Method for calculating imbalance of regional economic coordination degree based on taiji gradient
By combining a hierarchical architecture and a Taiji gradient model, the problems of real-time monitoring of regional economic coordination and identification of multi-dimensional imbalances were solved, enabling efficient and accurate identification and optimized regulation of regional economic data.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- 顾慧伦
- Filing Date
- 2026-04-17
- Publication Date
- 2026-07-31
AI Technical Summary
Existing technologies cannot achieve real-time monitoring of regional economic coordination and identification of multi-dimensional imbalance characteristics. They are difficult to adapt to the real-time processing needs of multi-regional, high-frequency, and large-scale economic data, and lack the ability to identify implicit and transmissive imbalances.
It adopts a three-tiered architecture of regional economic monitoring terminals, edge gateways, and regional edge nodes. Combined with lightweight preprocessing and simplified algorithms, it performs real-time and in-depth re-examination through the Taiji gradient model, constructs a feature system of coordinated fluctuations, scene correlation, system coupling, and spatiotemporal correlation, generates imbalance analysis reports, and provides optimization and control measures.
It enables real-time and efficient processing of economic data from multiple regions, significantly reduces data transmission volume and terminal computing power consumption, improves the comprehensiveness and accuracy of imbalance identification, can capture various types of imbalance, and its theoretical mechanism is more in line with the operating rules of the economic system.
Smart Images
Figure CN122492414A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of electricity meter data processing, and in particular to a method for calculating regional economic coordination imbalance based on Taiji gradient. Background Technology
[0002] Against the backdrop of the comprehensive implementation of the national strategy for coordinated regional development, regional economic systems are exhibiting complex operational characteristics characterized by multi-regional linkages, multi-factor coupling, and multi-scenario evolution. Accurately quantifying the degree of regional economic coordination, rapidly identifying imbalances, and effectively tracking the transmission paths of imbalances have become core technical requirements for macroeconomic regulation, regional planning, and optimal resource allocation.
[0003] Current mainstream methods for measuring regional economic coordination and imbalance include coupled coordination degree models, entropy weight methods, TOPSIS models, spatial Markov chains, and spatial Durbin models. However, these methods suffer from four significant technical shortcomings in practical applications: Traditional methods rely primarily on static calculations and lack a hierarchical, real-time data processing architecture. They are ill-suited to the real-time monitoring needs of multi-regional, high-frequency, and large-scale economic data, resulting in significant data transmission pressure and high terminal computing power consumption, making it difficult to achieve real-time early warning of regional economic imbalances. Existing technologies have not constructed a systematic, multi-dimensional system of imbalance characteristics, reflecting coordination levels only from a single dimension. They cannot simultaneously capture multiple imbalance characteristics such as short-term fluctuations, long-term trends, scenario differences, system coupling, and spatial correlations, and lack the ability to identify implicit and transmissive imbalances.
[0004] Therefore, it is necessary to design a regional economic coordination imbalance calculation method based on Taiji gradient that can solve the above-mentioned technical defects. Summary of the Invention
[0005] To address the technical deficiencies in the background technology, this invention proposes a method for calculating regional economic coordination imbalance based on Taiji gradient, which solves the aforementioned technical problems and meets practical needs. The specific technical solution is as follows: The method for calculating regional economic coordination imbalance based on Taiji gradient includes the following steps: The system collects economic operation-related data through an architecture consisting of regional economic monitoring terminals and edge terminals, and performs lightweight preprocessing on the economic operation-related data. Based on the preprocessed economic operation-related data, we extract coordinated fluctuation characteristics, scenario-based economic correlation characteristics, system state coupling characteristics, and spatiotemporal correlation characteristics. Based on the feature vector composed of some features from the coordinated fluctuation characteristics, system state coupling characteristics and spatiotemporal correlation characteristics, the edge end uses a simplified algorithm to perform real-time preliminary detection and uploads suspected imbalance data to the cloud. Based on suspected imbalance data, the cloud platform combines all features with the Taiji gradient model to conduct in-depth re-examination, generate an imbalance analysis report, and generate corresponding optimization and control measures based on the imbalance analysis report.
