Economic index time domain feature data processing method and related device

Abstract

The invention discloses an economic index time domain feature data processing method and a related device. The method comprises the following steps: detecting a trigger operation for an index analysis control of an economic index analysis function interface; in response to a trigger operation of the index analysis control, creating and sending an economic index time domain feature analysis request message carrying identification information of the target region, time period description information of the first time period and the power utilization index; an economic index time domain feature analysis response message from the server is received, and the index analysis response message comprises a first time domain feature analysis result of the macroeconomic index of the target area in the first time period; analyzing the economic index time domain feature analysis response message to obtain a first time domain feature analysis result; and displaying the first time domain feature analysis result of the macroeconomic index on an economic index analysis function interface. According to the method, the intelligence, the accuracy and the efficiency of processing the time domain characteristics of the macroeconomic indexes of the specific time period of the target region by the equipment are improved.

Description

Technical Field

[0001] The present application relates to the technical field of data analysis, and in particular to a method for processing time-domain characteristic data of economic indicators and related devices. Background Art

[0002] The current method of analyzing the time domain characteristics of the macroeconomy mainly relies on macroeconomic statistical data and questionnaire surveys, which have problems such as high data acquisition cost, slow update speed, and poor timeliness. Summary of the invention

[0003] The embodiments of the present application provide a method and related apparatus for processing time-domain characteristic data of economic indicators to improve the intelligence, accuracy and efficiency of the equipment in processing the time-domain characteristics of macroeconomic indicators of a specific period of time in a target area.

[0004] In a first aspect, an embodiment of the present application provides a method for processing time-domain characteristic data of economic indicators, which is applied to a terminal device, wherein the terminal device is communicatively connected to a server, and the method includes:

[0005] The trigger operation of the indicator analysis control of the economic indicator analysis function interface is detected;

[0006] In response to the triggering operation of the indicator analysis control, creating and sending an economic indicator time domain feature analysis request message carrying identification information of the target area, time period description information of the first time period, and electricity consumption indicators; and,

[0007] receiving an economic indicator time-domain characteristic analysis response message from the server, the indicator analysis response message including a first time-domain characteristic analysis result of the macroeconomic indicator of the target area in the first time period, a first correlation relationship in the first time-domain characteristic analysis result and a second correlation relationship in the second time-domain characteristic analysis result being consistent, the first correlation relationship or the second correlation relationship refers to an intrinsic correlation relationship between the macroeconomic indicator and the electricity consumption indicator, the second time-domain characteristic analysis result is a time-domain characteristic analysis result of the macroeconomic indicator of the target area in the second time period, the second time period is a historical time period that has already occurred, and the first time period is not completely the same as the second time period;

[0008] Parsing the economic indicator time domain feature analysis response message to obtain the first time domain feature analysis result;

[0009] The first time domain characteristic analysis result of the macroeconomic indicator is displayed on the economic indicator analysis function interface.

[0010] In a second aspect, an embodiment of the present application provides a device for processing time-domain characteristic data of economic indicators, which is applied to a terminal device, wherein the terminal device is communicatively connected to a server, and the device includes:

[0011] A detection unit, used to detect a triggering operation of an indicator analysis control on an economic indicator analysis function interface;

[0012] a processing unit, configured to respond to a trigger operation of the indicator analysis control, create and send an economic indicator time domain feature analysis request message carrying identification information of a target region, time period description information of a first time period, and an electricity consumption indicator; and

[0013] a receiving unit, configured to receive an economic indicator time-domain characteristic analysis response message from the server, the indicator analysis response message including a first time-domain characteristic analysis result of the macroeconomic indicator of the target area in the first time period, a first correlation relationship existing in the first time-domain characteristic analysis result and a second correlation relationship existing in the second time-domain characteristic analysis result being consistent, the first correlation relationship or the second correlation relationship refers to an intrinsic correlation relationship between the macroeconomic indicator and the electricity consumption indicator, the second time-domain characteristic analysis result is a time-domain characteristic analysis result of the macroeconomic indicator of the target area in the second time period, the second time period is a historical time period that has already occurred, and the first time period is not completely the same as the second time period;

[0014] A parsing unit, configured to parse the economic indicator time domain feature analysis response message to obtain the first time domain feature analysis result;

[0015] A display unit is used to display the first time domain characteristic analysis result of the macroeconomic indicator on the economic indicator analysis function interface.

[0016] In a third aspect, an embodiment of the present application provides an electronic device, comprising a processor and a memory storing execution instructions, wherein the memory stores one or more programs; when the processor executes the execution instructions stored in the memory, the processor executes the method described in the first aspect.

[0017] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium storing an energy data management program, including execution instructions. When a processor of an electronic device executes the execution instructions, the processor executes the method described in the first aspect.

