Resource flow and multi-dimensional visualization analysis method and system for steel industry

Abstract

The present application relates to a kind of resource flow and multi-dimensional visualization analysis method and system for steel industry, comprising: platform transaction, offline visit and so on multi-source data are collected and classified with credibility;Based on GIS map, with different icons mark steel plant attribute, and with solid line, dashed line and other different line type draw resource flow link, realize the fusion display of data credibility and space flow direction;In response to user operation, realize the dynamic drilling and backtracking of national-province-city three-level view, and synchronously aggregate or split corresponding level data;Receive the combination filtering condition of time, steel plant, product, region, quickly retrieve and update map view using multi-dimensional index structure;Through global state manager drive map and information display panel no refresh linkage.The present application realizes the fine analysis of steel resource flow from macro to micro, significantly improves the intuitiveness and efficiency of market decision.

Description

Technical Field

[0001] This invention relates to the field of data analysis and visualization technology, and in particular to resource flow analysis in the steel industry, geographic information system (GIS) visualization, and multidimensional data analysis technology. Specifically, it relates to a method, system, and storage medium for multidimensional visualization analysis of resource flow in the steel industry. Background Technology

[0002] As a pillar industry of the national economy, the management of resource flows and market analysis in the steel industry are crucial for optimizing industrial layout and formulating marketing strategies. Currently, steel companies generally rely on traditional reporting and general data visualization tools for resource flow analysis, which is insufficient to meet the needs of refined operations and efficient decision-making.

[0003] Chinese patent application CN 112328723 A discloses a GIS-based digital steel plant visualization analysis system. The system includes a data storage backend, an algorithm service platform, and a business application frontend, which can collect, organize, and visualize spatial data of the steel plant. However, this solution still has the following shortcomings: First, the integration depth of resource flow and geographic information is insufficient, failing to intuitively present the spatial relationship between steel mill distribution, sales areas, and logistics links, making it difficult for decision-makers to quickly grasp market layout; Second, the mixed display of multi-source data lacks differentiated labeling for data from different sources, making it difficult for decision-makers to quickly identify data reliability and increasing the risk of misjudgment; Third, the visualization dimension is singular, providing only a single level of data display, unable to achieve dynamic switching and drill-down analysis of multi-level views, and the macro layout and micro details cannot be analyzed continuously; Fourth, the data filtering function is weak, not supporting multi-condition combined queries such as time, steel mill, product, and region, resulting in long retrieval response times when facing massive amounts of data, seriously affecting analysis efficiency; Fifth, poor industry adaptability, lacking customized functions for the steel industry, such as steel mill classification, sub-category library, and site visit data integration, resulting in the inability to meet core business needs.

[0004] In summary, existing technologies cannot adequately meet the actual needs of the steel industry for refined analysis and efficient decision-making regarding resource flows. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the existing technology and provide a method and system for resource flow and multi-dimensional visualization analysis in the steel industry, which has solved or partially solved the shortcomings of the existing technology such as mixed data, lack of spatial correlation, single analysis granularity and low screening efficiency.

[0006] The objective of this invention can be achieved through the following technical solutions: One aspect of the present invention provides a method for resource flow and multi-dimensional visualization analysis in the steel industry, comprising the following steps: Acquire multi-source data from the steel business and preprocess it. Classify the preprocessed data according to the credibility of the data source to obtain standardized data including credibility category identifiers. On the GIS map, based on the location information of the steel plant, the steel plant is marked with an icon corresponding to its attributes. Based on the credibility category identifier, a differentiated line type is used to draw the resource flow link from the steel plant to the sales area, generating a resource flow visualization map. In response to the user's selection of a geographic region, dynamic drill-down and backtracking between geographic region levels are realized, and data aggregation or splitting of the corresponding level is performed synchronously when switching levels. The system receives user-defined combined filtering conditions, which include at least two of the following: time, steel mill, product, and region. It uses a multidimensional index structure to retrieve data that meets the conditions and dynamically updates the resource flow visualization map based on the retrieval results. An information display panel is set up in the associated display area of ​​the map view. In response to the detection of a hierarchical switch or a change in the filtering conditions of the map view, the business indicator data in the information display panel is requested and refreshed to realize the linkage display of the map view and multi-dimensional information.

