Economic value estimation method and system based on natural resource asset package

Abstract

The invention belongs to the technical field of economic value evaluation, and discloses an economic value estimation method and system based on a natural resource asset package, and the method comprises the steps: processing natural resource data through employing a natural language processing technology; identifying spatial distribution modes of different natural resource data by applying a geographic information technology, and defining a spatial range of an asset package; integrating the space range of the asset package and the physical quantity data by using geographic information processing software, establishing a physical quantity data set, and constructing an asset package evaluation model in combination with a machine learning algorithm; and evaluating the asset package by using the asset package evaluation model to obtain an asset package score, and establishing an asset package price system based on the natural resource type to obtain the economic value of the asset package. According to the method, the natural resource data of various sources are acquired and input, and the spatial range of the asset package is precisely defined by using the geographic information technology, so that the integrity and accuracy of the data are ensured, and a basis is provided for subsequent resource management and planning.

Description

Technical Field

[0001] The present invention relates to the technical field of economic value assessment, and particularly to an economic value estimation method and system based on a natural resource asset package. Background Art

[0002] As the material basis of human social and economic activities, the rational utilization and protection of natural resources play a crucial role in achieving sustainable development. However, in the aspect of the value assessment of natural resource assets, there is currently a lack of a comprehensive, efficient and real-time assessment method.

[0003] Traditional natural resource asset assessment methods have many deficiencies. First, the assessment cycle is long. Since the formation and development process of natural resources often takes several years or even decades, a comprehensive consideration of its long-term formation process and changing trends is necessary for accurate assessment, which undoubtedly increases the complexity and time cost of assessment. At the same time, the data required for natural resource asset assessment involves multiple aspects such as the quantity, quality, distribution, and utilization status of natural resources. These data are difficult to obtain comprehensively and accurately, and the data processing and analysis processes are cumbersome, further prolonging the assessment cycle.

[0004] Secondly, the assessment efficiency is low. Traditional assessment methods involve multiple links and steps such as on-site investigation, data collection, analysis and calculation, and expert review. The problems of connection and coordination between these links and steps are likely to lead to a cumbersome assessment process and low efficiency. In addition, most traditional assessment methods rely on manual operations, such as manual data recording, calculation and analysis, etc. This manual operation method not only takes time and effort, but also is prone to errors, seriously affecting the assessment efficiency.

[0005] Finally, the assessment results are one-sided and inaccurate. Traditional economic value estimation methods often only consider the value of a single resource, while ignoring the comprehensive consideration of other resources and their interrelationships, which leads to deviations in the assessment results and lack of comprehensiveness and accuracy.

[0006] Therefore, how to provide an economic value estimation method and system based on a natural resource asset package is an urgent problem to be solved at present. Summary of the Invention

[0007] Embodiments of the present invention provide an economic value estimation method and system based on a natural resource asset package to solve the above technical problems existing in the prior art.

[0008] To provide a basic understanding of some aspects of the disclosed embodiments, a simple summary is given below. This summary part is not a general review, nor is it intended to identify key / important constituent elements or delineate the protection scope of these embodiments. Its sole purpose is to present some concepts in a simple form as a prelude to the detailed description that follows.

[0009] According to the first aspect of the embodiments of the present invention, there is provided an economic value estimation method based on a natural resource asset package.

[0010] In one embodiment, an economic value estimation method based on a natural resource asset package includes: Obtain natural resource data from a multi-source data platform, process the natural resource data using natural language processing technology, and enter the processed natural resource data into a database. The natural resource data includes physical quantity data and price signal data; Use geographic information technology to perform spatial analysis on the natural resource data stored in the database, identify the spatial distribution patterns of different natural resource data, and define the spatial scope of the asset package; Use geographic information processing software to integrate the spatial scope of the asset package with the physical quantity data to establish a physical quantity data set, and construct an asset package evaluation model in combination with a machine learning algorithm; Use the asset package evaluation model to evaluate the asset package to obtain an asset package score, and establish an asset package price system based on the natural resource type; According to the asset package price system and the economic value calculation formula, obtain the economic value of the asset package.