[0018] In a fifth aspect, an embodiment of the present application provides a computer program product, wherein the computer program product includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute some or all of the steps described in the first aspect of the embodiment of the present application. The computer program product may be a software installation package.

[0019] It can be seen that in the embodiment of the present application, first, a trigger operation of the indicator analysis control for the economic indicator analysis function interface is detected; then, in response to the trigger operation of the indicator analysis control, an economic indicator time domain feature analysis request message carrying the identification information of the target area, the time period description information of the first time period and the electricity consumption index is created and sent; and an economic indicator time domain feature analysis response message is received from the server, the indicator analysis response message includes the first time domain feature analysis result of the macroeconomic indicator of the target area in the first time period, the first association relationship existing in the first time domain feature analysis result is consistent with the second association relationship existing in the second time domain feature analysis result, the first association relationship or the second association relationship refers to the intrinsic association relationship between the macroeconomic indicator and the electricity consumption index, the second time domain feature analysis result is the time domain feature analysis result of the macroeconomic indicator of the target area in the second time period, the second time period is a historical period that has occurred, and the first time period is not exactly the same as the second time period; then, the economic indicator time domain feature analysis response message is parsed to obtain the first time domain feature analysis result; finally, the first time domain feature analysis result of the macroeconomic indicator is displayed on the economic indicator analysis function interface.

[0020] The present application proposes a function based on automatic analysis of the time domain characteristics of the macroeconomic indicators of the target area during a specific period of time by a device, and based on the consistency of the intrinsic correlation between the macroeconomic indicators of the target area and the electricity consumption index data in different time periods, it realizes the more efficient and accurate creation of the time domain characteristics of the macroeconomic indicators of the target area, thereby improving the intelligence, accuracy and efficiency of the device in processing the time domain characteristics of the macroeconomic indicators of the target area during a specific period of time. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0022] Figure 1 is a system architecture diagram of a data processing system provided by an embodiment of the present application;

[0023] Figure 2 It is a flowchart of a method for processing time-domain characteristic data of economic indicators provided in an embodiment of the present application;

[0024] Figure 3 It is a schematic diagram of an economic indicator analysis function interface provided in an embodiment of the present application;

[0025] Figure 4 is a schematic diagram of a power analysis interface provided in an embodiment of the present application;

[0026] Figure 5 This is a block diagram of the functional units of a device for processing time-domain characteristic data of economic indicators provided in an embodiment of the present application;

[0027] Figure 6 This is a block diagram of the functional units of another device for processing time-domain characteristic data of economic indicators provided in an embodiment of the present application;

[0028] Figure 7 It is a structural schematic diagram of an electronic device proposed in an embodiment of the present application. DETAILED DESCRIPTION

[0029] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0030] The terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0031] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0032] The current method of analyzing the time domain characteristics of the macroeconomy mainly relies on macroeconomic statistical data and questionnaire surveys, which have problems such as high data acquisition cost, slow update speed, and poor timeliness.

[0033] In view of the above problems, an embodiment of the present application provides a method and a related device for processing time-domain characteristic data of economic indicators. The embodiment of the present application is described in detail below in conjunction with the accompanying drawings.

[0034] See also Figure 1 , Figure 1 1 is a system architecture diagram of a data processing system provided by an embodiment of the present application. Figure 1 As shown, the data processing system 100 includes a terminal device 101 and a server 102. The terminal device 101 can communicate with the server 102 through a network or other connection methods. The terminal device 101 refers to a device used by a user. The user can send a data analysis request message to the server 102 through a control in an application interface installed on the terminal device 101 to determine the time domain characteristics of economic activities. The terminal device 101 may include a tablet computer, a PDA, a vehicle-mounted electronic device, a server, a laptop computer, a mobile Internet electronic device (MID, Mobile Internet Devices) or a wearable electronic device (such as a smart watch, a Bluetooth headset), a smart phone (such as an Android phone, an iOS phone, a Windows Phone phone, etc.), etc. The above is only an example, not an exhaustive list, including but not limited to the above electronic devices. The server 102 obtains the time domain characteristic analysis results of the economic activities according to the target area, target time period and electricity consumption index determined by the user through the received request message, and sends a response message carrying the time domain characteristic analysis results to the terminal device 101, so that the terminal device 101 parses the response message and displays the time domain characteristic analysis results in the application interface.

[0035] See also Figure 2 , Figure 2 The present invention provides a flowchart of a method for processing time-domain characteristic data of economic indicators, which is applied to a terminal device, and the terminal device is connected to a server for communication. The method includes the following steps.

[0036] S210, detecting a triggering operation of an indicator analysis control of an economic indicator analysis function interface.