[0007] As a preferred technical solution, the dynamic drill-down and backtracking process between the geographic region levels includes the following steps: The default view loads the national view, displaying provincial summary data. When a user selects a region in a province, drill down to the corresponding province view and display the city-level summary data. When a user selects a specific city area, drill down to the corresponding city view to display detailed customer data. Returning to the previous view allows for hierarchical backtracking.

[0008] As a preferred technical solution, the combined filtering conditions include time filtering conditions, steel mill filtering conditions, product filtering conditions, and regional filtering conditions. The time filtering conditions support the selection of custom date ranges and preset time periods. The steel mill filtering conditions support internal and external group classification and multi-selection operations. The product filtering conditions are based on the built-in steel sub-category library for selection. The regional filtering conditions support selection by province or city, and the regional filtering conditions are linked with map point selection operations.

[0009] As a preferred technical solution, the method of retrieving data that meets the conditions using a multidimensional index structure includes: An index structure is pre-established based on four dimensions: time, steel mill, product, and region. After receiving confirmed filtering conditions, the target data is located through the index structure.

[0010] As a preferred technical solution, the information display panel includes an overview tab, a sales information tab, a customer information tab, and a visit information tab. The request to refresh the business indicator data in the information display panel is achieved by listening to the hierarchy switching event and filter condition change event of the map view through the global state manager, calling multiple microservice interfaces in parallel to obtain the corresponding data, and driving each tab component to perform refresh-free updates.

[0011] As a preferred technical solution, the preprocessing includes data cleaning, deduplication, missing value filling and outlier removal, and extraction of core fields, which include the steel mill's unique identifier, latitude and longitude coordinates, internal and external group attributes, sales area code, product category, sales volume, transaction time, customer information and data source type.

[0012] As a preferred technical solution, the process of marking steel mills with icons corresponding to their attributes includes the following steps: The group's own steel mills will be marked with solid icons in the first color, while steel mills operated in cooperation with other companies outside the group will be marked with border icons in a different color.

[0013] As a preferred technical solution, the multi-source data includes platform transaction data, offline visit data, and steel mill production data; the classification of preprocessed data according to the data source for credibility includes: assigning different credibility levels to different data, and the credibility of data from both platform transactions and offline visits, platform transaction data, and offline visit data decreases sequentially.

[0014] As a preferred technical solution, the process of drawing the resource flow link from the steel mill to the sales area using differentiated line types includes the following steps: Solid lines are used to draw data from platform transactions, dashed lines are used to draw data from offline visits, and dotted dashed lines are used to draw data that comes from both platform transactions and offline visits.

[0015] Another aspect of the present invention provides a resource flow and multi-dimensional visualization analysis system for the steel industry, used to implement the aforementioned resource flow and multi-dimensional visualization analysis method for the steel industry. The system includes: The multi-source data acquisition and trusted processing module is used to acquire multi-source data from the steel business and perform preprocessing, as well as classify the preprocessed data according to the trustworthiness of the data source. The GIS geographic visualization rendering module is used to mark steel mills on a GIS map using icons corresponding to their attributes, and to draw resource flow links using differentiated line types based on the credibility classification, thereby generating a resource flow visualization map. The three-level geographic multidimensional drill-down module is used to respond to the user's selection of geographic regions, realize dynamic drill-down and backtracking between the national view, provincial view, and city view, and trigger data aggregation or splitting at the corresponding level. The multi-condition combination precise filtering module is used to provide a combination of filtering conditions including at least time, steel mill, product and region, and to retrieve data that meets the conditions using a multi-dimensional index structure; The global data linkage display module is used to set up the information display panel and listen for operation events through the global status manager to drive the real-time linkage refresh of the resource flow to the visualization map and the information display panel. And underlying support components, which provide data storage, computing and interface support for each module.

