Method and system for strategic key mineral resource comprehensive evaluation and decision support service

Abstract

The invention provides a strategic key mineral resource comprehensive evaluation and decision support service method and system, and the method comprises the steps: S1, carrying out the data collection and preprocessing, and constructing a digital twinborn model; s2, carrying out whole industrial chain material flow analysis; s3, estimating the waste quantity and the recovery quantity of resource products, and calculating the stock quantity; and S4, performing comprehensive evaluation and early warning according to the calculated content, and visually displaying the data. According to the invention, digital modeling and simulation of the whole process of strategic key mineral resources from exploration and exploitation to recycling are realized, a data barrier of the whole industry chain is broken through, and a system solution of the whole life cycle is provided.

Description

Technical Field

[0001] The present invention relates to the field of resource minerals, and in particular to a method and system for comprehensive evaluation and decision support services of strategic key mineral resources. Background Art

[0002] Representative products of geological modeling and resource estimation software include Leapfrog, Datamine, Surpac, etc. This type of software can help mining companies conduct data analysis and decision support in key links such as geological modeling, mineral resource estimation, and mine design.

[0003] Representative products of mine production management systems include MineSight, XPAC, Minemax, etc. Such systems can help mining companies realize the information management of production operations such as mine production scheduling, equipment management, and logistics transportation.

[0004] Representative products of mineral resource assessment software include OMC, Whittle, NPV Scheduler, etc. This type of software can help mining companies conduct economic assessment of mineral resources, investment decision analysis, etc.

[0005] Most of these products focus on single links such as geological modeling, production management or economic evaluation, and it is difficult to provide comprehensive mineral resource decision-making support. There is a lack of comprehensive consideration and analysis of multiple factors such as geology, market, technology, and environment. The integration between these products is low, and it is difficult to achieve seamless connection and information sharing. The integration with the enterprise management information system is also relatively weak, making it difficult to support enterprise-level decision-making. These products are insufficient in the analysis and quantification of uncertain factors such as geology and market. There is a lack of dynamic monitoring of risk factors. These products focus more on professional analysis and have weak ability to support corporate strategic decision-making. There is a lack of advanced functions such as visualization of the decision-making process and scenario simulation. Summary of the invention

[0006] In view of the defects in the prior art, the purpose of the present invention is to provide a method and system for comprehensive evaluation and decision support services of strategic key mineral resources.

[0007] A strategic key mineral resource comprehensive assessment and decision support service method provided by the present invention includes:

[0008] Step S1: perform data collection and preprocessing to build a digital twin model;

[0009] Step S2: Conduct material flow analysis of the entire industry chain;

[0010] Step S3: Estimate the waste and recycling amount of resource products and calculate the inventory;

[0011] Step S4: Perform comprehensive evaluation and early warning based on the calculated content, and visualize the data.

[0012] Preferably, in step S1:

[0013] Data collection and preprocessing:

[0014] Users upload Excel files containing resource data to the corresponding subsystem through the backend management system;

[0015] The system verifies the Excel file format, stores it on the server if it passes, and parses the data and stores it in the MySQL database;

[0016] Extract relevant data from the database, including mining volume, trade volume, and consumption volume, and perform data cleaning, conversion, and fusion processing to form a consistent data set.

[0017] Digital twin model construction:

[0018] Based on the fused data, a digital twin model of resources is constructed using data-driven modeling methods;

[0019] Using knowledge graph technology, we build resource ontology models and semantic association networks to describe the attributes and relationships of resources.

[0020] Preferably, in step S2:

[0021] Use top-down and bottom-up material flow analysis methods to analyze the entire industrial chain of resources;

[0022] For resource flows in products, a bottom-up approach is used to calculate the resource content in each product by multiplying the resource content of the product by the output;

[0023] At each life cycle stage, the import flow, export flow, inflow, outflow, recovery, loss and inventory change of resources are calculated based on the mass balance equation.

[0024] Preferably, in step S3:

[0025] Estimated waste and recycling volumes:

[0026] The waste and recovery of resource products are estimated using Weibull distribution;

[0027] Calculate resource consumption, waste and recycling based on the average lifespan, cumulative distribution function and density function parameters of the product;

[0028] Inventory calculation:

[0029] Calculate the inventory of resources at each life cycle stage, considering initial inventory, inflow, outflow and product usage probability factors.