[0011] In one embodiment, the use of geographic information technology to perform spatial analysis on the natural resource data stored in the database, identify the spatial distribution patterns of different natural resource data, and define the spatial scope of the asset package includes: According to the natural resource data stored in the database, use a data fusion algorithm to fuse and process natural resource data from different sources; Based on the fused natural resource data, use a spatial analysis algorithm to identify the spatial distribution patterns of the natural resource data and analyze the distribution characteristics of different resources in the geographical space; Combined with the identified spatial distribution patterns, use a regional optimization algorithm to define the boundaries of the natural resource data and determine the spatial scope of the asset package.

[0012] In one embodiment, the combination of the identified spatial distribution patterns and the use of a regional optimization algorithm to define the boundaries of the natural resource data and determine the spatial scope of the asset package includes: According to the identified spatial distribution patterns, construct a spatial relationship network between natural resource data, and use graph theory algorithms to analyze the spatial connectivity of natural resource data to obtain the interaction relationship between natural resource data; Based on the obtained interaction relationship, evaluate the distribution trend of natural resource data in the target area by calculating the spatial autocorrelation coefficient, and identify and determine the spatial characteristics of the natural resource data. According to the spatial characteristics of natural resource data, use the regional optimization algorithm to delimit the boundary of natural resource data within the target area and determine the spatial scope of the asset package.

[0013] In one embodiment, based on the obtained interaction relationship, by calculating the spatial autocorrelation coefficient, evaluating the distribution trend of natural resource data within the target area, and identifying and determining the spatial characteristics of natural resource data include: By analyzing the interaction relationship between natural resource data, calculate the spatial autocorrelation coefficient of each natural resource data; Combined with the preset spatial interaction network model, assign weights to the calculated spatial autocorrelation coefficients, analyze the interaction intensity between natural resource data, and evaluate the distribution trend of natural resource data within the target area; According to the distribution trend of natural resource data and the spatial autocorrelation coefficient, use the regional optimization algorithm to identify the spatial characteristics of natural resource data within the target area.

[0014] In one embodiment, the calculation formula of the spatial autocorrelation coefficient is: ; In the formula, T i represents the spatial autocorrelation coefficient of natural resource data at position i ; x i represents the value of natural resource data at position i ; represents the average value of natural resource data at all positions; n represents the number of all observation positions; k represents the index value; x k represents the k th value of natural resource data at the observation position; j represents the index value; w ij represents the spatial relationship between position i and position j ; x j represents the j th value of natural resource data at the observation position.

[0015] In one embodiment, using the asset package evaluation model to evaluate the asset package, obtaining the asset package score, and establishing an asset package price system based on the natural resource type includes: Input the determined asset package into the asset package evaluation model, analyze the impact of the resource quality of natural resource data on the asset package benefits, and evaluate the contribution degree of different natural resource data in the asset package; According to the supply-demand relationship between market trends and natural resources, use the time series analysis algorithm to predict the economic value of the asset package, and combine the contribution degree of natural resource data in the asset package to obtain the asset package score. Based on the natural resource type and the obtained asset package score, use the income capitalization algorithm to establish a preliminary price system, and combine the regional economic factors to adjust the preliminary price system to construct the final asset package price system.

[0016] In one embodiment, the step of based on the natural resource type and the obtained asset package score, using the income capitalization algorithm to establish a preliminary price system, and combining the regional economic factors to adjust the preliminary price system to construct the final asset package price system includes: Classify the natural resource data according to the type of natural resources to identify different types of asset packages. According to different types of asset packages and the asset package score, use the income capitalization algorithm to preliminarily estimate the prices of different types of asset packages, and combine the historical natural resource data to determine the expected income and discount rate of different types of asset packages to establish a preliminary asset package price system. Collect the regional economic factors of the target area, use the preset data regression model to analyze the correlation between the regional economic factors and the asset package price, and use the weighted average algorithm to convert the regional economic factors into regional weighted adjustment factors. Use the regional weighted adjustment factors to adjust the preliminary asset package price system, and combine the market demand and resource supply situation to construct the final asset package price system.