[0037] Specifically, before the triggering operation of the indicator analysis control for the economic indicator analysis function interface is detected, the method also includes: displaying the economic indicator analysis function interface, the economic indicator analysis function interface including a region selection partition, a key indicator parameter selection partition and an economic cycle characteristic analysis control; after the triggering operation of the indicator analysis control for the economic indicator analysis function interface is detected, the method also includes: obtaining identification information of the target region entered by the user through the region selection partition, and obtaining the electricity consumption indicator entered by the user through the key indicator parameter selection partition.

[0038] Among them, see Figure 3 , Figure 3is a schematic diagram of an economic indicator analysis function interface provided in an embodiment of the present application, such as Figure 3 As shown, the economic indicator analysis function interface includes a region selection partition, a time period selection partition, a key indicator parameter selection partition, a power analysis control, and an economic cycle characteristic analysis control. Among them, the user selects the region, time period, etc. by clicking the small triangle behind each partition. Among them, the region selection partition is used to indicate the geographical location information of electricity consumption to determine the location distribution of electricity consumption, and the time period selection partition is used to indicate the time information of electricity consumption, including the daily, weekly, monthly or annual electricity consumption time distribution. Exemplarily, click on the region selection partition, and a drop-down list appears, including multiple regions arranged in order, such as Beijing, Tianjin, Hebei Province, Shanxi Province, Inner Mongolia Autonomous Region, Liaoning Province, etc. Further, specific regions of each province can also be selected. For example, click on Shanxi Province, Taiyuan City, Datong City, Yangquan City, Changzhi City, etc. will appear. Continue to click on the city level, and the next level of regions will appear, and the target region will be determined in turn. Among them, the identification information of the target region can be an administrative division code, a full name or abbreviation of a place name, geographic coordinates, etc.

[0039] Among them, the time period selection partition can be a past period, a current period, or a future period, but there are certain time period restrictions for the future period, and only a short-term time domain feature prediction can be performed. Among them, the key indicator parameter selection partition is used to determine the power consumption index, which can be power consumption, power load, per capita power consumption and other indicators.

[0040] If the power analysis control is clicked, the power analysis interface is displayed. The power analysis interface is used to predict the user's power consumption and provide feedback information for the first time domain feature analysis result. Specifically, the economic indicator analysis function interface includes an electric power analysis control, and after the first time domain characteristic analysis result of the macroeconomic indicator is displayed on the economic indicator analysis function interface, the method also includes: detecting a trigger operation of the electric power analysis control, displaying an electric power analysis interface, the electric power analysis interface including a screening partition for electric power data, a display partition for electric power data, a verification control and an abnormality detection control; detecting a trigger operation for the verification control of the electric power analysis interface; acquiring target electric power data displayed in the display partition for electric power data, the target electric power data being obtained after the user enters the electric power data time period, the electric power data category and the electric power data region through the screening partition for electric power data; in response to the trigger operation of the verification control, creating and sending a verification request message carrying the target electric power data and the first time domain characteristic analysis result; and receiving a verification response message from the server, the verification response message including a verification result, the verification result being used to indicate the accuracy of the first time domain characteristic analysis result; parsing the verification response message to obtain the verification result; and displaying the verification result on the electric power analysis interface.

[0041] Among them, see Figure 4 , Figure 4 is a schematic diagram of a power analysis interface provided by an embodiment of the present application, such as Figure 4 As shown, the power analysis interface includes a filtering partition for power consumption data, a display partition for power consumption data, a verification control, and anomaly detection controls, wherein the filtering partition for power consumption data includes filtering in multiple dimensions, such as time period filtering, region filtering, data category filtering, etc. Specifically, the time period filtering, region filtering, and data category filtering are respectively consistent with the time period, target region, and power consumption indicator determined in the above-mentioned economic indicator analysis function interface.

[0042] The display area of ​​the power consumption data is a display area of ​​the data, which can be a text description, a chart analysis, or a display of specific data features. After filtering the power consumption data in the filtering area of ​​the power consumption data, the target power consumption data obtained is displayed in the display area of ​​the power consumption data.

[0043] Among them, according to the user clicking the verification control, a verification request is sent to the server. After receiving the message, the server cleans, filters, converts and normalizes the acquired target electricity consumption data, and uses deep learning technology to predict the pre-processed electricity consumption data to obtain predicted electricity consumption data. According to the intrinsic correlation between electricity consumption indicators and macroeconomic indicators, it is determined whether the predicted electricity consumption data and the first time domain feature analysis results conform to the intrinsic correlation. If the conformity is high, the corresponding first time domain feature analysis results have high accuracy, otherwise, the opposite is true.

