A method for constructing a dynamic hierarchical zoning resource model of graphite

Abstract

This invention discloses a method for constructing a dynamic graded and zoned graphite resource model, comprising the following steps: Step 1: Obtaining basic information data of the graphite resource system, including geographical location information of the graphite resource distribution area, including longitude and latitude; Step 2: Dividing the graphite resources into zones based on their location; Step 3: Obtaining the storage volume of graphite resources in different zones, establishing a database for storage, and further classifying the zones according to the existing content of graphite resources; Step 4: Establishing an existing content model based on the graphite resource content of the graded zones; Step 5: Obtaining the consumption volume of graphite resources in the graded zones over the past ten years, as well as the methods of graphite consumption, and establishing analysis models for different zones; Step 6: Coupled with the existing content model and the analysis model to obtain a dynamic model of graphite resource graded and zoned distribution, reflecting the content curves of graphite resources in different zones over the next ten years, as well as the methods of graphite consumption.

Description

Technical Field

[0001] This invention relates to the field of dynamic modeling technology, and in particular to a method for constructing a dynamic hierarchical partitioned resource model for graphite. Background Technology

[0002] A dynamic model is a model that describes the equilibrium relationships between the components of a system and between the system and its external environment, as well as the dynamic processes of these relationships. Dynamic models reflect the dynamic characteristics of the interaction of various factors during the system's motion and change. Compared to static models, they incorporate the time factor, thus enabling more effective simulation of real-world systems.

[0003] With the development of science and technology, the world's industrial technology is accelerating its transformation towards intelligentization, and more and more operations require the construction of dynamic models to achieve the expected results. When constructing a hierarchical and regional dynamic model of graphite resource distribution, it is necessary to establish a dynamic model that can realistically reflect the changes in reserves in different regions and accurately simulate the future remaining amount and consumption rate of graphite in different regions. Summary of the Invention

[0004] To overcome the shortcomings of existing technologies, this invention provides a method for constructing a dynamic hierarchical and zoning resource model for graphite. This dynamic model for graphite resource hierarchical and zoning can accurately simulate and calculate the remaining content M of graphite resources in different regions over the next ten years. S And the consumption rate ν.

[0005] To address the aforementioned technical problems, this invention provides the following technical solution: a method for constructing a dynamic graded and zoned graphite resource model, comprising the following steps: Step 1: Obtaining basic information data of the graphite resource system, including geographical location information of the graphite resource distribution area, the geographical location information including basic characteristic parameters of longitude and latitude; Step 2: Dividing the graphite resources into zones based on their location; Step 3: Obtaining the storage capacity of graphite resources in different zones, establishing a database for data storage, and further grading and dividing the zones according to the existing content of graphite resources; Step 4: Establishing an existing content model based on the graphite resource content of the graded zones; Step 5: Obtaining the consumption of graphite resources in the graded zones over the past ten years, as well as the methods of graphite consumption, and establishing analytical models for different zones; Step 6: Coupled with the existing content model and the analytical model to obtain a dynamic model of graphite resource grading and zoning, reflecting the content curves of graphite resources in different zones over the next ten years, as well as the methods of graphite consumption.

[0006] As a preferred technical solution of the present invention, the basic data for establishing the analysis model include M, ΔM and T, where M is the graphite resource content in different regions, ΔM is the graphite resource consumption in different regions, and T is time.

[0007] As a preferred technical solution of the present invention, when establishing the analysis model, accidental values ​​are added, including the amount and method of unexpectedly consumed graphite resources, as well as the amount and method of unexpectedly acquired graphite resources.

[0008] As a preferred technical solution of the present invention, when establishing the analysis model, the obtained data is analyzed by comparing data analysis methods and sensitivity analysis methods. The analysis data includes M, ΔM, T, the amount of graphite accidentally consumed and the amount of graphite accidentally obtained.

[0009] As a preferred technical solution of the present invention, the remaining content M of graphite resources in different regions over the next ten years is simulated and calculated using a dynamic model of graphite resource classification and zoning. S And the consumption rate ν.