[0017] In one embodiment, the step of obtaining the economic value of the asset package according to the asset package price system and the economic value calculation formula includes: According to the various resource patches in the asset package and their corresponding attributes, combined with the established asset package price system, use the economic value calculation formula to calculate the economic value of each resource patch. Accumulate the economic values of all resource patches to obtain the preliminary economic value of the asset package. Combine the synergy between different natural resource data in the asset package to adjust the preliminary economic value to obtain the final economic value of the asset package.

[0018] In one embodiment, the expression of the economic value calculation formula is: ; In the formula, Z represents the economic value of the resource patch; R represents the asset price of the resource patch; S represents the land type area of the resource patch.

[0019] According to the second aspect of the embodiments of the present invention, an economic value estimation system based on a natural resource asset package is provided.

[0020] In one embodiment, the economic value estimation system based on a natural resource asset package includes: A data acquisition and processing module, configured to obtain natural resource data from a multi-source data platform, process the natural resource data using natural language processing technology, and enter the processed natural resource data into a database, where the natural resource data includes physical quantity data and price signal data; An asset package definition module, configured to perform spatial analysis on the natural resource data stored in the database using geographic information technology, identify the spatial distribution patterns of different natural resource data, and define the spatial scope of the asset package; An evaluation model construction module, configured to integrate the spatial scope of the asset package and the physical quantity data using geographic information processing software to establish a physical quantity data set, and construct an asset package evaluation model in combination with machine learning algorithms; A price system establishment module, configured to evaluate the asset package using the asset package evaluation model to obtain an asset package score, and establish an asset package price system based on the natural resource type; An economic value calculation module, configured to obtain the economic value of the asset package according to the asset package price system and the economic value calculation formula.

[0021] According to the third aspect of the embodiments of the present invention, a computer device is provided.

[0022] In some embodiments, the computer device includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the steps of the above method are implemented.

[0023] According to the fourth aspect of the embodiments of the present invention, a computer-readable storage medium is provided.

[0024] In one embodiment, a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the above method are implemented.

[0025] The technical solutions provided by the embodiments of the present invention may include the following beneficial effects: 1. By acquiring and entering natural resource data from multiple sources and using geographic information technology to accurately define the spatial scope of the asset package, the present invention ensures the integrity and accuracy of the data, not only improving the accuracy and efficiency of resource management, but also being able to identify the interactions and synergistic effects between different resource types, providing a scientific basis for subsequent resource management and planning.

[0026] 2. By using the asset package evaluation model to evaluate the asset package, the scores obtained by the present invention comprehensively reflect the value potential of the asset package, taking into account the quality and benefit relationship of resources, as well as market trends and supply-demand relationships, making the evaluation results closer to the actual situation, thus ensuring the rationality and flexibility of the price system and better adapting to the dynamic changes of the market.

[0027] 3. By combining the asset package price system with the economic value calculation formula, the present invention can calculate the economic value of the asset package, providing a scientific basis for the development and utilization of natural resources, property rights transactions, etc., and further improving the efficiency and effectiveness of resource management and use.

[0028] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The drawings herein are incorporated into the specification and form a part of the specification, showing embodiments consistent with the present invention and used together with the specification to explain the principles of the present invention.

[0030] Figure 1 is a flowchart of a method for estimating the economic value of a natural resource asset package shown according to an exemplary embodiment; Figure 2 is a schematic block diagram of the principle of a system for estimating the economic value of a natural resource asset package shown according to an exemplary embodiment; Figure 3 is a schematic structural diagram of a computer device shown according to an exemplary embodiment. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0031] The following description and the accompanying drawings fully disclose specific embodiments herein, enabling those skilled in the art to practice them. Parts and features of some embodiments may be included in or replace parts and features of other embodiments. The scope of the embodiments herein includes the entire scope of the claims and all available equivalents of the claims. In this document, the terms "first", "second", etc. are only used to distinguish one element from another, without requiring or implying any actual relationship or order between these elements. In fact, the first element can also be called the second element, and vice versa. Moreover, the terms "comprising", "including" or any other variant thereof are intended to cover non-exclusive inclusion, such that a structure, device or equipment comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such structure, device or equipment. Without further limitation, an element defined by the statement "comprising one..." does not exclude the existence of additional identical elements in the structure, device or equipment comprising the said element. In the description of the embodiments herein, each embodiment is described in a progressive manner, with the emphasis of each embodiment being on the differences from other embodiments. The same or similar parts among the embodiments can be referred to each other.