[0044] Among them, it is also possible to formulate corresponding power consumption optimization strategies based on the predicted power consumption data, provide personalized decision-making suggestions and recommendations to decision makers, and help them better formulate and adjust policies and strategies. Furthermore, user needs can be considered when generating suggestions. It is also possible to track and evaluate the implementation process of decision-making suggestions and provide timely feedback on decision-making effects.

[0045] It can be seen that in this embodiment, the first time domain feature analysis result is verified by the predicted power consumption data to ensure the accuracy of the first time domain feature analysis result.

[0046] Specifically, after the verification result is displayed on the power analysis interface, the method also includes: detecting a trigger operation of the abnormality detection control; in response to the trigger operation of the abnormality detection control, creating and sending an abnormality detection request message carrying the verification result, the target power consumption data and the first time domain feature analysis result; and receiving an abnormality detection response message from the server, the abnormality detection response message including an abnormality detection result, the abnormality detection result is used to indicate the presence of outlier data in the target power consumption data, and the abnormality detection result includes an analysis result for the outlier data; parsing the abnormality detection response message to obtain the abnormality detection result; and displaying the abnormality detection result on the power analysis interface.

[0047] Among them, when the user clicks the anomaly detection control, an anomaly detection request is sent to the server. After receiving the message, the server first determines whether the first time domain feature analysis result is reliable based on the verification result. When the accuracy of the first time domain feature analysis result meets the preset threshold, that is, when the first time domain feature analysis result is reliable, the anomaly detection technology is used to find data points in the power consumption data that do not meet the first time domain feature analysis result, and determine them as outliers; when the accuracy of the first time domain feature analysis result does not meet the preset threshold, that is, when the first time domain feature analysis result is unreliable, a time series graph or a scatter plot is drawn to intuitively display the changing trend of the power consumption data and the location of the outliers. Furthermore, the identified outliers can be further analyzed and evaluated in combination with industry knowledge and experience to confirm whether they are indeed abnormal, so as to identify abnormal changes or potential risks in economic activities.

[0048] It can be seen that in this embodiment, abnormal changes in economic activities or potential risks are identified through anomaly detection of electricity consumption data, so that countermeasures can be formulated in a timely manner.

[0049] S220, in response to the triggering operation of the indicator analysis control, creating and sending an economic indicator time domain feature analysis request message carrying identification information of the target area, time period description information of the first time period, and electricity consumption indicators.

[0050] Among them, according to the user clicking the indicator analysis control in the economic indicator analysis function interface, the terminal device sends an economic indicator time domain feature analysis request message to the server. Among them, the time period description information of the first time period is used to clarify the activities or tasks allowed in a specific time period, as well as the nature and purpose of these activities or tasks, including time range, activity content, applicable objects and restrictions. Among them, electricity consumption indicators include but are not limited to per capita electricity consumption, construction land, building area, industrial production, educational facilities and safety standards.

[0051] S230, receiving an economic indicator time-domain characteristic analysis response message from the server, wherein the indicator analysis response message includes a first time-domain characteristic analysis result of the macroeconomic indicator of the target area in the first time period.

[0052] Among them, the first correlation relationship in the first time domain feature analysis result is consistent with the second correlation relationship in the second time domain feature analysis result, the first correlation relationship or the second correlation relationship refers to the intrinsic correlation between the macroeconomic indicator and the electricity consumption indicator, the second time domain feature analysis result is the time domain feature analysis result of the macroeconomic indicator of the target area in the second time period, the second time period is a historical period that has already occurred, and the first time period is not exactly the same as the second time period.

[0053] Specifically, the process of determining the first time domain feature analysis result includes the following steps: obtaining electricity consumption index data corresponding to the electricity consumption index based on the identification information of the target area and the time period description information of the first time period; performing target operations on the electricity consumption index data to obtain electricity consumption feature data, and the target operations include preprocessing operations and feature engineering operations; determining a first correlation relationship between the electricity consumption feature data and the macroeconomic indicator; and analyzing the changing trend of the macroeconomic indicator based on the first correlation relationship to obtain the first time domain feature analysis result.

[0054] Among them, the power consumption index data of the area is obtained according to the target area and time determined by the user. For example, if the power consumption index is power consumption and the time range is from 9:00 on June 28 to 16:00 on June 29, it can be retrieved from the database including power consumption data of various regions, industries and individual users at various times. Specifically, the power consumption index data may include data such as power consumption, power load, and per capita power consumption. Macroeconomic indicators include gross domestic product (GDP), consumer price index (CPI), and producer price index (PPI).