[0030] Preferably, in step S4:

[0031] Comprehensive assessment and early warning:

[0032] Use multi-criteria decision-making and life cycle assessment methods to conduct a comprehensive assessment of strategic mineral resources and form a resource security situation analysis report;

[0033] Provide early warning of resource supply security based on supply and demand trend analysis and forecasting models;

[0034] Data visualization display:

[0035] Present resource analysis results through data visualization techniques;

[0036] When users enter the comprehensive data dashboard page, the system displays charts and data on spatiotemporal evolution, comprehensive evaluation, and dynamic monitoring, including Sankey diagrams of resources, bar charts of final products, reserve distribution maps, and trade flow maps.

[0037] Decision support services:

[0038] Provide users with strategic mineral resource decision support services based on comprehensive assessment results and early warning information;

[0039] It provides decision support functions such as resource supply risk assessment, alternative resource recommendation, supply chain optimization, and policy simulation, allowing users to formulate resource security strategies.

[0040] A strategic key mineral resource comprehensive assessment and decision support service system provided by the present invention comprises:

[0041] Module M1: perform data collection and preprocessing to build a digital twin model;

[0042] Module M2: Conduct material flow analysis of the entire industry chain;

[0043] Module M3: Estimate the waste and recycling volume of resource products and calculate the inventory volume;

[0044] Module M4: Conduct comprehensive assessment and early warning based on the calculated content, and visualize the data.

[0045] Preferably, in the module M1:

[0046] Data collection and preprocessing:

[0047] Users upload Excel files containing resource data to the corresponding subsystem through the backend management system;

[0048] The system verifies the Excel file format, stores it on the server if it passes, and parses the data and stores it in the MySQL database;

[0049] Extract relevant data from the database, including mining volume, trade volume, and consumption volume, and perform data cleaning, conversion, and fusion processing to form a consistent data set.

[0050] Digital twin model construction:

[0051] Based on the fused data, a digital twin model of resources is constructed using data-driven modeling methods;

[0052] Using knowledge graph technology, we build resource ontology models and semantic association networks to describe the attributes and relationships of resources.

[0053] Preferably, in the module M2:

[0054] Use top-down and bottom-up material flow analysis methods to analyze the entire industrial chain of resources;

[0055] For resource flows in products, a bottom-up approach is used to calculate the resource content in each product by multiplying the resource content of the product by the output;

[0056] At each life cycle stage, the import flow, export flow, inflow, outflow, recovery, loss and inventory change of resources are calculated based on the mass balance equation.

[0057] Preferably, in the module M3:

[0058] Estimated waste and recycling volumes:

[0059] The waste and recovery of resource products are estimated using Weibull distribution;

[0060] Calculate resource consumption, waste and recycling based on the average lifespan, cumulative distribution function and density function parameters of the product;

[0061] Inventory calculation:

[0062] Calculate the inventory of resources at each life cycle stage, considering initial inventory, inflow, outflow and product usage probability factors.

[0063] Preferably, in the module M4:

[0064] Comprehensive assessment and early warning:

[0065] Use multi-criteria decision-making and life cycle assessment methods to conduct a comprehensive assessment of strategic mineral resources and form a resource security situation analysis report;

[0066] Provide early warning of resource supply security based on supply and demand trend analysis and forecasting models;

[0067] Data visualization display:

[0068] Present resource analysis results through data visualization techniques;

[0069] When users enter the comprehensive data dashboard page, the system displays charts and data on spatiotemporal evolution, comprehensive evaluation, and dynamic monitoring, including Sankey diagrams of resources, bar charts of final products, reserve distribution maps, and trade flow maps.

[0070] Decision support services:

[0071] Provide users with strategic mineral resource decision support services based on comprehensive assessment results and early warning information;

[0072] It provides decision support functions such as resource supply risk assessment, alternative resource recommendation, supply chain optimization, and policy simulation, allowing users to formulate resource security strategies.