[0032] In this document, the orientation or positional relationship indicated by the terms "longitudinal", "transverse", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing this document and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation on the present invention. In the description herein, unless otherwise specified and limited, the terms "mounted", "connected" and "coupled" shall be understood in a broad sense. For example, it may be a mechanical connection or an electrical connection, or may be the internal communication of two elements. It may be directly connected or indirectly connected through an intermediate medium. For those of ordinary skill in the art, the specific meanings of the above terms can be understood according to specific circumstances.

[0033] In this document, unless otherwise stated, the term "plurality" means two or more.

[0034] In this document, the character " / " indicates that the objects before and after are in an "or" relationship. For example, A / B means: A or B.

[0035] In this document, the term "and / or" is an associative relationship describing an object, indicating that three relationships can exist. For example, A and / or B means: A or B, or, A and B these three relationships.

[0036] It should be understood that although the steps in the flowchart are sequentially shown according to the indication of the arrows, these steps are not necessarily executed sequentially in the order indicated by the arrows. Unless there is a clear description in this article, there is no strict order limit for the execution of these steps, and these steps can be executed in other orders. Moreover, at least a part of the steps in the figure may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed alternately or in turn with at least a part of other steps or sub-steps or stages of other steps.

[0037] Each module in the device or system of the present application can be implemented in whole or in part by software, hardware, and their combination. The above-mentioned modules can be embedded in the processor of the computer device in hardware form or independent of it, 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.

[0038] Without conflict, the embodiments in the present invention and the features in the embodiments can be combined with each other.

[0039] Figure 1 An embodiment of a method for estimating the economic value based on a natural resource asset package of the present invention is shown.

[0040] In this optional embodiment, the method for estimating the economic value based on a natural resource asset package includes: Obtain natural resource data from a multi-source data platform, process the natural resource data using natural language processing technology, and enter the processed natural resource data into a database. The natural resource data includes physical quantity data and price signal data; Use geographic information technology to perform spatial analysis on the natural resource data stored in the database, identify the spatial distribution patterns of different natural resource data, and define the spatial scope of the asset package; Use geographic information processing software to integrate the spatial scope of the asset package with the physical quantity data, establish a physical quantity data set, and construct an asset package evaluation model in combination with a machine learning algorithm; Use the asset package evaluation model to evaluate the asset package, obtain an asset package score, and establish an asset package price system based on the natural resource type; According to the asset package price system and the economic value calculation formula, obtain the economic value of the asset package.

[0041] In this optional embodiment, the use of geographic information technology to perform spatial analysis on the natural resource data stored in the database, identify the spatial distribution patterns of different natural resource data, and define the spatial scope of the asset package includes: According to the natural resource data stored in the database, use a data fusion algorithm to fuse the natural resource data from different sources; Based on the fused natural resource data, use a spatial analysis algorithm to identify the spatial distribution pattern of the natural resource data and analyze the distribution characteristics of different resources in the geographical space; Combined with the identified spatial distribution pattern, use a regional optimization algorithm to define the boundary of the natural resource data and determine the spatial scope of the asset package.

[0042] In this alternative embodiment, the step of combining the identified spatial distribution pattern and using a regional optimization algorithm to define the boundary of the natural resource data and determine the spatial scope of the asset package includes: According to the identified spatial distribution pattern, construct a spatial relationship network between the natural resource data, and use graph theory algorithms to analyze the spatial connectivity of the natural resource data to obtain the interaction relationship between the natural resource data; Based on the obtained interaction relationship, by calculating the spatial autocorrelation coefficient, evaluate the distribution trend of the natural resource data in the target area, and identify and determine the spatial characteristics of the natural resource data; According to the spatial characteristics of the natural resource data, use a regional optimization algorithm to delimit the boundary of the natural resource data in the target area and determine the spatial scope of the asset package.