[0055] Specifically, the process of determining the electricity consumption characteristic data includes the following steps: performing preprocessing operations on the electricity consumption index data to obtain preprocessed reference data; performing feature extraction on the preprocessed reference data to obtain multiple reference features, and determining the correlation between each reference feature in the multiple reference features and a target variable, wherein the target variable is used to indicate a key performance indicator or result variable in an economic activity; screening the multiple reference features according to the correlation between each reference feature and the target variable to obtain multiple target features; constructing new features according to the target variable to obtain multiple cross features, wherein the cross features are used to indicate the combined features of any target features in the multiple target features; performing feature conversion processing, feature dimensionality reduction processing and feature encoding processing on the multiple target features and the multiple cross features in turn to obtain the electricity consumption characteristic data.

[0056] Among them, the electricity consumption index data is cleaned, screened, converted and normalized to obtain preprocessed reference data. The most representative and predictive features can be selected from the preprocessed reference data. Specifically, by calculating the correlation between the features and the target variables, the chi-square test is used to select the features with significant influence. The target variable can be the specific conditions and characteristics of economic activities in the target period, such as production, consumption, investment and other aspects. Then, according to the features of the reference data and the target variable, new features are created, and the combination of different features is considered to capture more information in the data or better relate to the target, and multiple target features are obtained. The multiple target features include the obtained cross features and multiple reference features.

[0057] Among them, feature conversion processing is used to convert the original features, feature dimensionality reduction processing is used to reduce the dimension of the power data feature space, and feature encoding processing is used to unify the form of processing data. Specifically, multiple target features are converted, that is, the features of skewed distribution are converted, such as using logarithmic transformation or Box-Cox transformation to make it closer to normal distribution, and then the high-dimensional feature space can be converted into a low-dimensional feature space using dimensionality reduction techniques such as principal component analysis PCA, retaining the most important feature information, and finally converting the non-numerical features in the final feature information into a numerical form that can be processed by the model, converting the non-numerical features into a numerical form that can be processed by the model, performing one-hot encoding or label encoding on the categorical variables, converting them into binary vectors or integer encoding, and obtaining the power consumption feature data.

[0058] Among them, the correlation between electricity consumption characteristic data and macroeconomic indicators is studied through data mining and statistical analysis technology. Specifically, the Pearson correlation coefficient or data mining technology is used to study the correlation between them, and statistical analysis is performed to explore the correlation between different macroeconomic indicators and the degree of influence of macroeconomic indicators on electricity consumption characteristic data, and the first correlation is obtained. Specifically, the first correlation and the second correlation are consistent to indicate that there is an inherent stable correlation between macroeconomic indicators and electricity consumption indicators. For example, the increase in economic activities is usually accompanied by the increase in energy consumption, especially electricity consumption. Therefore, by analyzing the changing trend of electricity consumption data, since electricity consumption data usually has higher real-time and sensitivity, it can indirectly reflect the fluctuation of economic activities. And electricity consumption data in different time periods, such as quarters and years, often show a certain periodicity and regularity, which is consistent with the periodicity of economic activities. By analyzing the electricity consumption data in these time periods, the time domain characteristics of economic activities can be revealed, that is, the performance and changing laws of economic activities at different time points.

[0059] Furthermore, a mapping model can be constructed based on the correlation between electricity consumption indicators and macroeconomic indicators. Specifically, a linear regression modeling method can be selected, and the selected model can be applied to the relationship between electricity consumption data and macroeconomic indicators to establish a mapping model. Among them, the mapping model can capture the specific relationship between electricity data and macroeconomic indicators. This data mining-based analysis ensures that the mapping model can reflect the true correlation between electricity use and macroeconomic activities, so that the model can learn the mapping relationship between the two based on historical data and predict future macroeconomic indicators. Among them, the linear regression method is selected to establish the model, and the accuracy of the model is optimized by minimizing the error between the predicted value and the actual value, so as to provide good prediction capabilities under reasonable assumptions. The mapping model can be continuously updated with the input of new electricity data and economic indicators, thereby maintaining the accuracy and timeliness of its prediction. By analyzing the relationship between multiple macroeconomic indicators and electricity data, the model can integrate information from various aspects and construct a more comprehensive economic indicator mapping. This helps to better understand the comprehensive impact of different economic activities on electricity consumption. Furthermore, the accuracy, stability and reliability of the mapping model can be evaluated through model evaluation and verification techniques, and the accuracy of the mapping model can be evaluated using the model evaluation indicator mean square error.