[0006] Furthermore, the edge terminal includes edge gateways and regional edge nodes, and the specific process for collecting economic operation-related data is as follows: The regional economic monitoring terminal collects economic data, system status data, and environmental data at a set sampling period. The economic data includes total economic output, per capita output, industrial structure, residents' income, investment scale, and consumption level. The system status data includes economic operation stability, fiscal revenue and expenditure health, data communication quality, and system fault identification. The environmental data includes resource endowment, environmental capacity, policy support, and market openness. By aggregating economic data from multiple regions within a single city, administrative region, or economic zone through edge gateways, and collecting synchronous development data from various regions within the same economic circle; By covering multiple city clusters, economic belts, or provincial units through regional edge nodes, data on the stability of regional economic gradients, the characteristics of regional development peak and trough periods, and the propagation patterns of economic imbalances in adjacent regions are collected.
[0007] Furthermore, the lightweight preprocessing specifically includes: regional economic monitoring terminals using built-in thresholds to remove invalid data; edge gateways using time-series neighbor mean interpolation to fill in missing data; and regional edge nodes using simplified wavelet compression algorithms to reduce data volume while preserving time-series trends and spatial correlation characteristics.
[0008] Furthermore, the coordinated volatility characteristics include short-term volatility coefficient and long-term trend coefficient. The simplified formula for the short-term volatility coefficient is: F(t) = |P(t) - P_average(t)| / P_average(t); The simplified formula for the long-term trend coefficient is: Y = (End of period Y - Beginning of period Y) / N.
[0009] Furthermore, the scenario-based economic correlation characteristic is the scenario deviation value, which can be simplified into the following formula: C(t) = |P(t) - Pbasis(t)| / Pbasis(t).
[0010] Furthermore, the system state coupling characteristics include the correlation coefficient and the coupling feature vector. The simplified formula for the correlation coefficient is: R = .
[0011] Further spatiotemporal correlation characteristics include spatial coupling degree and regional imbalance propagation time difference. The simplified formula for spatial coupling degree is: ; The propagation time difference formula is: Trans(A, B) = Tpeak(B) - Tpeak(A).
[0012] Furthermore, the edge-end real-time initial detection uses a simplified LOF algorithm, and data that triggers imbalance candidates for multiple consecutive cycles is judged as suspected imbalanced data.
[0013] Furthermore, the cloud-based deep review adopts a simplified Taiji gradient model, with the core formula as follows: Taiji potential T=YZ Taiji gradient G=|T| Coordination degree C=2√(Y×Z) / (Y+Z) Imbalance degree D=1-C where Y is the positive potential of economic growth and Z is the negative potential of equilibrium constraint.
[0014] Furthermore, the imbalance levels are divided into three levels: mild, moderate, and severe, corresponding to regional optimization prompts, regional imbalance warnings, and cross-regional high-level control strategies, respectively.
[0015] Compared with existing technologies, the regional economic coordination imbalance calculation method based on Taiji gradient provided by this invention has the following beneficial effects: This invention employs a three-tiered data acquisition architecture consisting of regional economic monitoring terminals, edge gateways, and regional edge nodes. Combined with lightweight preprocessing techniques such as invalid data removal, missing value imputation, and data compression, it significantly reduces data transmission volume and terminal computing power consumption, enabling real-time and efficient processing of multi-regional economic data. It constructs a four-feature system encompassing coordinated fluctuations, scenario correlation, system coupling, and spatiotemporal correlation, comprehensively capturing various imbalance types such as short-term mutations, long-term deviations, scenario incompatibility, spatial imbalances, and transmission and diffusion, greatly improving the comprehensiveness and accuracy of imbalance identification. Furthermore, it introduces the Tai Chi gradient theory into the calculation of regional economic coordination, using Yin-Yang balance to reflect the dialectical unity of the economic system and gradient values to intuitively represent the intensity of imbalance, making the theoretical mechanism more aligned with the operational laws of the economic system. Attached Figure Description
[0016] Figure 1 This is a flowchart illustrating the method for calculating regional economic coordination imbalance based on Taiji gradient in this invention. Detailed Implementation
[0017] In the description of this invention, it should be understood that the terms "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "middle," and "inner," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. Furthermore, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, features defined with "first," "second," etc., may explicitly or implicitly include one or more of that feature. In the description of this invention, it should be noted that unless otherwise explicitly specified and limited, the terms "installed," "connected," and "joined" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention through specific circumstances.