[0073] Compared with the prior art, the present invention has the following beneficial effects:

[0074] 1. The present invention realizes the digital modeling and simulation of the whole process of strategic key mineral resources from exploration and mining to recycling and utilization, breaks through the data barriers of the whole industry chain, and provides a system solution for the whole life cycle. Compared with the existing decentralized management model, this system can monitor and optimize strategic key mineral resources more comprehensively and dynamically, and improve the level of refined and intelligent management.

[0075] 2. The present invention adopts a data-driven modeling method, integrating multi-source heterogeneous data from geological exploration, mining and smelting, trade circulation, consumption and use, etc., to improve the accuracy and applicability of the model. Using knowledge graph technology, a semantically associated strategic key mineral resource knowledge base is constructed to enhance the relevance and interpretability of the data. Compared with the traditional static, single data source analysis method, the present invention can more comprehensively and dynamically characterize the spatiotemporal distribution characteristics and evolution laws of strategic key mineral resources.

[0076] 3. The present invention innovatively applies the material flow analysis method combining top-down and bottom-up to the management of strategic key mineral resources. By quantitatively analyzing the material flow input, output, inventory, and loss of resources at each stage of their life cycle, the metabolic process and driving factors of resources are revealed, providing a decision-making basis for optimal resource allocation. Compared with the existing static material flow analysis, the present invention takes into account the impact of dynamic factors such as technological progress and policy changes, and the analysis results are more targeted.

[0077] 4. The present invention uses Weibull distribution to estimate the waste and recycling of resource products, which is more in line with the characteristics of the product life cycle than the traditional static estimation method, and the estimation results are more reliable. By calculating the inventory changes of strategic key mineral resources at various stages, the resource utilization efficiency and loss and waste are revealed, providing a handle for improving the level of resource recycling.

[0078] 5. The present invention uses multi-criteria decision-making, life cycle assessment and other methods to conduct a comprehensive assessment of strategic key mineral resources from multiple perspectives such as resource endowment, development and utilization, ecological environment, economic benefits, and supply security, and forms a security situation analysis report. Based on supply and demand trend analysis and prediction models, early warning of resource security is carried out. Compared with a single evaluation indicator, the evaluation results of the present invention are more comprehensive, balanced, and more instructive.

[0079] 6. The present invention has developed a visual comprehensive data dashboard of strategic key mineral resources, which intuitively presents key data charts of the entire life cycle of resources and provides users with a convenient and friendly human-computer interaction interface. Compared with traditional report presentation, the present invention uses data visualization technology to greatly improve the efficiency of information transmission and user experience, assisting decision makers to intuitively understand resource status and optimize resource allocation. BRIEF DESCRIPTION OF THE DRAWINGS

[0080] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0081] Figure 1 Display a flow chart for a static Sange diagram;

[0082] Figure 2 Upload Excel operation flow chart to the system;

[0083] Figure 3 It is the operation flow chart of the space-time evolution system;

[0084] Figure 4 It is the operation flow chart of the comprehensive resource assessment system;

[0085] Figure 5 It is the operation flow chart of the material dynamic evolution system;

[0086] Figure 6 This is the 1+1+N system structure diagram. DETAILED DESCRIPTION

[0087] The present invention is described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those of ordinary skill in the art, several changes and improvements can also be made without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0088] Embodiment 1:

[0089] According to a strategic key mineral resource comprehensive assessment and decision support service method provided by the present invention, Figure 1-Figure 6 As shown, including:

[0090] Step S1: perform data collection and preprocessing to build a digital twin model;

[0091] Specifically, in step S1:

[0092] Data collection and preprocessing:

[0093] Users upload Excel files containing resource data to the corresponding subsystem through the backend management system;

[0094] The system verifies the Excel file format, stores it on the server if it passes, and parses the data and stores it in the MySQL database;

[0095] Extract relevant data from the database, including mining volume, trade volume, and consumption volume, and perform data cleaning, conversion, and fusion processing to form a consistent data set.

[0096] Digital twin model construction:

[0097] Based on the fused data, a digital twin model of resources is constructed using data-driven modeling methods;

[0098] Using knowledge graph technology, we build resource ontology models and semantic association networks to describe the attributes and relationships of resources.