[0010] As a preferred technical solution of the present invention, when performing sensitivity analysis, the influence of the amount of graphite accidentally consumed and the amount of graphite accidentally acquired on the overall content is studied from the perspective of quantitative analysis.

[0011] As a preferred technical solution of the present invention, comparative data analysis is conducted to compare and contrast the consumption amount, time, and consumption method, and to study whether the relationship among the three is coordinated and whether there are causal variables.

[0012] As a preferred technical solution of the present invention, when dividing the area into levels, the left and right errors in the area size between different areas do not exceed 100㎡.

[0013] Compared with the prior art, the beneficial effects that this invention can achieve are:

[0014] This construction method divides graphite resources into graded regions, with the area size of different regions varying by no more than 100 square meters, reducing the deviation of sample data within each region. It then establishes an existing content model based on the graphite resource reserves in different regions, and an analytical model based on the consumption rate and consumption methods in different regions. By incorporating two random variables—unexpected gains and unexpected consumption—into the analytical model, the final dynamic model and simulation data become more accurate. Coupled with the existing content model and the analytical model, a dynamic model of graphite resource grading and zoning is obtained, capable of accurately simulating and calculating the remaining graphite resource content M in different regions over the next ten years. S And the consumption rate ν. Attached Figure Description

[0015] Figure 1 This is a flowchart of the present invention; Detailed Implementation

[0016] To make the technical means, creative features, and achieved objectives and effects of this invention easier to understand, the invention is further described below with reference to specific embodiments. However, the following embodiments are merely preferred embodiments of this invention and not all of them. Other embodiments obtained by those skilled in the art based on the embodiments described herein without creative effort are all within the protection scope of this invention. Unless otherwise specified, the experimental methods in the following embodiments are conventional methods, and the materials and reagents used in the following embodiments are commercially available unless otherwise specified.

[0017] Example 1

[0018] Please refer to Figure 1 As shown, this invention provides a method for constructing a dynamic hierarchical and zoning resource model for graphite, comprising the following steps: Step 1: Obtaining basic information data of the graphite resource system, including geographical location information of the graphite resource distribution area, the geographical location information including basic characteristic parameters of longitude and latitude; Step 2: Dividing the graphite resources into zones according to their location; Step 3: Obtaining the storage capacity of graphite resources in different zones, establishing a database for data storage, and further classifying the zones according to the existing content of graphite resources; Step 4: Establishing an existing content model based on the graphite resource content of the graded zones; Step 5: Obtaining the storage capacity of graphite resources in the past ten... This paper analyzes the consumption of graphite resources in different regions over the years, as well as the methods of graphite consumption. The basic data for these models include M, ΔM, and T, where M represents the graphite resource content in different regions, ΔM represents the graphite resource consumption in different regions, and T represents time. Step six involves coupling the existing content model and the analysis model to obtain a dynamic model for graphite resource grading and zoning. This model reflects the graphite resource content curves and consumption methods in different regions over the next ten years. Using this dynamic model, the remaining graphite resource content M in different regions over the next ten years is simulated and calculated. S and consumption rate ν;

[0019] In a specific embodiment of the present invention, basic information data of the graphite resource system is first acquired, including geographical location information of the graphite resource distribution area. The geographical location information includes basic characteristic parameters of longitude and latitude. Then, the graphite resources are divided into regions based on their location. Next, the storage capacity of graphite resources in different regions is acquired, a database is established for data storage, and the regions are further classified according to the existing content of graphite resources. Then, an existing content model is established based on the graphite resource content of the classified regions. After the existing content model is established, the consumption of graphite resources in the classified regions over the past ten years and the mode of graphite consumption are acquired. An analysis model for different regions is established. The basic data for establishing the analysis model includes M, ΔM, and T, where M is the graphite resource content of different regions, ΔM is the graphite resource consumption of different regions, and T is time. Finally, the existing content model and the analysis model are coupled to obtain a dynamic model of graphite resource classification and zoning, which reflects the content curve of graphite resources in different regions and the mode of graphite consumption over the next ten years. Through the dynamic model of graphite resource classification and zoning, the remaining content M of graphite resources in different regions over the next ten years is simulated and calculated. S This construction method, based on the consumption rate ν, divides graphite resources into graded regions, establishes existing content models according to the reserves in different regions, and establishes analytical models according to the consumption rate and consumption patterns in different regions. The two models are coupled to obtain a dynamic model of graphite resource grading and zoning, which can accurately simulate and calculate the remaining graphite resource content M in different regions over the next ten years. S And the consumption rate ν.