[0018] The embodiments of the present invention will be described below with reference to the accompanying drawings and related examples. The embodiments of the present invention are not limited to the following examples, and the present invention relates to the relevant necessary components in this technical field, which should be regarded as well-known technology in this technical field and can be known and mastered by those skilled in this technical field.
[0019] See Figure 1 This invention provides a method for calculating regional economic coordination imbalance based on Taiji gradient, comprising the following steps: Economic operation-related data is collected through an architecture consisting of regional economic monitoring terminals and edge terminals. This data undergoes lightweight preprocessing, which includes: regional economic monitoring terminals using built-in thresholds to remove invalid data; edge gateways using time-series neighbor-mean interpolation to fill in missing data; and regional edge nodes employing a simplified wavelet compression algorithm to reduce data volume while preserving temporal trends and spatial correlation characteristics. The edge terminals, including edge gateways and regional edge nodes, are used in the following specific process for collecting economic operation-related data: The regional economic monitoring terminal collects economic data, system status data, and environmental data at a set sampling period. The economic data includes total economic output, per capita output, industrial structure, residents' income, investment scale, and consumption level. The system status data includes economic operation stability, fiscal revenue and expenditure health, data communication quality, and system fault identification. The environmental data includes resource endowment, environmental capacity, policy support, and market openness. By aggregating economic data from multiple regions within a single city, administrative region, or economic zone through edge gateways, and collecting synchronous development data from various regions within the same economic circle; By covering multiple city clusters, economic zones, or provincial units through regional edge nodes, data on the stability of regional economic gradients, the characteristics of peak and trough periods in regional development, and the propagation patterns of economic imbalances in adjacent regions are collected. Real-time initial detection at the edge nodes employs a simplified LOF algorithm; data triggering imbalance candidates for multiple consecutive periods is classified as suspected imbalance data. Imbalance levels are categorized into three levels: mild, moderate, and severe, corresponding to regional optimization prompts, regional imbalance warnings, and cross-regional high-level regulatory strategies, respectively.
[0020] Based on preprocessed economic operation data, coordinated fluctuation characteristics, scenario-based economic correlation characteristics, system state coupling characteristics, and spatiotemporal correlation characteristics are extracted. Coordinated fluctuation characteristics include short-term fluctuation coefficients and long-term trend coefficients. The simplified formula for the short-term fluctuation coefficient is: F(t) = |P(t) - P_average(t)| / P_average(t); The simplified formula for the long-term trend coefficient is: Y = (End of period Y - Beginning of period Y) / N.
[0021] The scenario-based economic correlation feature is the scenario deviation value, and the simplified calculation formula is: C(t) = |P(t) - Pbasis(t)| / Pbasis(t).
[0022] System state coupling characteristics include correlation coefficient and coupling feature vector. The simplified formula for the correlation coefficient is: R = .
[0023] Based on the feature vector composed of some features from the characteristics of coordinated fluctuation, system state coupling, and spatiotemporal correlation, the edge terminal uses a simplified algorithm for real-time initial detection and uploads suspected imbalance data to the cloud; the cloud-based deep re-inspection uses a simplified Taiji gradient model, with the core formula as follows: Taiji potential T=YZ Taiji gradient G=|T| Coordination degree C=2√(Y×Z) / (Y+Z) Imbalance degree D=1-C where Y is the positive trend of economic growth and Z is the negative trend of equilibrium constraint.
[0024] Based on suspected imbalance data, the cloud platform combines all features with the Taiji gradient model to conduct in-depth re-examination, generate an imbalance analysis report, and generate corresponding optimization and control measures based on the imbalance analysis report.
[0025] Spatiotemporal correlation characteristics include spatial coupling degree and regional imbalance propagation time difference. The simplified formula for spatial coupling degree is: ; The propagation time difference formula is: Trans(A, B) = Tpeak(B) - Tpeak(A).