[0099] Step S2: Conduct material flow analysis of the entire industry chain;

[0100] Specifically, in step S2:

[0101] Use top-down and bottom-up material flow analysis methods to analyze the entire industrial chain of resources;

[0102] For resource flows in products, a bottom-up approach is used to calculate the resource content in each product by multiplying the resource content of the product by the output;

[0103] At each life cycle stage, the import flow, export flow, inflow, outflow, recovery, loss and inventory change of resources are calculated based on the mass balance equation.

[0104] Step S3: Estimate the waste and recycling amount of resource products and calculate the inventory;

[0105] Specifically, in step S3:

[0106] Estimated waste and recycling volumes:

[0107] The waste and recovery of resource products are estimated using Weibull distribution;

[0108] Calculate resource consumption, waste and recycling based on the average lifespan, cumulative distribution function and density function parameters of the product;

[0109] Inventory calculation:

[0110] Calculate the inventory of resources at each life cycle stage, considering initial inventory, inflow, outflow and product usage probability factors.

[0111] Step S4: Perform comprehensive evaluation and early warning based on the calculated content, and visualize the data.

[0112] Specifically, in step S4:

[0113] Comprehensive assessment and early warning:

[0114] Use multi-criteria decision-making and life cycle assessment methods to conduct a comprehensive assessment of strategic mineral resources and form a resource security situation analysis report;

[0115] Provide early warning of resource supply security based on supply and demand trend analysis and forecasting models;

[0116] Data visualization display:

[0117] Present resource analysis results through data visualization techniques;

[0118] When users enter the comprehensive data dashboard page, the system displays charts and data on spatiotemporal evolution, comprehensive evaluation, and dynamic monitoring, including Sankey diagrams of resources, bar charts of final products, reserve distribution maps, and trade flow maps.

[0119] Decision support services:

[0120] Provide users with strategic mineral resource decision support services based on comprehensive assessment results and early warning information;

[0121] It provides decision support functions such as resource supply risk assessment, alternative resource recommendation, supply chain optimization, and policy simulation, allowing users to formulate resource security strategies.

[0122] Embodiment 2:

[0123] Embodiment 2 is a preferred example of Embodiment 1, and is used to illustrate the present invention in more detail.

[0124] The present invention also provides a strategic key mineral resources comprehensive assessment and decision support service system, which can be implemented by executing the process steps of the strategic key mineral resources comprehensive assessment and decision support service method, that is, technical personnel in this field can understand the strategic key mineral resources comprehensive assessment and decision support service method as the preferred implementation mode of the strategic key mineral resources comprehensive assessment and decision support service system.

[0125] A strategic key mineral resource comprehensive assessment and decision support service system provided by the present invention comprises:

[0126] Module M1: perform data collection and preprocessing to build a digital twin model;

[0127] Specifically, in the module M1:

[0128] Data collection and preprocessing:

[0129] Users upload Excel files containing resource data to the corresponding subsystem through the backend management system;

[0130] The system verifies the Excel file format, stores it on the server if it passes, and parses the data and stores it in the MySQL database;

[0131] Extract relevant data from the database, including mining volume, trade volume, and consumption volume, and perform data cleaning, conversion, and fusion processing to form a consistent data set.

[0132] Digital twin model construction:

[0133] Based on the fused data, a digital twin model of resources is constructed using data-driven modeling methods;

[0134] Using knowledge graph technology, we build resource ontology models and semantic association networks to describe the attributes and relationships of resources.

[0135] Module M2: Conduct material flow analysis of the entire industry chain;

[0136] Specifically, in the module M2:

[0137] Use top-down and bottom-up material flow analysis methods to analyze the entire industrial chain of resources;

[0138] For resource flows in products, a bottom-up approach is used to calculate the resource content in each product by multiplying the resource content of the product by the output;

[0139] At each life cycle stage, the import flow, export flow, inflow, outflow, recovery, loss and inventory change of resources are calculated based on the mass balance equation.

[0140] Module M3: Estimate the waste and recycling volume of resource products and calculate the inventory volume;

[0141] Specifically, in the module M3:

[0142] Estimated waste and recycling volumes:

[0143] The waste and recovery of resource products are estimated using Weibull distribution;

[0144] Calculate resource consumption, waste and recycling based on the average lifespan, cumulative distribution function and density function parameters of the product;

[0145] Inventory calculation:

[0146] Calculate the inventory of resources at each life cycle stage, considering initial inventory, inflow, outflow and product usage probability factors.