[0016] Compared with the prior art, the present invention has at least one of the following beneficial effects: (1) The integration and visualization of steel resource flow with geographic information and data credibility has been realized: Existing technologies focus on spatial analysis such as network analysis and collision detection within the plant area, which cannot integrate and analyze multi-source market sales data after steel products leave the plant. They lack the assessment and display of the credibility of data sources, making it difficult to support accurate decision-making at the market level. This invention classifies multi-source data by credibility and uses differentiated line types to draw the resource flow link from the steel plant to the national sales area on the map. This extends the analytical perspective from the plant area to the national market, enabling decision-makers to intuitively understand the distribution and context of resources with different credibility in the national market, avoiding low-quality data from misleading market decisions, and significantly improving the efficiency of data interpretation.

[0017] (2) Improve the adaptability of decision-making scenarios: Existing technologies are only for analysis of fixed spaces within the factory and do not have the ability to perform large-scale, multi-level geographical drill-down and data aggregation and splitting. They cannot meet the continuous analysis needs from macro market layout to micro customer details. This invention responds to the user's selection of geographical areas and realizes dynamic drill-down and backtracking of three-level views of the country, provinces and cities. When switching levels, it simultaneously performs data aggregation or splitting of the corresponding level, filling the gap of existing technologies in the granularity of macro market analysis. It provides decision-makers with seamless full-granular market analysis capabilities, which can not only overlook the national market pattern, but also penetrate to the customer details of a single city. The adaptability of decision-making scenarios is qualitatively improved.

[0018] (3) It achieves accurate and rapid positioning of massive market sales data: Existing business analysis components do not include multi-dimensional retrieval of market sales data and cannot support combined queries by market business dimensions such as time, product category, and customer region. It is difficult to quickly locate target market data. This invention receives combined filtering conditions that include at least time, steel mill, product, and region, and uses a specially constructed multi-dimensional index structure to quickly retrieve target data. It achieves accurate and rapid positioning of massive market sales data, shortening the traditional data query work that takes several minutes or even longer to the second level. This enables market analysts to quickly define the sales picture of specific products, specific time periods, and specific regions, greatly improving the flexibility and efficiency of market analysis.

[0019] (4) Enhance user experience: Existing technologies aim to optimize the layout and logistics of the plant through spatial analysis. Their functional design does not fit the business characteristics of steel companies’ sales departments in analyzing, monitoring and making decisions on the flow of market resources. This invention distinguishes the attributes of steel plants inside and outside the group and uses different icons, has a built-in steel sub-category library, and provides customized functions that are deeply integrated with the market sales business of the steel industry, such as providing visit information linkage. It realizes a set of technical solutions tailored to the scenario of resource flow and market analysis in the steel industry, avoids the redundancy and incompatibility defects of general or other scenario tools, and the operation process is fully in line with the usage habits of the sales decision-making team. Attached Figure Description

[0020] Figure 1 This is a flowchart of a resource flow and multi-dimensional visualization analysis method for the steel industry, as shown in the embodiment. Figure 2 This is a schematic diagram illustrating the data processing and display process in the embodiment; Figure 3 This is a schematic diagram of a resource flow and multi-dimensional visualization analysis system for the steel industry, as shown in the embodiment. Figure 4 This is a schematic diagram of the system workflow in the embodiment. Detailed Implementation

[0021] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0022] Example 1 To address the problems existing in the aforementioned prior art, this embodiment provides a method for resource flow and multi-dimensional visualization analysis in the steel industry.

[0023] See Figure 2 The method first acquires multi-source data, including platform transaction data, site visit data, and steel mill-related data. Then, the data platform collects, cleans, and integrates the data, subsequently providing a unified data service API. Data is then combined and filtered within a visualization application, and multi-dimensional drill-down views (national / provincial / city views) are enabled for data linkage.