[0043] In this alternative embodiment, the step of based on the obtained interaction relationship, by calculating the spatial autocorrelation coefficient, evaluate the distribution trend of the natural resource data in the target area, and identify and determine the spatial characteristics of the natural resource data includes: By analyzing the interaction relationship between the natural resource data, calculate the spatial autocorrelation coefficient of each natural resource data; Combined with a preset spatial interaction network model, assign weights to the calculated spatial autocorrelation coefficients, analyze the interaction intensity between the natural resource data, and evaluate the distribution trend of the natural resource data in the target area; According to the distribution trend of the natural resource data and the spatial autocorrelation coefficient, use a regional optimization algorithm to identify the spatial characteristics of the natural resource data in the target area.

[0044] In this alternative embodiment, the calculation formula of the spatial autocorrelation coefficient is: ; In the formula, T i represents the spatial autocorrelation coefficient of the natural resource data at the location i ; x i represents the value of the natural resource data at the location i ; Represents the average value of natural resource data at all positions; n Represents the number of all observed positions; k Represents the index value; x k Represents the k value of natural resource data at the j th observed position; w ij Represents the position i and the position j spatial relationship between them; x j Represents the j value of natural resource data at the

[0045] In this alternative embodiment, evaluating the asset package using the asset package evaluation model to obtain an asset package score, and establishing an asset package price system based on the natural resource type includes: Inputting the determined asset package into the asset package evaluation model, analyzing the impact of the resource quality of natural resource data on the asset package benefits, and evaluating the contribution degree of different natural resource data in the asset package; According to the supply - demand relationship between the market trend and natural resources, using the time - series analysis algorithm to predict the economic value of the asset package, and combining with the contribution degree of natural resource data in the asset package to obtain the asset package score; Based on the natural resource type and the obtained asset package score, using the income capitalization algorithm to establish a preliminary price system, and adjusting the preliminary price system in combination with location economic factors to construct the final asset package price system.

[0046] In this alternative embodiment, based on the natural resource type and the obtained asset package score, using the income capitalization algorithm to establish a preliminary price system, and adjusting the preliminary price system in combination with location economic factors to construct the final asset package price system includes: Classifying natural resource data according to the type of natural resources to identify different types of asset packages; According to different types of asset packages and asset package scores, using the income capitalization algorithm to preliminarily estimate the prices of different types of asset packages, and combining with historical natural resource data to determine the expected income and discount rate of different types of asset packages, and establishing a preliminary asset package price system; Collecting the location economic factors of the target area, using a preset data regression model to analyze the correlation between the location economic factors and the asset package price, and using the weighted average algorithm to convert the location economic factors into location weighted adjustment factors; Using the location weighted adjustment factors to adjust the preliminary asset package price system, and combining with the market demand and resource supply situation to construct the final asset package price system.

[0047] In this alternative embodiment, obtaining the economic value of the asset package according to the asset package price system and the economic value calculation formula includes: Calculating the economic value of each resource patch according to the types of resource patches and corresponding attributes in the asset package, combining the established asset package price system, and using the economic value calculation formula; Accumulating the economic values of all resource patches to obtain the preliminary economic value of the asset package; Combining the synergy between different natural resource data in the asset package, adjusting the preliminary economic value to obtain the final economic value of the asset package.

[0048] In this alternative embodiment, the expression of the economic value calculation formula is: ; In the formula, Z represents the economic value of the resource patch; R represents the asset price of the resource patch; S represents the land type area of the resource patch.