[0026] Example 1: Calculation Steps for Imbalanced Economic Coordination in a Single City Region (S100): Data Acquisition and Lightweight Preprocessing. Taking a prefecture-level city as the research object, regional economic monitoring terminals are deployed to collect data on total economic output, per capita income, industrial structure, fiscal health, and resource environment at the district and county levels; edge gateways aggregate data from each district and county to calculate the synchronicity of regional development; regional edge nodes summarize city-wide data to monitor the stability of the city's economic gradient. Terminals remove abnormal data that significantly exceeds the historical reasonable range; edge gateways fill in short-term missing data using the mean of neighboring values; regional edge nodes simplify and compress the data, preserving trends and correlation characteristics.
[0027] Step S200: Multi-dimensional feature extraction calculates the short-term fluctuation coefficient of the economic index of each district and county to identify short-term abrupt changes; calculates the long-term trend coefficient to determine whether the economy is on an upward, downward, or stable trend; calculates the scenario deviation value according to the main urban area, suburbs, and county scenarios respectively; calculates the correlation coefficient between economic development and system stability, and the synchronicity between regions; calculates the spatial coupling degree and the time difference of imbalance propagation to form a complete feature set.
[0028] Step S300: The edge terminal real-time initial inspection constructs an initial inspection feature set based on short-term fluctuation coefficient, system coupling characteristics, and spatial coupling degree; a simplified LOF algorithm is used for rapid judgment; if a certain data meets the imbalance condition for three consecutive periods, it is marked as suspected imbalance data and uploaded to the cloud.
[0029] Step S400: Cloud-based deep review and control output of all cloud access features, calculation of Yang momentum, Yin momentum, Taiji momentum, Taiji gradient, coordination degree, and imbalance degree; determine that the region is slightly imbalanced, the reason for which is that the tertiary industry fluctuates too much and there are local deviations in urban and rural development; generate a slightly imbalance analysis report, output optimization instructions through the edge gateway, and suggest optimizing the layout of the service industry and strengthening the flow of urban and rural factors.
[0030] Example 2: Calculation of Economic Imbalance in Urban Agglomerations. Taking a medium-sized urban agglomeration as an example, the method of this invention is used to perform the entire calculation process. Data Layer: Terminals collect economic, social, resource, and environmental data from each city; gateways aggregate city-wide data; edge nodes cover the entire urban agglomeration. Preprocessing Layer: Outlier removal, missing value imputation, and data compression are completed. Feature Layer: Fluctuation features, scene features, coupling features, and spatiotemporal features are extracted to identify low synchronicity in development between core and peripheral cities within the urban agglomeration, decreased spatial coupling, and a slow transmission trend of imbalance. Initial Edge Detection: Three peripheral cities are marked as suspected imbalance areas. Cloud-based Re-detection: Using the Taiji gradient model, the imbalance degree is in the moderate range, and the imbalance gradient shows an expanding trend; it is determined to be moderate imbalance, mainly due to unreasonable industrial division of labor and insufficient infrastructure connectivity. Regulation Output: A moderate imbalance alarm is sent to the regional economic regulation platform, providing specific feature data and location information, and suggesting the promotion of industrial synergy, infrastructure integration, and equalization of basic public services.
[0031] A severe anomaly indicates an abnormal state that has been confirmed or is highly suspected of being a serious electricity safety incident. It can be used to identify major risks, such as electricity theft, main line faults, or transformer overload. Regional optimization strategies include, but are not limited to, adjusting transformer tap positions, issuing peak-shifting electricity usage recommendations, and activating backup power supply plans, among others.
[0032] This invention achieves differentiated handling from the user side to the regional side through a hierarchical response mechanism. It can establish a mapping relationship between detection results and handling actions, realize rapid location and hierarchical response to abnormal events, improve the stability of power grid operation and maintenance efficiency, and enhance the system's adaptive response capability to power consumption anomalies at different levels.
[0033] The above description is only a preferred embodiment of the present invention. It should be noted that those skilled in the art can make several improvements and modifications without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.