[0024] See Figure 1 and Figure 4 The method includes the following steps: Step S1, Targeted Collection and Preprocessing of Multi-Source Steel Business Data: Acquire multi-source data of steel business and preprocess it. Classify the preprocessed data according to the credibility of the data source to obtain standardized data including credibility category identifiers.

[0025] The entire process is integrated with the enterprise's data platform, enabling fully automated data collection and processing without manual intervention. Specific operational steps are as follows: 1. Data Source Integration and Targeted Data Acquisition. The module connects to the enterprise's three core data sources using ETL tools such as Sqoop and DataX.

[0026] The platform's transaction database includes formal business data such as sales contracts, logistics tracking numbers, transaction amounts, sales volumes, and customer contract information. The offline visit and data collection database includes research data such as on-site visit records by marketing personnel, customer feedback, and potential cooperation information. The steel mill production database includes production-side data such as steel mill location, capacity, product categories, and inventory, enabling full data synchronization and offline batch collection.

[0027] 2. Data Cleaning and Outlier Removal. The built-in outlier monitoring engine performs deduplication, noise reduction, missing value imputation, and outlier removal on the collected raw data, eliminating invalid visit data and erroneous data with missing geographical locations to ensure the quality of basic data.

[0028] 3. Data Standardization and Core Field Extraction. Standardize data formats, units, and field naming rules, and extract core analytical fields, including: unique steel mill identifier, steel mill latitude and longitude coordinates, internal and external group attributes, administrative division code of sales area, product subcategories, sales volume, transaction time, customer information, data source type, and visit status, forming a structured and standardized core dataset.

[0029] 4. Data Classification, Labeling, and Credibility Assessment. Based on data source and reliability, standardized data is divided into three categories and labeled. The first category is platform transaction data, which has high credibility and serves as the core basis for decision-making. The second category is data collected through offline visits, which has moderate credibility and serves as a supplementary basis for decision-making. The third category is dual-source overlapping data, i.e., verified by both transactions and visits, which has the highest credibility and enables full-process data traceability.

[0030] Step S2, Construction of a three-level geographic base map and differentiated visualization rendering based on GIS technology: On the GIS map, steel plants are marked with icons corresponding to their attributes according to their location information, and resource flow links from steel plants to sales areas are drawn using differentiated line types according to credibility category identifiers, generating a resource flow visualization map.

[0031] Based on a GIS geographic information system, a three-level linked map base map is built, linking the national, provincial, and city levels. Differentiated visual identifiers intuitively distinguish steel plant attributes, data sources, and resource flows, solving the problems of mixed and spatially inefficient traditional data displays. Specific detailed operations are as follows: 1. Construction of a three-level GIS base map. Using official administrative division data, a precise three-level geographic base map is built, binding national, provincial, and city-level administrative division codes, establishing a spatial indexing mechanism, and supporting zooming, panning, and full-screen display.

[0032] 2. Differentiated icon rendering for steel mills. Based on the attributes of steel mills within and outside the group, different colored icons are used for precise positioning and labeling: solid blue icons identify steel mills owned by the group, while white-bordered icons identify cooperative steel mills outside the group. The icon positions are linked to the actual latitude and longitude of the steel mills, allowing users to quickly identify the attributes and distribution of steel mills through the icons.

[0033] 3. Differentiated rendering of resource flow to sales channels. Based on the data classification and labeling results, different line types are used to draw the resource flow channels from steel mills to sales areas, enabling visual differentiation of data sources. Solid lines correspond to the first type of high-reliability transaction data, dashed lines correspond to the second type of data collected through site visits, and dotted dashed lines correspond to the third type of data with overlapping dual sources. One end of the line is precisely bound to the steel mill icon, and the other end extends to the corresponding sales area, intuitively presenting the resource flow.

[0034] 4. Basic geographic information labeling. The names of provinces, city administrative divisions, core logistics hubs, and key customer areas are simultaneously labeled on the base map to help decision-makers quickly locate geographic locations and improve the spatial display logic.