[0147] Module M4: Conduct comprehensive assessment and early warning based on the calculated content, and visualize the data.

[0148] Specifically, in the module M4:

[0149] Comprehensive assessment and early warning:

[0150] Use multi-criteria decision-making and life cycle assessment methods to conduct a comprehensive assessment of strategic mineral resources and form a resource security situation analysis report;

[0151] Provide early warning of resource supply security based on supply and demand trend analysis and forecasting models;

[0152] Data visualization display:

[0153] Present resource analysis results through data visualization techniques;

[0154] When users enter the comprehensive data dashboard page, the system displays charts and data on spatiotemporal evolution, comprehensive evaluation, and dynamic monitoring, including Sankey diagrams of resources, bar charts of final products, reserve distribution maps, and trade flow maps.

[0155] Decision support services:

[0156] Provide users with strategic mineral resource decision support services based on comprehensive assessment results and early warning information;

[0157] It provides decision support functions such as resource supply risk assessment, alternative resource recommendation, supply chain optimization, and policy simulation, allowing users to formulate resource security strategies.

[0158] Embodiment 3:

[0159] Embodiment 3 is a preferred example of Embodiment 1, and is used to illustrate the present invention in more detail.

[0160] Strategic key mineral resources are the material basis for the country's economic and social development, and are of great significance to ensuring national resource security, industrial security and national defense security. In order to strengthen the scientific management and efficient utilization of strategic key mineral resources, this project intends to build a comprehensive assessment and decision support service system for strategic key mineral resources. The system will comprehensively use advanced technologies such as digital twins, cloud computing, and big data to achieve perception, modeling, simulation, prediction, and comprehensive assessment and decision support for the entire life cycle of strategic key mineral resources, and help sustainable management and efficient utilization of resources.

[0161] This system adopts the overall architecture of "1+1+N", namely, 1 strategic key mineral resource big data center, 1 data visualization management and service platform, and N application service subsystems. The system is divided into four layers: collection layer, data layer, application layer and display layer.

[0162] 1. Collection layer: Through web crawlers, data APIs and other means, collect public data on the mining, processing, circulation and other aspects of strategic key mineral resources. At the same time, integrate existing historical data such as geological exploration and reserve assessment.

[0163] 2. Data layer: It adopts a distributed cloud storage architecture and supports multiple data types such as structured, semi-structured and unstructured. It uses big data technology to clean, integrate, manage and analyze the massive heterogeneous data collected.

[0164] 3. Application layer: Based on the data layer, construct a digital twin model of strategic key mineral resources, including resource distribution model, supply and demand relationship model, industrial chain network model, etc. R&D resource comprehensive evaluation, dynamic monitoring of material flow in the entire industrial chain, demand forecasting, safety warning and other intelligent application services.

[0165] 4. Display layer: Using visualization technologies such as SVG, charts, and data screens, it provides users with intuitive multi-dimensional data visual analysis functions. It displays information such as the spatial distribution of strategic key mineral resources and the overall supply chain.

[0166] The key technologies of the present invention include:

[0167] 1. Multi-source heterogeneous data fusion: Use technologies such as ontology mapping and data extraction to achieve semantic association and fusion of structured and unstructured data and build a strategic key mineral resources knowledge base.

[0168] 2. Data-based digital twin modeling: Based on public data resources, big data mining technology is used to build resource distribution models, supply and demand relationship models, industrial chain network models, etc., to achieve data-based mapping of the entire life cycle of strategic key mineral resources.

[0169] 3. Cloud computing architecture: Adopt cloud computing architecture to support distributed storage, computing and services of massive data.

[0170] 4. Big data analysis: Use data mining, machine learning and other technologies to analyze and predict strategic key mineral resources in multiple dimensions and time and space sequences, revealing resource consumption trends, supply and demand relationships and potential risks.

[0171] 5. Visualization: In the form of a large data screen, using visualization technologies such as SVG and charts, the spatial distribution of strategic key mineral resources and the overall supply chain are intuitively displayed.