[0049] It should be added that a specific embodiment of an economic value estimation method based on a natural resource asset package is as follows: Step 1. Data collection and entry: Obtain physical quantity data and other relevant materials, and enter physical quantity and price signal data such as the latest remote sensing image data of the whole city, annual land use change survey data, administrative region boundary data, forest desertification results, forest grassland wetland desertification census results, construction land benchmark land price results, agricultural land grading and benchmark land price results, provincial statistical yearbooks (for the recent three years), documents, market transaction data, cost operation income materials, etc. into the system database.

[0050] Step 2. Determine the asset package scope: Draw the asset package scope based on the remote sensing image or select the asset package scope according to the administrative region. Integrate the asset package scope with physical quantity data such as annual land use change survey data according to the geographical information professional processing software environment to obtain the physical quantity data set.

[0051] Step 3. Construction of the natural resource asset package evaluation model: Establish an asset package matching model according to the physical quantity data set. The model is based on multiple dimensions such as the richness of the types of natural resources contained in the asset package, the interaction and synergy between various resources, the quality of various resources themselves, the preliminary benefit evaluation results, and the future development potential demonstrated by the overall combination of the asset package. Comprehensively use data analysis techniques and algorithm logic to construct an asset package evaluation model.

[0052] Step 4. Asset package scoring: Evaluate the asset package according to the asset package evaluation model. By deeply exploring the internal connections between resources, quantitatively analyzing the corresponding relationship between resource quality and benefits, and reasonably predicting the future growth space and value improvement potential of the asset package, a comprehensive asset package score is finally obtained.

[0053] Step 5. Establishment of the asset package price system: If the score of the asset package meets the standard for establishing the asset package, the price system can be established according to the price signal data in the database for different resource types, such as construction land, agricultural land, forests, grasslands, and wetlands. For construction land, the calculation of its economic value mainly relies on the benchmark price correction method, and the benchmark price is corrected in a timely manner according to market dynamics, policy adjustments, and special conditions. The economic value of agricultural land is calculated by combining the income capitalization method and the benchmark price correction method. Forest resource assets are divided into forest land and forest trees. The economic value calculation of forest land requires the comprehensive application of the income capitalization method, the forest land transfer price correction method, and the benchmark price correction method. The economic value calculation of forest trees adopts the forest tree transaction price correction method, the replacement cost method, and the market price reversion method. The economic value calculation of grasslands requires the comprehensive application of the income capitalization method, the grassland transfer price correction method, and the benchmark price correction method. The economic value calculation of wetlands mainly relies on the market value method and the replacement cost method.

[0054] By flexibly applying various evaluation methods and combining with the price signal data in the real-time updated database, a price system for various natural resource assets is constructed; at the same time, adjustment coefficients are determined according to location factors, socio-economic factors, and the interaction and mutual influence between assets and the overall synergistic effect of the asset package, and the overall price of the natural resource asset package is constructed by combining the price systems of each asset involved in the asset package.

[0055] Step 6. Estimate the economic value: Calculate the economic value of the patch and accumulate it to obtain the overall economic value of the asset package. The economic value of the patch = asset price × patch land type area, and the overall economic value of the asset package is obtained by accumulating the economic values of all patches within the asset package range.

[0056] The economic value calculation formula is: ; In the formula, Z represents the economic value of the resource patch; R represents the asset price of the resource patch; S represents the land type area of the resource patch.

[0057] Figure 2 An embodiment of an economic value estimation system based on a natural resource asset package of the present invention is shown.

[0058] In this alternative embodiment, the economic value estimation system based on a natural resource asset package includes: A data acquisition and processing module 201, configured to obtain natural resource data from a multi-source data platform, process the natural resource data using natural language processing technology, and enter the processed natural resource data into a database. The natural resource data includes physical quantity data and price signal data; An asset package definition module 202, configured to perform spatial analysis on the natural resource data stored in the database using geographic information technology, identify the spatial distribution patterns of different natural resource data, and define the spatial scope of the asset package; An evaluation model construction module 203, configured to integrate the spatial scope of the asset package and the physical quantity data using geographic information processing software to establish a physical quantity data set, and construct an asset package evaluation model in combination with machine learning algorithms; A price system establishment module 204, configured to evaluate the asset package using the asset package evaluation model to obtain an asset package score, and establish an asset package price system based on the natural resource type; An economic value calculation module 205, configured to obtain the economic value of the asset package according to the asset package price system and the economic value calculation formula.