[0035] Step S3: In response to the user's selection of a geographic region, dynamic drill-down and backtracking between geographic region levels are implemented, and data aggregation or splitting of the corresponding level is performed synchronously when switching levels.

[0036] It supports manual user-triggered level switching, enabling seamless drill-down and backtracking from macro to micro levels. The drill-down process involves no page redirection or data delay, and all analysis data at the corresponding level is updated synchronously. Specific detailed operations are as follows: 1. Initial loading of the national view. The system loads the national map view by default, which displays macro indicators such as the distribution of all steel mills nationwide, cross-provincial resource flow links, total national sales volume, and core steel mill capacity, helping decision-makers to control the overall layout of the national market.

[0037] 2. Drill-down operation in provincial view. When a user clicks on any province or administrative division icon in the national view, the front end automatically captures the unique administrative division code and name of that province. The drill-down module triggers spatial index retrieval, quickly retrieving data such as all steel mills, city-level sales chains, and sales volume distribution in various cities within the province. The map seamlessly switches to the provincial view.

[0038] 3. Drill-down operation in city view. When a user clicks on any city icon in the provincial view, the front end captures the corresponding city's administrative division code and drills down to the city-level view, displaying detailed data such as the distribution of steel mills within the city, key customer locations, sales volume per customer, and visit records, enabling refined analysis down to the city level.

[0039] 4. Hierarchical Backtracking and View Reset. Users can click the "Back to Previous Level" button to backtrack between cities, provinces, and the entire country. A one-click reset function restores the initial national view, meeting the needs of repeated comparative analysis.

[0040] 5. Drill-down data synchronization rules. Each time a level is switched, the aggregation and splitting of the corresponding level data are triggered synchronously. The national view displays provincial summary data, the provincial view displays city summary data, and the city view displays individual customer detailed data. The data caliber is consistent and unbiased throughout the process.

[0041] Step S4: Receive the user-defined combined filtering conditions, use a multi-dimensional index structure to retrieve data that meets the conditions, and dynamically update the resource flow visualization map based on the search results.

[0042] A multi-dimensional data index structure is built, supporting various operation methods such as drop-down selection, manual input, multi-selection, and selection of all, enabling multi-condition combined queries. The filtered results are fed back to the visualization module in real time, greatly improving data retrieval efficiency. Specific detailed operations are as follows: 1. Filtering configuration and operation.

[0043] Time filtering. By default, it automatically loads all data for the current year. It supports custom selection of start and end dates, accurate to the day. It also allows quick selection of commonly used time intervals such as the last 7 days, the last 30 days, and the last quarter, adapting to different period analysis needs.

[0044] Steel mill filtering. Supports categorized filtering of steel mills within and outside the group, as well as precise selection of single or multiple steel mills. The system is adaptable to the search needs of dozens of steel mills, with no data lag.

[0045] Product filtering. It has a built-in library of more than 20 subcategories in the steel industry, such as hot-rolled coils, cold-rolled coils, stainless steel, and silicon steel, supporting accurate filtering of all categories to fit the steel product business system.

[0046] Regional filtering. Supports precise filtering by province and city, and can be directly linked to the map for filtering.

[0047] 2. Multidimensional index retrieval and response.

[0048] Based on preprocessed standardized data, the module builds a four-dimensional index structure of time, steel mill, product, and region. After the user confirms the filtering conditions, the system quickly retrieves the target data with a filtering response time of ≤2 seconds, which is significantly more efficient than the 10-15 minute retrieval time of traditional tools.

[0049] 3. Screening results are provided in real time.

[0050] After filtering is completed, the map view automatically highlights the steel mills and sales links that meet the criteria, hides irrelevant data, and the global data linkage module updates the corresponding indicators in sync, realizing the integration of filtering and display.

[0051] Step S5: Set up an information display panel in the associated display area of ​​the map view. In response to the detection of a level switch or filter condition change in the map view, request and refresh the business indicator data in the information display panel to realize the linkage display of map view and multi-dimensional information.