[0060] Among them, time series analysis methods can be used to conduct trend analysis, seasonal analysis and cycle analysis on macroeconomic indicators and electricity consumption index data based on correlation relationships; further, the different stages of the economic cycle can be identified based on the cyclical characteristics of macroeconomic indicators and the changing trend of electricity consumption index data, and the turning points and phased changes in the economic cycle can be found by using time series analysis methods and turning point identification technology. Furthermore, it is also possible to predict and model the relevant data of the power system based on the turning points and phased changes in the economic cycle based on deep learning technology, and analyze the causal relationship between the power market and the macroeconomy. Furthermore, it is also possible to use machine learning, statistical analysis and other methods based on power big data and other related data to predict future economic trends, so as to provide personalized decision-making suggestions and recommendations to decision makers, so as to better formulate and adjust policies and strategies.

[0061] S240, parsing the economic indicator time domain feature analysis response message to obtain the first time domain feature analysis result.

[0062] The terminal device parses the economic indicator time domain feature analysis response message sent by the server to obtain the first time domain feature analysis result in the response message. The first time domain feature analysis result can be the change pattern of the macroeconomic indicator in the first time period, such as the turning point and phased change of at least one economic cycle in the first time period.

[0063] S250, displaying the first time domain characteristic analysis result of the macroeconomic indicator on the economic indicator analysis function interface.

[0064] Among them, when the first time domain characteristic analysis result is obtained, a result display window can be popped up in the economic indicator analysis function interface, and the first time domain characteristic analysis result can be displayed in the result display window. Specifically, the first time domain characteristic analysis result can be presented in the form of a chart, report or numerical value, which is used to intuitively display the time domain change characteristics of the economic indicator and its relationship with the electricity consumption data. Furthermore, the first time domain characteristic analysis result can also be summarized and described in text in the result display window. For example, it can be that the industrial production activities in Datong City, Shanxi Province in the first quarter of 2024 have made an important contribution to the growth of GDP, and this impact remains stable in different time periods.

[0065] It can be seen that in the embodiment of the present application, a function is proposed based on the automatic analysis of the time domain characteristics of the macroeconomic indicators of the target area in a specific period of time by the device, and based on the consistency of the intrinsic correlation between the macroeconomic indicators of the target area and the electricity consumption index data in different time periods, a more efficient and accurate creation of the time domain characteristics of the macroeconomic indicators of the target area is achieved, thereby improving the intelligence, accuracy and efficiency of the device in processing the time domain characteristics of the macroeconomic indicators of the target area in a specific period of time.

[0066] For the above embodiments, please refer to Figure 5 , Figure 5 is a block diagram of the functional units of a device for processing time-domain characteristic data of economic indicators provided by an embodiment of the present application, such as Figure 5As shown, the processing device 50 of economic indicator time-domain characteristic data includes: a detection unit 51, which is used to detect the trigger operation of the indicator analysis control for the economic indicator analysis function interface; a processing unit 52, which is used to respond to the trigger operation of the indicator analysis control, create and send an economic indicator time-domain characteristic analysis request message carrying the identification information of the target area, the time period description information of the first time period and the electricity consumption index; and a receiving unit 53, which is used to receive the economic indicator time-domain characteristic analysis response message from the server, the indicator analysis response message including the first time-domain characteristic analysis result of the macroeconomic indicator of the target area in the first time period, the first correlation existing in the first time-domain characteristic analysis result The first correlation relationship or the second correlation relationship refers to the intrinsic correlation between the macroeconomic indicator and the electricity consumption indicator. The second time domain characteristic analysis result is the time domain characteristic analysis result of the macroeconomic indicator of the target area in the second time period. The second time period is a historical period that has already occurred. The first time period is not exactly the same as the second time period. The parsing unit 54 is used to parse the economic indicator time domain characteristic analysis response message to obtain the first time domain characteristic analysis result. The display unit 55 is used to display the first time domain characteristic analysis result of the macroeconomic indicator in the economic indicator analysis function interface.

[0067] Among them, the process of determining the first time domain feature analysis result includes the following steps: obtaining electricity consumption index data corresponding to the electricity consumption index according to the identification information of the target area and the time period description information of the first time period; performing target operations on the electricity consumption index data to obtain electricity consumption feature data, and the target operations include preprocessing operations and feature engineering operations; determining a first correlation relationship between the electricity consumption feature data and the macroeconomic indicator; analyzing the changing trend of the macroeconomic indicator according to the first correlation relationship to obtain the first time domain feature analysis result.

[0068] Among them, the process of determining the electricity consumption characteristic data includes the following steps: performing preprocessing operations on the electricity consumption index data to obtain preprocessed reference data; performing feature extraction on the preprocessed reference data to obtain multiple reference features, and determining the correlation between each reference feature in the multiple reference features and the target variable, and the target variable is used to indicate the key performance indicators or result variables in economic activities; screening the multiple reference features according to the correlation between each reference feature and the target variable to obtain multiple target features; constructing new features according to the target variable to obtain multiple cross features, and the cross features are used to indicate the combined features of any target features in the multiple target features; performing feature conversion processing, feature dimensionality reduction processing and feature encoding processing on the multiple target features and the multiple cross features in turn to obtain the electricity consumption characteristic data.