[0059] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in Figure 3 The figure. The computer device includes a processor, a memory, and a network interface connected through a system bus. 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, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store static information and dynamic information data. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the steps in the above method embodiments are implemented.

[0060] Those skilled in the art can understand that Figure 3 The structure shown in is only a block diagram of a part of the structure related to the solution of the present invention, and does not constitute a limitation on the computer device to which the solution of the present invention is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0061] In addition, the present invention also provides a computer device, including a memory and a processor. A computer program is stored in the memory, and when the processor executes the computer program, the steps in the above method embodiments are implemented.

[0062] In addition, the present invention also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0063] 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, storage, database, or other medium used in the embodiments of the present invention can include at least one of non-volatile and volatile memories. The non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical memory, etc. The volatile memory can include random access memory (RAM) or external cache memory. 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.

[0064] The present invention is not limited to the structures already described and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present invention is only limited by the appended claims.

Claims

1. An economic value estimation method based on a natural resource asset package, characterized in that, The method includes: Obtaining natural resource data from a multi-source data platform, processing the natural resource data using natural language processing technology, and entering the processed natural resource data into a database, where the natural resource data includes physical quantity data and price signal data; Using geographic information technology to perform spatial analysis on the natural resource data stored in the database, identifying the spatial distribution patterns of different natural resource data, and defining the spatial scope of the asset package; Integrating the spatial scope of the asset package with the physical quantity data using geographic information processing software to establish a physical quantity dataset, and constructing an asset package evaluation model in combination with machine learning algorithms; Evaluating the asset package using the asset package evaluation model to obtain an asset package score, and establishing an asset package price system based on the natural resource type; Obtaining the economic value of the asset package according to the asset package price system and the economic value calculation formula.

2. The economic value estimation method based on the natural resource asset package according to claim 1 is characterized in that, The using geographic information technology to perform spatial analysis on the natural resource data stored in the database, identifying the spatial distribution patterns of different natural resource data, and defining the spatial scope of the asset package includes: According to the natural resource data stored in the database, using a data fusion algorithm to fuse the natural resource data from different sources; Based on the fused natural resource data, using a spatial analysis algorithm to identify the spatial distribution patterns of the natural resource data and analyze the distribution characteristics of different resources in the geographical space; Combined with the identified spatial distribution patterns, using a regional optimization algorithm to define the boundary of the natural resource data and determine the spatial scope of the asset package.

3. The economic value estimation method based on the natural resource asset package according to claim 2, characterized in that, The combined with the identified spatial distribution patterns, using a regional optimization algorithm to define the boundary of the natural resource data and determine the spatial scope of the asset package includes: According to the identified spatial distribution patterns, constructing a spatial relationship network between natural resource data, and using graph theory algorithms to analyze the spatial connectivity of natural resource data to obtain the interaction relationship between natural resource data; Based on the obtained interaction relationship, by calculating the spatial autocorrelation coefficient, evaluating the distribution trend of natural resource data in the target area, and identifying and determining the spatial characteristics of natural resource data; According to the spatial characteristics of the natural resource data, using a regional optimization algorithm to delimit the boundary of the natural resource data in the target area and determine the spatial scope of the asset package.

4. The economic value estimation method based on natural resource asset package according to claim 3, wherein The based on the obtained interaction relationship, by calculating the spatial autocorrelation coefficient, evaluating the distribution trend of natural resource data in the target area, and identifying and determining the spatial characteristics of natural resource data includes: By analyzing the interaction relationship between natural resource data, calculating the spatial autocorrelation coefficient of each natural resource data; Combined with a preset spatial interaction network model, assigning weights to the calculated spatial autocorrelation coefficients, analyzing the interaction intensity between natural resource data, and evaluating the distribution trend of natural resource data in the target area; According to the distribution trend of natural resource data and the spatial autocorrelation coefficient, using a regional optimization algorithm to identify the spatial characteristics of natural resource data in the target area.