[0052] This step relies on the global state manager to achieve seamless linkage of all components without page refresh, breaking the drawbacks of traditional page jumps and scattered data. It integrates and displays macro indicators and micro details, making it convenient for decision-makers to obtain complete information in one stop. The specific detailed operations are as follows.

[0053] 1. Integrated Display Panel Layout. An integrated display panel is fixed on the right side of the GIS map, divided into four independent tabs: Overview, Sales Information, Customer Information, and Visit Information. The panel position is fixed and does not move with map zooming or panning, making it convenient to operate and providing a user-friendly experience.

[0054] 2. Global Status Monitoring and Scheduling. The system has a built-in global status manager that monitors map drill-down events, filter condition change events, and data update events in real time. Once a status change is detected, multiple microservice API calls are immediately triggered in parallel to schedule the corresponding data.

[0055] 3. Data refreshes in tandem across all tabs. The four tabs, as independent UI components, receive API data in real time and automatically refresh the data without manual loading. The Overview tab displays core metrics such as total sales volume, total transaction value, number of users served, and number of users visited, depending on the level / filter criteria. The Sales Information tab displays the steel mill's regional product distribution, regional category distribution, monthly sales performance, and major sales cities. The Customer Information tab displays customer-related data such as the list of core customers, the number of new customers, and customer distribution. The Visit Information tab displays business follow-up data such as visit records, number of visits by marketing personnel, and conversion rates of potential customers.

[0056] This method has the following characteristics: (1) Differentiated visualization of multi-source data. Color icons are used to distinguish steel plant types, and three line types are used to distinguish data sources, so as to realize the intuitive display of data in multiple dimensions. Decision-makers can quickly identify the credibility of data sources, avoid abnormal data from misleading decisions, improve the efficiency of data interpretation compared with traditional methods, and make the resource flow and distribution pattern clear at a glance, reducing the cost of manual analysis.

[0057] (2) Three-level geographic drill-down combined with data linkage, drill-down at the national, provincial and city levels, and synchronously update the corresponding multi-dimensional data to meet the needs of different granularity analysis, covering all dimensions from macro market to micro customer, and improving the adaptability of decision-making scenarios by 90%; realizing continuous and refined analysis, and completely solving the problems of single analysis granularity and scenario fragmentation of traditional tools.

[0058] (3) By combining four dimensions of time, steel plant, product and region, multi-condition combination query is constructed to accurately locate target data and shorten the screening response time. Compared with the traditional 10-15 minute retrieval time, the query efficiency is improved, the target data is accurately located, and the preparation time in the early stage of analysis is greatly shortened.

[0059] (4) Customized adaptation for the steel industry. Built-in steel mill classification, steel sub-category library, visit data linkage, logistics link display and other industry-specific functions, which are tailored to the characteristics of steel business, avoid the drawbacks of redundant functions and insufficient adaptation of general tools, the operation process is in line with the usage habits of industry personnel, the ease of operation is improved, and the actual application value of the system is greatly improved.

[0060] (5) Unified Linked Display Without Refreshing. Real-time linkage between map, filter, and indicator panel is achieved through the global status manager. All data can be integrated without switching pages, which shortens the time for decision-makers to obtain complete information, avoids errors in manual data integration, greatly improves the immersive analysis experience, improves overall decision-making efficiency, and helps enterprises respond quickly to market changes.

[0061] Example 2 Based on Example 1, this example provides a resource flow and multi-dimensional visualization analysis system for the steel industry. It is used to implement the resource flow and multi-dimensional visualization analysis method for the steel industry in Example 1. The system adopts a hierarchical modular architecture combined with closed-loop interaction. The core of the system consists of five core functional modules, data interaction interfaces, and underlying support components. The modules achieve bidirectional real-time data interaction through high-speed data interfaces, without page jumps or data delays. The overall architecture has the characteristics of high cohesion, low coupling, and scalability, and is suitable for the massive multi-source data processing and real-time visualization needs of the steel industry.