[0069] The first time domain feature analysis result includes at least one of the following: a trend analysis result, a seasonal analysis result, and a cycle analysis result.

[0070] In a possible embodiment, the economic indicator analysis function interface also includes an electric power analysis control. After the economic indicator analysis function interface displays the first time domain characteristic analysis result of the macroeconomic indicator, the processing device 50 of the economic indicator time domain characteristic data is specifically used to: detect the trigger operation of the electric power analysis control, display the electric power analysis interface, the electric power analysis interface includes a screening partition for electric power data, a display partition for electric power data, a verification control and an abnormality detection control; detect the trigger operation of the verification control for the electric power analysis interface; obtain the target electric power data displayed in the display partition of the electric power data, the target electric power data is obtained after the user enters the electric power data time period, the electric power data category and the electric power data area through the screening partition of the electric power data; in response to the trigger operation of the verification control, create and send a verification request message carrying the target electric power data and the first time domain characteristic analysis result; and receive a verification response message from the server, the verification response message including a verification result, the verification result is used to indicate the accuracy of the first time domain characteristic analysis result; parse the verification response message to obtain the verification result; and display the verification result on the electric power analysis interface.

[0071] In a possible embodiment, after the verification result is displayed on the power analysis interface, the processing device 50 of the economic indicator time domain characteristic data is specifically used to: detect the triggering operation of the abnormality detection control; in response to the triggering operation of the abnormality detection control, create and send an abnormality detection request message carrying the verification result, the target power consumption data and the first time domain characteristic analysis result; and receive an abnormality detection response message from the server, the abnormality detection response message including an abnormality detection result, the abnormality detection result is used to indicate the presence of outlier data in the target power consumption data, and the abnormality detection result includes an analysis result for the outlier data; parse the abnormality detection response message to obtain the abnormality detection result; and display the abnormality detection result on the power analysis interface.

[0072] In a possible embodiment, before detecting the triggering operation of the indicator analysis control for the economic indicator analysis function interface, the processing device 50 for the economic indicator time-domain characteristic data is also specifically used to: display the economic indicator analysis function interface, and the economic indicator analysis function interface includes a region selection partition, a key indicator parameter selection partition and an economic cycle characteristic analysis control; after detecting the triggering operation of the indicator analysis control for the economic indicator analysis function interface, the processing device 50 for the economic indicator time-domain characteristic data is also specifically used to: obtain the identification information of the target region entered by the user through the region selection partition, and obtain the electricity consumption indicator entered by the user through the key indicator parameter selection partition.

[0073] It can be understood that since the method embodiment and the device embodiment are different presentation forms of the same technical concept, the content of the method embodiment part in this application should be synchronously adapted to the device embodiment part and will not be repeated here.

[0074] In the case of integrated units, see Figure 6 , Figure 6 is a block diagram of the functional units of another device for processing time-domain characteristic data of economic indicators provided by an embodiment of the present application, such as Figure 6 As shown, the processing device 50 for economic indicator time domain characteristic data includes: a processing module 502 and a communication module 501. The processing module 502 is used to control and manage the actions of the processing device 50 for economic indicator time domain characteristic data, for example, to execute the steps of the detection unit 51, the processing unit 52, the receiving unit 53, the parsing unit 54 and the display unit 55, and / or to execute other processes of the technology described herein. The communication module 501 is used for the interaction between the processing device 50 for economic indicator time domain characteristic data and other devices. Figure 6 As shown, the processing device 50 for economic indicator time-domain characteristic data may further include a storage module 503, and the storage module 503 is used to store program codes and data of the processing device 50 for economic indicator time-domain characteristic data.

[0075] Wherein, the processing module 502 can be a processor or a controller, for example, a central processing unit (CPU), a general processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It can implement or execute various exemplary logic boxes, modules and circuits described in conjunction with the disclosure of the present application. The processor can also be a combination that implements a computing function, for example, a combination of one or more microprocessors, a combination of a DSP and a microprocessor, and the like. The communication module 501 can be a transceiver, an RF circuit or a communication interface, and the like. The storage module 503 can be a memory.

[0076] All relevant contents of each scenario involved in the above method embodiment can be referred to the functional description of the corresponding functional module, which will not be repeated here. The processing device 50 for the time domain characteristic data of the economic indicator can execute the above Figure 2 The processing method of time domain characteristic data of economic indicators shown.