[0172] The innovation of the present invention is:

[0173] 1. Public data-driven digital twin: Different from the traditional real-time sensor data-driven system, this system is based on public data resources and uses big data mining technology to build a digital twin model of strategic key mineral resources. It overcomes the problems of insufficient sensor deployment and difficulty in data acquisition, and is an innovative way to implement digital twins.

[0174] 2. The material flow of the whole industry chain is connected: the industry chain of strategic key mineral resources mining, processing, circulation, consumption, recycling, etc. is connected, and the whole process of material flow is visualized and supervised. This makes up for the deficiency of existing products that only focus on a single link.

[0175] 3. Resource security early warning: Based on the supply and demand trend analysis, early warning of the supply security of strategic key mineral resources is provided to provide decision-making support for national macroeconomic regulation. Existing products lack early warning functions.

[0176] 4. Strategic resource management: Focus on strategic key mineral resources and provide digital solutions for their sustainable management and utilization. Existing digital twin products are mainly aimed at industrial equipment and have not yet entered the field of strategic resources.

[0177] The expected results of the present invention are:

[0178] 1. Form theories, methods and key technologies for the digital twin of strategic key mineral resources throughout their life cycle.

[0179] 2. Develop a decision-making support system for displaying the material metabolism evolution and comprehensive evaluation of the entire life cycle of strategic key mineral resources.

[0180] 3. Provide digital management and decision-making support for the strategic planning, development and utilization, and industrial development of my country's strategic key mineral resources.

[0181] The present invention solves the following technical problems:

[0182] Lack of comprehensiveness: Most existing products focus on a single link and lack comprehensive evaluation and decision support for the entire life cycle of mineral resources. This invention achieves comprehensive analysis and evaluation of the entire process of mineral resources from mining to recycling by constructing a digital twin of the metabolic evolution of material flows in the entire life cycle of strategic mineral resources.

[0183] Low system integration: The existing products have low integration, making it difficult to achieve information sharing and enterprise-level decision support. This invention adopts the "1+1+N" model to effectively integrate the big data center, data visualization management and service platform, and multiple application services, thereby improving the integrity and synergy of the system.

[0184] Limited uncertainty analysis capabilities: Existing products are insufficient in analyzing and quantifying uncertainties such as geology and the market. This invention uses digital twin technology to connect the physical space of industrial factories with the digital space through modeling, discover deep-level relationships, and improve the analysis and early warning capabilities of uncertainties.

[0185] Weak decision support function: Existing products focus on professional analysis and have weak support for enterprise strategic decision-making. This invention greatly enhances the system's support capabilities in strategic decision-making by building a comprehensive resource evaluation system and providing functions such as multi-scenario prediction and visualization display.

[0186] Insufficient data collection and processing capabilities: The present invention adopts an efficient and highly compatible system data collection and sensor collection solution, integrating technologies such as the Internet of Things and big data, improving the system's capabilities in data collection, storage and processing, and providing a data foundation for the realization of comprehensive digitized digital twins.

[0187] The implementation method of the strategic key mineral resources comprehensive evaluation and decision support service system of the present invention is as follows Figure 1 , Figure 2 , Figure 3 , Figure 4 As shown below, Figure 1 , Figure 2 , Figure 3 and Figure 4 For detailed explanation:

[0188] like Figure 2As shown, the specific operation process of uploading Excel in the background management system is described in detail as follows:

[0189] Taking phosphorus as an example, the steps of solving the problem using the technical solution of this application are as follows:

[0190] 1. Data collection and preprocessing:

[0191] The user uses the phosphorus element account to log in to the backend management system and uploads the Excel file containing phosphorus element data to the strategic mineral resources spatiotemporal evolution system, comprehensive resource evaluation system and material dynamic monitoring system.

[0192] The system verifies the Excel format, stores it on the server after verification, and parses the data and stores it in the MySQL database.

[0193] Extract phosphorus-related data from the database, including mining volume, trade volume, consumption, inventory, recycling volume, etc., and perform data cleaning, conversion and fusion processing to improve data quality and form a consistent phosphorus data set.

[0194] 2. Digital twin model construction:

[0195] Based on the fused phosphorus data, a data-driven modeling method is used to construct a digital twin model of phosphorus.

[0196] Using knowledge graph technology, a phosphorus ontology model and semantic association network are established to describe the properties and relationships of phosphorus.