5. The economic value estimation method based on natural resource asset packages according to claim 4, characterized in that The calculation formula of the spatial autocorrelation coefficient is: ； In the formula, T i represents the spatial autocorrelation coefficient of natural resource data at location i ; x i represents the value of natural resource data at location i ; represents the average value of natural resource data at all locations; n represents the number of all observed locations; k represents the index value; x k represents the k -th value of natural resource data at the observed location; j Represents an index value; w ij Represents a position i and the position j spatial relationship between; x j Represents the j natural resource data value at the observation position.

6. The economic value estimation method based on a natural resource asset package according to claim 1, wherein Evaluating the asset package using the asset package evaluation model to obtain an asset package score, and establishing an asset package price system based on the natural resource type includes: Inputting the determined asset package into the asset package evaluation model, analyzing the impact of the resource quality of natural resource data on the asset package benefits, and evaluating the contribution degree of different natural resource data in the asset package; Predicting the economic value of the asset package using the time series analysis algorithm according to the supply-demand relationship between the market trend and natural resources, and combining the contribution degree of natural resource data in the asset package to obtain the asset package score; Based on the natural resource type and the obtained asset package score, establishing a preliminary price system using the income reduction algorithm, and adjusting the preliminary price system in combination with the regional economic factors to construct the final asset package price system.

7. An economic value estimation method based on a natural resource asset package according to claim 6, characterized in that, The step of establishing a preliminary price system using the income reduction algorithm based on the natural resource type and the obtained asset package score, and adjusting the preliminary price system in combination with the regional economic factors to construct the final asset package price system includes: Classifying the natural resource data according to the type of natural resources to identify different types of asset packages; According to different types of asset packages and the asset package score, using the income reduction algorithm to preliminarily estimate the prices of different types of asset packages, and combining the historical natural resource data to determine the expected income and discount rate of different types of asset packages, and establishing a preliminary asset package price system; Collecting the regional economic factors of the target area, analyzing the correlation between the regional economic factors and the asset package price using the preset data regression model, and converting the regional economic factors into regional weighted adjustment factors using the weighted average algorithm; Adjusting the preliminary asset package price system using the regional weighted adjustment factors, and combining the market demand and resource supply situation to construct the final asset package price system.

8. The economic value estimation method based on natural resource asset packages according to claim 1, characterized in that The step of obtaining the economic value of the asset package according to the asset package price system and the economic value calculation formula includes: According to the various resource patches and their corresponding attributes in the asset package, combining the established asset package price system, and calculating the economic value of each resource patch using the economic value calculation formula; Accumulating the economic values of all resource patches to obtain the preliminary economic value of the asset package; Combining the synergy effect between different natural resource data in the asset package to adjust the preliminary economic value to obtain the final economic value of the asset package.

9. The economic value estimation method based on a natural resource asset package according to claim 8, characterized in that The expression of the economic value calculation formula is: ； In the formula, Z represents the economic value of the resource patch; R represents the asset price of the resource patch; S represents the land type area of the resource patch.

10. An economic value estimation system based on a natural resource asset package, characterized in that, The system includes: A data acquisition and processing module, which is used to obtain natural resource data from a multi-source data platform, process the natural resource data using natural language processing technology, and input the processed natural resource data into the database. The natural resource data includes physical quantity data and price signal data; An asset package definition module, which is used to perform spatial analysis on the natural resource data stored in the database using geographic information technology, identify the spatial distribution patterns of different natural resource data, and define the spatial scope of the asset package; An evaluation model construction module, which is used to integrate the spatial scope of the asset package and the physical quantity data using geographic information processing software to establish a physical quantity data set, and construct an asset package evaluation model in combination with machine learning algorithms; A price system establishment module, which is used to evaluate the asset package by using the asset package evaluation model to obtain the asset package score, and establish an asset package price system based on the natural resource type; An economic value calculation module, which is used to obtain the economic value of the asset package according to the asset package price system and the economic value calculation formula.

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