set to December, the historical time node is the previous 11 months, and the unit of the actual demand or predicted demand of pesticides represented by the vertical axis is tons. The preset integral difference U0=10, then the comparison process of the difference U based on the integral of the drawn time-predicted demand curve and the integral of the drawn time-actual demand curve and the preset integral difference U0 is as follows: If the difference U is greater than the preset integral difference U0, it indicates that the current time node is in a low demand stage for the agricultural product, and the preset demand ratio is adjusted based on the ratio V of the difference to the preset integral difference; If the difference U is less than or equal to the preset integral difference U0, it means that the part where the predicted demand exceeds the actual demand is a model set for emergency situations, and the agricultural inputs information management is determined to be qualified.

[0045] Specifically, the analysis unit in the embodiment of the present invention is further configured to increase the preset demand ratio based on the ratio of the difference value to the preset integral difference value, and the ratio is proportional to the increase of the preset demand ratio.

[0046] Specifically, in this embodiment, based on the preset ratio V0 of the difference value to the preset integral difference value=1.1, the comparison process based on the ratio V of the difference value to the preset integral difference value and the preset ratio V0 is as follows: If the ratio V is less than or equal to the preset ratio V0, the preset demand ratio is adjusted to 1.2 times the original preset demand ratio; If the ratio V is greater than the preset ratio V0, the preset demand ratio is adjusted to 1.7 times the original preset demand ratio.

[0047] See also Figure 4 , which is a flowchart of the steps for determining the quality of agricultural input information management based on the comparison result of the difference between the ratio of predicted demand to actual demand and the preset demand ratio and the preset difference according to an embodiment of the present invention. The analysis unit of this embodiment of the present invention is further configured to generate a corresponding processing method based on the comparison result of the difference between the ratio and the preset demand ratio and the preset difference, including issuing a notification to adjust the number of training iterations of the prediction model, or determining whether the agricultural input information management is qualified based on the proportion of the number of expired products in the actual demand, or adjusting the screening benchmark based on the difference between the actual demand and the preset demand.

[0048] Specifically, in this embodiment, the difference R0 can be divided into a first preset difference R1 and a second preset difference R2. In the setting difference standard, the first preset difference R1=0.15 and the second preset difference R2=0.05. It should be noted that, in other embodiments, the values of R1 and R2 can also be determined based on the needs of agricultural input information management; the comparison process based on the difference R and R1 and R2 is as follows: If the difference R is greater than or equal to the first preset difference R1, it means that the number of training iterations of the model is insufficient, resulting in the prediction result of the preset model being inaccurate, and a notification is issued to adjust the number of training iterations of the prediction model; If the difference R is less than the first preset difference R1 and greater than the second preset difference R2, it means that it is impossible to determine whether other factors cause this result. Then, the agricultural input information management is determined to be qualified based on the proportion W of the number of expired products in actual demand. If the difference R is less than or equal to the second preset difference R2, it is determined that the agricultural input information management is qualified.

[0049] Specifically, the analysis unit described in the embodiment of the present invention is also used to generate a corresponding processing method based on the comparison result between the proportion and the preset proportion, including determining whether the agricultural information management is qualified, or adjusting the screening benchmark based on the difference between the actual demand and the preset demand.

[0050] Specifically, in this embodiment, the preset proportion W0=0.2, and the comparison process based on the proportion W and the preset proportion W0 is as follows: If the proportion W is greater than the preset proportion W0, it means that the products output due to expiration are mixed with the products output due to demand, which may lead to misjudgment, and the agricultural input information management is determined to be qualified; If the proportion W is less than or equal to the preset proportion W0, it is determined that the actual demand may have increased due to an emergency, and the agricultural input information management is determined to be unqualified, and the screening benchmark is adjusted based on the difference M between the actual demand and the preset demand.

[0051] Specifically, the analysis unit in the embodiment of the present invention is further configured to lower the screening benchmark based on the difference between the actual demand and the preset demand, and the difference is proportional to the extent of the reduction in the screening benchmark.

[0052] Specifically, in this embodiment, the preset difference M0 between the actual demand and the preset demand is 4, and the comparison process based on the difference M between the actual demand and the preset demand and the preset difference M0 is as follows: If the difference M is less than or equal to the preset difference M0, the screening benchmark is adjusted to 0.9 times the original screening benchmark; If the difference M is greater than the preset difference M0, the screening criterion is adjusted to 0.62 times the original screening criterion.

[0053] Specifically, the analysis unit in the embodiment of the present invention is further configured to increase the demand data of a single type of agricultural product at a historical time node based on the screening benchmark, and the screening benchmark is proportional to the increase in the demand data.

[0054] Specifically, in this embodiment, the preset screening benchmark N0=0.09, and the comparison process based on the screening benchmark N and the preset screening benchmark N0 is as follows: If the screening benchmark N is less than or equal to the preset screening benchmark N0, the demand data is adjusted to 1.6 times the original demand data; If the screening criterion N is greater than the preset screening criterion N0, the demand data is adjusted to 2.1 times the original demand data.