Claims
1. A method for calculating regional economic coordination imbalance based on Taiji gradient, characterized in that, Includes the following steps: The system collects economic operation-related data through an architecture consisting of regional economic monitoring terminals and edge terminals, and performs lightweight preprocessing on the economic operation-related data. Based on the preprocessed economic operation-related data, we extract coordinated fluctuation characteristics, scenario-based economic correlation characteristics, system state coupling characteristics, and spatiotemporal correlation characteristics. Based on the feature vector composed of some features from the coordinated fluctuation characteristics, system state coupling characteristics and spatiotemporal correlation characteristics, the edge end uses a simplified algorithm to perform real-time preliminary detection and uploads suspected imbalance data to the cloud. Based on suspected imbalance data, the cloud platform combines all features with the Taiji gradient model to conduct in-depth re-examination, generate an imbalance analysis report, and generate corresponding optimization and control measures based on the imbalance analysis report.
2. The Taiji gradient-based regional economic coordination degree imbalance calculation method according to claim 1, characterized in that, The edge terminal includes edge gateways and regional edge nodes. The specific process for collecting economic operation-related data is as follows: The regional economic monitoring terminal collects economic data, system status data, and environmental data at a set sampling period. The economic data includes total economic output, per capita output, industrial structure, residents' income, investment scale, and consumption level. The system status data includes economic operation stability, fiscal revenue and expenditure health, data communication quality, and system fault identification. The environmental data includes resource endowment, environmental capacity, policy support, and market openness. By aggregating economic data from multiple regions within a single city, administrative region, or economic zone through edge gateways, and collecting synchronous development data from various regions within the same economic circle; By covering multiple city clusters, economic belts, or provincial units through regional edge nodes, data on the stability of regional economic gradients, the characteristics of regional development peak and trough periods, and the propagation patterns of economic imbalances in adjacent regions are collected.
3. The Taiji gradient-based regional economic coordination degree imbalance calculation method according to claim 2, characterized in that, The lightweight preprocessing specifically includes: regional economic monitoring terminals using built-in thresholds to remove invalid data; edge gateways using time-series neighbor mean interpolation to fill in missing data; and regional edge nodes using simplified wavelet compression algorithms to reduce data volume while preserving time-series trends and spatial correlation characteristics.
4. The Taiji gradient-based regional economic coordination degree imbalance calculation method according to claim 1, characterized in that, Coordinated volatility characteristics include short-term volatility coefficient and long-term trend coefficient. The simplified formula for the short-term volatility coefficient is: F(t) = |P(t) - P_average(t)| / P_average(t); The simplified formula for the long-term trend coefficient is: Y = (End of period Y - Beginning of period Y) / N.
5. The Taiji gradient-based regional economic coordination degree imbalance calculation method according to claim 1, characterized in that, The scenario-based economic correlation feature is the scenario deviation value, and the simplified calculation formula is: C(t) = |P(t) - Pbasis(t)| / Pbasis(t).
6. The Taiji gradient-based regional economic coordination degree imbalance calculation method according to claim 2, characterized in that, System state coupling characteristics include correlation coefficient and coupling feature vector. The simplified formula for the correlation coefficient is: R = 。 7. The method for calculating regional economic coordination imbalance based on Taiji gradient according to claim 4, characterized in that, Spatiotemporal correlation characteristics include spatial coupling degree and regional imbalance propagation time difference. The simplified formula for spatial coupling degree is: ； The propagation time difference formula is: Trans(A, B) = Tpeak(B) - Tpeak(A). 8.The Taiji gradient-based regional economic coordination imbalance calculation method according to claim 1, characterized in that, The edge-end real-time initial detection uses a simplified LOF algorithm, and data that triggers imbalance candidates for multiple consecutive cycles is judged as suspected imbalanced data.
9. The method for calculating regional economic coordination imbalance based on Taiji gradient according to claim 1, characterized in that, The cloud-based deep review adopts a simplified Taiji gradient model, with the core formula as follows: Taiji potential T=YZ Taiji gradient G=|T| Coordination degree C=2√(Y×Z) / (Y+Z) Imbalance degree D=1-C where Y is the positive potential of economic growth and Z is the negative potential of equilibrium constraint.
10. The Taiji gradient-based regional economic coordination degree imbalance calculation method according to claim 9, characterized in that, The imbalance level is divided into three levels of mild, moderate and severe, which correspond to regional optimization prompt, regional imbalance alarm and cross-regional high-level control strategy respectively.