[0020] Example 2

[0021] This embodiment is an improvement upon Embodiment 1. Please refer to the following for details. Figure 1 When establishing the analysis model, random values ​​are included, including the amount and method of unexpected consumption of graphite resources, as well as the amount and method of unexpected acquisition of graphite resources.

[0022] In this embodiment: When establishing a dynamic model for the classification and zoning of graphite resources, it is necessary to analyze and model the graphite resource content in different regions. During the process of establishing the analysis model, random values ​​are added, including the amount and method of unexpectedly consumed graphite resources, as well as the amount and method of unexpectedly acquired graphite resources. Adding random variables can improve the accuracy of the analysis model and make the final dynamic model and simulation data more accurate.

[0023] Example 3

[0024] This embodiment is an improvement upon Embodiment 1. Please refer to the following for details. Figure 1 When establishing the analytical model, the obtained data is analyzed by comparing data analysis methods and sensitivity analysis methods. The analyzed data includes M, △In sensitivity analysis, the amount of graphite consumed and acquired unexpectedly is studied from a quantitative perspective to investigate the impact of these three factors on the overall content. Comparative data analysis is then conducted to compare the amount, time, and method of consumption to investigate whether the relationship between the three factors is coordinated and whether there are causal variables.

[0025] In this embodiment: when establishing a dynamic model for the classification and zoning of graphite resources, it is necessary to analyze and model the graphite resource content of different regions. During the analysis and modeling process, the obtained data is analyzed by comparing data analysis methods and sensitivity analysis methods. The analyzed data includes M, △ M, T, the amount of graphite accidentally consumed and the amount of graphite accidentally acquired. In the sensitivity analysis, from a quantitative perspective, the impact of the amount of graphite accidentally consumed and acquired on the total content is studied. In the comparative data analysis, the consumption amount, time and consumption method are compared and compared to study whether the relationship between the three is coordinated and whether there are causal variables. This can improve the accuracy of the analysis results and make the final dynamic model and simulation data more accurate.

[0026] Example 4

[0027] This embodiment is an improvement upon Embodiment 1. Please refer to the following for details. Figure 1 When dividing the area into different zones, the left and right error in area size between different zones shall not exceed 100㎡;

[0028] In this embodiment: When establishing a dynamic model for the classification and zoning of graphite resources, it is necessary to first classify the regions according to the geographical information and storage content data of the graphite resources. When classifying the regions, the left and right error of the area size between different regions does not exceed 100㎡, so as to reduce the deviation of the sample data of each region, improve the accuracy of the analysis results, and make the final dynamic model and simulation data more accurate.