[0062] See Figure 3 The system includes: (1) Multi-source data acquisition and trusted processing module, which implements the function of step S1 in Example 1. Specifically, it is used to acquire multi-source data of steel business and perform preprocessing, and classify the preprocessed data according to the data source based on the credibility.

[0063] (2) GIS geographic visualization rendering module, which implements the function of step S2 in embodiment 1, is used to mark steel plants on the GIS map with icons corresponding to the attributes of steel plants, and draw resource flow links with differentiated line types according to the credibility classification, and generate a resource flow visualization map. (3) The three-level geographic multidimensional drill-down module realizes the function of step S3 in Example 1. It is used to respond to the user's selection operation of geographic area, realize dynamic drill-down and backtracking between national view, provincial view and city view, and trigger data aggregation or splitting at the corresponding level. (4) Multi-condition combination precise screening module, which realizes the function of step S4 in Example 1, is used to provide at least a combination of screening conditions including time, steel plant, product and region, and to use a multi-dimensional index structure to retrieve data that meets the conditions; (5) Global data linkage display module, which implements the function of step S4 in embodiment 1, is used to set the information display panel and listen to operation events through the global status manager to drive the real-time linkage refresh of the resource flow visualization map and the information display panel. (6) Underlying support components, used to provide data storage, computing and interface support for each module.

[0064] The system follows a workflow of data input, standardized processing, spatial visualization rendering, user interaction command reception, data retrieval and updating, integrated linkage display, and decision output. First, the multi-source data acquisition and reliable processing module connects to the enterprise data platform to collect, clean, classify, and standardize multi-source heterogeneous data, generating a high-quality core dataset. Then, the data is transmitted to the GIS geographic visualization rendering module via API, where a three-level map is built and differentiated visualization rendering is achieved based on GIS technology. Simultaneously, the basic data is pushed to the global data linkage display module. When users issue operation commands through the three-level geographic multi-dimensional drill-down module and the multi-condition combination precise filtering module, the commands are transmitted in real-time to the data processing and visualization modules. The data processing module quickly retrieves target data using multi-dimensional indexes, while the visualization module synchronously updates the map view. The global state manager monitors all operations and data changes throughout the process, scheduling microservice API interfaces in parallel to drive the right-side linkage panel to refresh data in real-time. Ultimately, this achieves an intuitive display and in-depth analysis of resource flows, with no data delays or page jumps, forming a complete technical closed loop. This provides strong technical support for steel enterprises' resource allocation, market layout, and marketing decisions.

[0065] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for resource flow and multi-dimensional visualization analysis in the steel industry, characterized in that, Includes the following steps: Acquire multi-source data from the steel business and preprocess it. Classify the preprocessed data according to the credibility of the data source to obtain standardized data including credibility category identifiers. On the GIS map, based on the location information of the steel plant, the steel plant is marked with an icon corresponding to its attributes. Based on the credibility category identifier, a differentiated line type is used to draw the resource flow link from the steel plant to the sales area, generating a resource flow visualization map. In response to the user's selection of a geographic region, dynamic drill-down and backtracking between geographic region levels are realized, and data aggregation or splitting of the corresponding level is performed synchronously when switching levels. The system receives user-defined combined filtering conditions, which include at least two of the following: time, steel mill, product, and region. It uses a multidimensional index structure to retrieve data that meets the conditions and dynamically updates the resource flow visualization map based on the retrieval results. An information display panel is set up in the associated display area of ​​the map view. In response to the detection of a hierarchical switch or a change in the filtering conditions of the map view, the business indicator data in the information display panel is requested and refreshed to realize the linkage display of the map view and multi-dimensional information.

2. The resource flow and multi-dimensional visualization analysis method for the steel industry according to claim 1, characterized in that, The dynamic drill-down and backtracking process between geographic region levels includes the following steps: The default view loads the national view, displaying provincial summary data. When a user selects a region in a province, drill down to the corresponding province view and display the city-level summary data. When a user selects a specific city area, drill down to the corresponding city view to display detailed customer data. Returning to the previous view allows for hierarchical backtracking.