[0197] 3. Material flow analysis of the entire industry chain:

[0198] Conduct material flow analysis on the entire phosphorus industry chain, using top-down and bottom-up material flow analysis methods.

[0199] For phosphorus flows in phosphorus-containing products, a bottom-up approach was used to calculate the phosphorus content of each product by multiplying the phosphorus content of the product by the production volume of that product.

[0200] In each life cycle stage, the import flow, export flow, inflow, outflow, recovery, loss and inventory change of phosphorus are calculated based on the mass balance equation.

[0201] 4. Estimation of waste and recycling volume:

[0202] The Weibull distribution was used to estimate the waste and recovery of phosphorus-containing products.

[0203] The consumption, waste and recycling of phosphorus are calculated based on the average life of the product, cumulative distribution function, density function and other parameters.

[0204] 5. Inventory calculation:

[0205] Calculate the inventory of phosphorus at each life cycle stage, considering factors such as initial inventory, inflow, outflow and product use probability.

[0206] 6. Comprehensive assessment and early warning:

[0207] Use multi-criteria decision-making, life cycle assessment and other methods to conduct a comprehensive assessment of phosphorus resources and form a phosphorus resource security situation analysis report.

[0208] Based on supply and demand trend analysis and forecasting models, early warning of phosphorus resource supply security is provided.

[0209] 7. Data visualization:

[0210] The results of phosphorus analysis are intuitively displayed through data visualization technology.

[0211] When users enter the comprehensive phosphorus resource data dashboard page, the system displays the main charts and data on the spatiotemporal evolution of strategic mineral resources, comprehensive resource assessment and dynamic material monitoring, including the Sankey diagram of the phosphorus element, the final product bar chart, the China reserve distribution map, the world reserve distribution map and the world trade flow map.

[0212] 8.Decision support services:

[0213] Based on the comprehensive assessment results and early warning information of phosphorus resources, provide users with decision-making support services for phosphorus resources.

[0214] It provides decision support functions such as phosphorus resource supply risk assessment, alternative resource recommendation, supply chain optimization, policy simulation, etc., to help users formulate phosphorus resource security strategies.

[0215] Those skilled in the art know that, in addition to realizing the system and its various devices, modules, and units provided by the present invention in a purely computer-readable program code, it is entirely possible to realize the same functions in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, the system and its various devices, modules, and units provided by the present invention can be considered as a hardware component, and the devices, modules, and units included therein for realizing various functions can also be regarded as structures within the hardware component; the devices, modules, and units for realizing various functions can also be regarded as both software modules for realizing the method and structures within the hardware component.

[0216] The above describes the specific embodiments of the present invention. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which does not affect the essence of the present invention. In the absence of conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims

1. A comprehensive evaluation and decision support service method for strategic key mineral resources, characterized in that: include: Step S1: perform data collection and preprocessing to build a digital twin model; Step S2: Conduct material flow analysis of the entire industry chain; Step S3: Estimate the waste and recycling amount of resource products and calculate the inventory; Step S4: Perform comprehensive evaluation and early warning based on the calculated content, and visualize the data.

2. The strategic key mineral resources comprehensive assessment and decision support service method according to claim 1 is characterized in that: In step S1: Data collection and preprocessing: Users upload Excel files containing resource data to the corresponding subsystem through the backend management system; The system verifies the Excel file format, stores it on the server if it passes, and parses the data and stores it in the MySQL database; Extract relevant data from the database, including mining volume, trade volume, and consumption volume, and perform data cleaning, conversion, and fusion processing to form a consistent data set. Digital twin model construction: Based on the fused data, a digital twin model of resources is constructed using data-driven modeling methods; Using knowledge graph technology, we build resource ontology models and semantic association networks to describe the attributes and relationships of resources.

3. The strategic key mineral resources comprehensive assessment and decision support service method according to claim 1, characterized in that: In step S2: Use top-down and bottom-up material flow analysis methods to analyze the entire industrial chain of resources; For resource flows in products, a bottom-up approach is used to calculate the resource content in each product by multiplying the resource content of the product by the output; At each life cycle stage, the import flow, export flow, inflow, outflow, recovery, loss and inventory change of resources are calculated based on the mass balance equation.