[0029] Working Principle: First, basic information data of the graphite resource system is acquired, including the geographical location information of the graphite resource distribution area. The geographical location information includes basic characteristic parameters such as longitude and latitude. Then, the graphite resources are divided into regions based on their location. Next, the storage capacity of graphite resources in different regions is acquired, and a database is established for data storage. Based on the existing content of graphite resources, the regions are further classified. When classifying the regions, the left-right error in area between different regions does not exceed 100㎡, which reduces the deviation of sample data in each region and improves the accuracy of the analysis results, making the final dynamic model and simulation data more accurate. Then, an existing content model is established based on the graphite resource content of the classified regions. After the existing content model is established, the consumption of graphite resources in the classified regions over the past ten years, as well as the methods of graphite consumption, are obtained to establish analysis models for different regions. The basic data for establishing the analysis model includes M, △ M and T, where M represents the graphite resource content in different regions. △ M represents the graphite resource consumption in different regions, and T represents time. During the model building process, random variables are incorporated, including the amount and method of unexpected graphite resource consumption, as well as the amount and method of unexpected graphite resource acquisition. Incorporating random variables improves the accuracy of the analytical model, making the final dynamic model and simulation data more accurate. In the modeling process, the obtained data is analyzed by comparing data analysis methods and sensitivity analysis methods. The analyzed data includes M, ΔM, T, the amount of unexpectedly consumed graphite, and the amount of unexpectedly acquired graphite. In the sensitivity analysis, the unexpectedly consumed graphite is studied from a quantitative perspective. The impact of quantity and unexpected graphite acquisition on the overall content is investigated. In the comparative data analysis, the consumption amount, time, and consumption method are compared to study the relationship between these three factors and whether causal variables exist. This improves the accuracy of the analysis results, making the final dynamic model and simulation data more accurate. Finally, the existing content model and the analytical model are coupled to obtain a dynamic model for graphite resource grading and zoning. This model reflects the graphite resource content curves in different regions over the next ten years, as well as the methods of graphite consumption. Using this dynamic model, the remaining graphite resource content M in different regions over the next ten years can be simulated and calculated. S This construction method, based on the consumption rate ν, divides graphite resources into graded regions, establishes existing content models according to the reserves in different regions, and establishes analytical models according to the consumption rate and consumption patterns in different regions. The two models are coupled to obtain a dynamic model of graphite resource grading and zoning, which can accurately simulate and calculate the remaining graphite resource content M in different regions over the next ten years. S And the consumption rate ν.

[0030] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for constructing a dynamic hierarchical partitioning resource model for graphite, characterized in that: Includes the following steps: Step 1: Obtain basic information data of the graphite resource system, including the geographical location information of the graphite resource distribution area, which includes basic characteristic parameters of longitude and latitude; Step 2: Divide the area into zones based on the location of the graphite resources; Step 3: Obtain the reserves of graphite resources in different areas, establish a database for data storage, and further classify the areas according to the existing content of graphite resources; Step 4: Establish an existing content model based on the graphite resource content of the graded regions; Step 5: Obtain the consumption of graphite resources in different regions over the past decade, as well as the methods of graphite consumption, and establish analytical models for different regions; the basic data for establishing the analytical models include M, ΔM and T, where M is the graphite resource content in different regions, ΔM is the graphite resource consumption in different regions, and T is time; Step Six: Couple the existing content model and the analysis model to obtain a dynamic model of graphite resource grading and zoning, which reflects the content curves of graphite resources in different regions and the way graphite is consumed in the next ten years.

2. The method for constructing a dynamic hierarchical partitioning resource model for graphite according to claim 1, characterized in that: When building the analytical model, random values ​​are included, including the amount and method of unexpected consumption of graphite resources, as well as the amount and method of unexpected acquisition of graphite resources.

3. The method for constructing a dynamic hierarchical partitioning resource model for graphite according to claim 2, characterized in that: When establishing the analytical model, the obtained data is analyzed by comparing data analysis methods and sensitivity analysis methods. The analyzed data includes M, ΔM, T, the amount of graphite consumed unexpectedly, and the amount of graphite gained unexpectedly.

4. The method for constructing a dynamic hierarchical partitioning resource model for graphite according to claim 1, characterized in that: Using a dynamic model of graphite resource grading and zoning, the remaining graphite resources in different regions over the next ten years can be simulated and calculated. And the consumption rate ν.

5. The method for constructing a dynamic hierarchical partitioning resource model for graphite according to claim 3, characterized in that: In conducting sensitivity analysis, from a quantitative perspective, the impact of the amount of graphite accidentally consumed and the amount of graphite accidentally acquired on the overall content was studied.

6. The method for constructing a dynamic hierarchical partitioning resource model for graphite according to claim 3, characterized in that: By conducting comparative data analysis, we can compare and contrast the consumption amount, time, and consumption method to study whether the relationship among the three is coordinated and whether there are causal variables.

7. The method for constructing a dynamic hierarchical partitioning resource model for graphite according to claim 1, characterized in that: When dividing the area into different zones, the size difference between different zones should not exceed 100㎡.

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