[0055] Thus far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art may make equivalent changes or substitutions to the relevant technical features, and the technical solutions after such changes or substitutions will fall within the scope of protection of the present invention.

[0056] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that the present invention is susceptible to various modifications and variations. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. An agricultural information management platform based on data analysis, characterized in that: include: An environmental data acquisition unit, which is used to acquire environmental data of any area at the next time node, wherein the environmental data includes temperature and humidity; A demand data acquisition unit, which is used to obtain demand data of a single type of agricultural product in the region at a historical time node; a data preprocessing unit connected to the demand data acquisition unit and configured to screen the demand data using a mutual information method; a prediction unit, connected to the environmental data acquisition unit and the data preprocessing unit, respectively, for predicting the demand for a single type of agricultural product at the next time point using a prediction model based on the filtered demand data and the environmental data to obtain a predicted demand; An inventory acquisition unit, which is used to calculate the actual demand for a single type of agricultural product at the next time point based on the dynamic changes in dealer inventory; an analysis unit, connected to the prediction unit and the inventory acquisition unit, respectively, for determining whether the agricultural input information management is qualified based on the ratio of the predicted demand to the actual demand of a single type of agricultural input product, and generating a corresponding treatment method based on the reason for the failure if the agricultural input information management is unqualified, wherein the treatment method includes adjusting the screening criteria, adjusting the preset ratio, issuing a notification to adjust the number of training iterations of the prediction model, and adjusting the demand data of historical time nodes; A control unit is connected to the analysis unit and is used to make adjustments based on the processing method.

2. The agricultural input information management platform based on data analysis according to claim 1 is characterized in that: The analysis unit is further configured to determine whether the agricultural input information management is qualified based on the ratio of the predicted demand to the actual demand and the preset demand ratio, and to adjust a screening benchmark based on a difference between the ratio and the preset demand ratio, or to determine whether the agricultural input information management is qualified based on a variance of historical ratios or a difference between the ratio and the preset demand ratio, or to adjust a screening benchmark based on the difference between the actual demand and the preset demand; Among them, the historical ratio is the ratio of the historical predicted demand at different time nodes in the historical moment to the corresponding historical actual demand.

3. The agricultural input information management platform based on data analysis according to claim 2 is characterized in that: The analyzing unit is further configured to increase the screening benchmark based on a difference between the ratio and the preset required ratio, and the difference is proportional to an increase in the screening benchmark.

4. The agricultural input information management platform based on data analysis according to claim 2 is characterized in that: The analysis unit is also used to generate a corresponding processing method based on the comparison result of the variance of the historical ratio and the preset variance, including adjusting the screening benchmark based on the difference between the ratio and the preset demand ratio, or determining whether the agricultural input information management is qualified based on the difference between the integral of the drawn time-forecast demand curve and the integral of the drawn time-actual demand curve.

5. The agricultural input information management platform based on data analysis according to claim 4 is characterized in that: The analysis unit is also used to generate corresponding processing results based on the comparison result of the difference between the integral of the drawn time-forecast demand curve and the integral of the drawn time-actual demand curve and the preset integral difference, including adjusting the preset demand ratio based on the ratio of the difference and the preset integral difference, or determining that the agricultural inputs information management is qualified.

6. The agricultural input information management platform based on data analysis according to claim 5 is characterized in that: The analyzing unit is further configured to increase the preset demand ratio based on a ratio of the difference value to the preset integral difference value, and the ratio is proportional to an increase in the preset demand ratio.

7. The agricultural input information management platform based on data analysis according to claim 2 is characterized in that: The analysis unit is also used to generate a corresponding processing method based on the comparison result of the difference between the ratio and the preset demand ratio and the preset difference, including issuing a notification to adjust the number of training iterations of the prediction model, or determining whether the agricultural input information management is qualified based on the proportion of the number of expired products in the actual demand, or adjusting the screening benchmark based on the difference between the actual demand and the preset demand.

8. The agricultural input information management platform based on data analysis according to claim 7 is characterized in that: The analysis unit is also used to generate a corresponding processing method based on the comparison result of the proportion and the preset proportion, including determining whether the agricultural input information management is qualified, or adjusting the screening benchmark based on the difference between the actual demand and the preset demand.

9. The agricultural input information management platform based on data analysis according to claim 7, characterized in that: The analysis unit is further configured to lower the screening benchmark based on a difference between the actual demand and the preset demand, and the difference is proportional to a reduction extent of the screening benchmark.

10. The agricultural input information management platform based on data analysis according to claim 9, characterized in that: The analysis unit is further configured to increase the demand data of a single type of agricultural product at a historical time node based on the screening benchmark, and the screening benchmark is proportional to the increase in the demand data.

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