4. The strategic key mineral resources comprehensive assessment and decision support service method according to claim 1, characterized in that: In step S3: Estimated waste and recycling volumes: The waste and recovery of resource products are estimated using Weibull distribution; Calculate resource consumption, waste and recycling based on the average lifespan, cumulative distribution function and density function parameters of the product; Inventory calculation: Calculate the inventory of resources at each life cycle stage, considering initial inventory, inflow, outflow and product usage probability factors.

5. The strategic key mineral resources comprehensive assessment and decision support service method according to claim 1, characterized in that: In step S4: Comprehensive assessment and early warning: Use multi-criteria decision-making and life cycle assessment methods to conduct a comprehensive assessment of strategic mineral resources and form a resource security situation analysis report; Provide early warning of resource supply security based on supply and demand trend analysis and forecasting models; Data visualization display: Present resource analysis results through data visualization techniques; When users enter the comprehensive data dashboard page, the system displays charts and data on spatiotemporal evolution, comprehensive evaluation, and dynamic monitoring, including Sankey diagrams of resources, bar charts of final products, reserve distribution maps, and trade flow maps. Decision support services: Provide users with strategic mineral resource decision support services based on comprehensive assessment results and early warning information; It provides decision support functions such as resource supply risk assessment, alternative resource recommendation, supply chain optimization, and policy simulation, allowing users to formulate resource security strategies.

6. A strategic key mineral resource comprehensive assessment and decision support service system, characterized in that: include: Module M1: perform data collection and preprocessing to build a digital twin model; Module M2: Conduct material flow analysis of the entire industry chain; Module M3: Estimate the waste and recycling volume of resource products and calculate the inventory volume; Module M4: Conduct comprehensive assessment and early warning based on the calculated content, and visualize the data.

7. The strategic key mineral resources comprehensive assessment and decision support service system according to claim 6 is characterized in that: In the module M1: Data collection and preprocessing: Users upload Excel files containing resource data to the corresponding subsystem through the backend management system; The system verifies the Excel file format, stores it on the server if it passes, and parses the data and stores it in the MySQL database; Extract relevant data from the database, including mining volume, trade volume, and consumption volume, and perform data cleaning, conversion, and fusion processing to form a consistent data set. Digital twin model construction: Based on the fused data, a digital twin model of resources is constructed using data-driven modeling methods; Using knowledge graph technology, we build resource ontology models and semantic association networks to describe the attributes and relationships of resources.

8. The strategic key mineral resources comprehensive assessment and decision support service system according to claim 6 is characterized in that: In the module M2: Use top-down and bottom-up material flow analysis methods to analyze the entire industrial chain of resources; For resource flows in products, a bottom-up approach is used to calculate the resource content in each product by multiplying the resource content of the product by the output; At each life cycle stage, the import flow, export flow, inflow, outflow, recovery, loss and inventory change of resources are calculated based on the mass balance equation.

9. The strategic key mineral resources comprehensive assessment and decision support service system according to claim 6 is characterized in that: In the module M3: Estimated waste and recycling volumes: The waste and recovery of resource products are estimated using Weibull distribution; Calculate resource consumption, waste and recycling based on the average lifespan, cumulative distribution function and density function parameters of the product; Inventory calculation: Calculate the inventory of resources at each life cycle stage, considering initial inventory, inflow, outflow and product usage probability factors.

10. The strategic key mineral resources comprehensive assessment and decision support service system according to claim 6, characterized in that: In the module M4: Comprehensive assessment and early warning: Use multi-criteria decision-making and life cycle assessment methods to conduct a comprehensive assessment of strategic mineral resources and form a resource security situation analysis report; Provide early warning of resource supply security based on supply and demand trend analysis and forecasting models; Data visualization display: Present resource analysis results through data visualization techniques; When users enter the comprehensive data dashboard page, the system displays charts and data on spatiotemporal evolution, comprehensive evaluation, and dynamic monitoring, including Sankey diagrams of resources, bar charts of final products, reserve distribution maps, and trade flow maps. Decision support services: Provide users with strategic mineral resource decision support services based on comprehensive assessment results and early warning information; It provides decision support functions such as resource supply risk assessment, alternative resource recommendation, supply chain optimization, and policy simulation, allowing users to formulate resource security strategies.

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