3. The resource flow and multi-dimensional visualization analysis method for the steel industry according to claim 1, characterized in that, The combined filtering conditions include time filtering conditions, steel mill filtering conditions, product filtering conditions, and regional filtering conditions. The time filtering conditions support the selection of custom date ranges and preset time periods. The steel mill filtering conditions support internal and external group classification and multi-selection operations. The product filtering conditions are based on the built-in steel sub-category library. The regional filtering conditions support selection by province or city, and the regional filtering conditions are linked to map point selection operations.

4. The resource flow and multi-dimensional visualization analysis method for the steel industry according to claim 3, characterized in that, The method of retrieving data that meets the conditions using a multidimensional index structure includes: An index structure is pre-established based on four dimensions: time, steel mill, product, and region. After receiving confirmed filtering conditions, the target data is located through the index structure.

5. The resource flow and multi-dimensional visualization analysis method for the steel industry according to claim 1, characterized in that, The information display panel includes an overview tab, a sales information tab, a customer information tab, and a visit information tab. The request to refresh the business indicator data in the information display panel is achieved by listening to the hierarchy switching event and filter condition change event of the map view through the global state manager, calling multiple microservice interfaces in parallel to obtain the corresponding data, and driving each tab component to perform refresh-free updates.

6. The resource flow and multi-dimensional visualization analysis method for the steel industry according to claim 1, characterized in that, The preprocessing includes data cleaning, deduplication, missing value filling, and outlier removal, and extracts core fields, including the steel mill's unique identifier, latitude and longitude coordinates, internal and external group attributes, sales area code, product category, sales volume, transaction time, customer information, and data source type.

7. The resource flow and multi-dimensional visualization analysis method for the steel industry according to claim 1, characterized in that, The process of using icons corresponding to steel mill attributes to mark steel mills includes the following steps: The group's own steel mills will be marked with solid icons in the first color, while steel mills operated in cooperation with other companies outside the group will be marked with border icons in a different color.

8. The resource flow and multi-dimensional visualization analysis method for the steel industry according to claim 1, characterized in that, The multi-source data includes platform transaction data, offline visit data, and steel mill production data. The classification of preprocessed data based on its source of credibility includes: assigning different credibility levels to different data, with the credibility of data originating from both platform transactions and offline visits decreasing sequentially from platform transaction data to offline visit data.

9. A method for resource flow and multi-dimensional visualization analysis in the steel industry according to claim 8, characterized in that, The process of using differentiated line types to draw the resource flow link from the steel mill to the sales area includes the following steps: Solid lines are used to draw data from platform transactions, dashed lines are used to draw data from offline visits, and dotted dashed lines are used to draw data that comes from both platform transactions and offline visits.

10. A resource flow and multi-dimensional visualization analysis system for the steel industry, characterized in that, The system is used to implement the resource flow and multi-dimensional visualization analysis method for the steel industry as described in any one of claims 1-9, and includes: The multi-source data acquisition and trusted processing module is used to acquire multi-source data from the steel business and perform preprocessing, as well as classify the preprocessed data according to the trustworthiness of the data source. The GIS geographic visualization rendering module is used to mark steel mills on a GIS map using icons corresponding to their attributes, and to draw resource flow links using differentiated line types based on the credibility classification, thereby generating a resource flow visualization map. The three-level geographic multidimensional drill-down module is used to respond to the user's selection of geographic regions, realize dynamic drill-down and backtracking between the national view, provincial view, and city view, and trigger data aggregation or splitting at the corresponding level. The multi-condition combination precise filtering module is used to provide a combination of filtering conditions including at least time, steel mill, product and region, and to retrieve data that meets the conditions using a multi-dimensional index structure; The global data linkage display module is used to set up the information display panel and listen for operation events through the global status manager to drive the real-time linkage refresh of the resource flow to the visualization map and the information display panel. And underlying support components, which provide data storage, computing and interface support for each module.

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