[0077] See also Figure 7 , Figure 7 is a schematic diagram of the structure of an electronic device proposed in an embodiment of the present application, such as Figure 7 As shown, the electronic device 70 includes a processor 710, a memory 720, a communication interface 730 and one or more programs 721. The one or more programs 721 are stored in the memory and are configured to be executed by the processor. When the program is executed, it includes part or all of the steps of any method for processing time domain characteristic data of economic indicators recorded in the above method embodiments. The processor, memory and communication interface are interconnected and complete communication with each other.

[0078] The memory may be a volatile memory such as a dynamic random access memory (DRAM), or a non-volatile memory such as a mechanical hard disk. The memory is used to store a set of executable program codes, and the processor is used to call the executable program codes stored in the memory, and may execute part or all of the steps of any method for processing time-domain characteristic data of economic indicators as described in the embodiment of the method for processing time-domain characteristic data of economic indicators.

[0079] It can be seen that the electronic device 70 described in the embodiment of the present application first detects a trigger operation of the indicator analysis control for the economic indicator analysis function interface; then responds to the trigger operation of the indicator analysis control, creates and sends an economic indicator time domain feature analysis request message carrying the identification information of the target area, the time period description information of the first time period and the electricity consumption indicator; and receives an economic indicator time domain feature analysis response message from the server, the indicator analysis response message includes a first time domain feature analysis result of the macroeconomic indicator of the target area in the first time period, the first association relationship existing in the first time domain feature analysis result is consistent with the second association relationship existing in the second time domain feature analysis result, the first association relationship or the second association relationship refers to the intrinsic association relationship between the macroeconomic indicator and the electricity consumption indicator, the second time domain feature analysis result is the time domain feature analysis result of the macroeconomic indicator of the target area in the second time period, the second time period is a historical period that has occurred, and the first time period is not exactly the same as the second time period; then parses the economic indicator time domain feature analysis response message to obtain the first time domain feature analysis result; finally, displays the first time domain feature analysis result of the macroeconomic indicator on the economic indicator analysis function interface. The present application proposes a function based on automatic analysis of the time domain characteristics of the macroeconomic indicators of the target area during a specific period of time by a device, and based on the consistency of the intrinsic correlation between the macroeconomic indicators of the target area and the electricity consumption index data in different time periods, it realizes the more efficient and accurate creation of the time domain characteristics of the macroeconomic indicators of the target area, thereby improving the intelligence, accuracy and efficiency of the device in processing the time domain characteristics of the macroeconomic indicators of the target area during a specific period of time.

[0080] An embodiment of the present application also provides a computer storage medium, wherein the computer storage medium stores a computer program for electronic data exchange, wherein the computer program enables a computer to execute part or all of the steps of any method described in the above method embodiments, and the above computer includes an electronic device.

[0081] The embodiment of the present application also provides a computer program product, the computer program product includes a non-transitory computer-readable storage medium storing a computer program, the computer program is operable to cause a computer to execute some or all of the steps of any method described in the method embodiment. The computer program product may be a software installation package, and the computer includes an electronic device.

[0082] It should be noted that, for the sake of simplicity, the aforementioned method implementations are all described as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the implementations described in the specification are all optional implementations, and the actions and modules involved are not necessarily required by the present application.

[0083] In the above-mentioned embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0084] In the several embodiments provided in this application, it should be understood that the disclosed device can be implemented in other ways. For example, the device implementation described above is only schematic, such as the division of the units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the device or unit can be electrical or other forms.

[0085] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0086] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above integrated unit may be implemented in the form of hardware or in the form of a software program module.

[0087] If the integrated unit is implemented in the form of a software program module and sold or used as an independent product, it can be stored in a computer-readable memory. According to this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a memory, including a number of instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned memory includes: U disk, read-only memory (ROM), random access memory (RAM), mobile hard disk, disk or optical disk and other media that can store program codes.

[0088] A person of ordinary skill in the art can understand that all or part of the steps in the various methods of the above-mentioned embodiments can be completed by instructing the relevant hardware through a program, and the program can be stored in a computer-readable memory, which can include: a flash drive, a read-only memory, a random access memory, a magnetic disk or an optical disk, etc.

[0089] The above is a detailed introduction to the implementation methods of the present application. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above implementation methods is only used to help understand the method and core idea of ​​the present application. At the same time, for general technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A method for processing time-domain characteristic data of economic indicators, characterized in that: Applied to a terminal device, the terminal device is communicatively connected with a server, and the method comprises: The trigger operation of the indicator analysis control of the economic indicator analysis function interface is detected; In response to the triggering operation of the indicator analysis control, creating and sending an economic indicator time domain feature analysis request message carrying identification information of the target area, time period description information of the first time period, and electricity consumption indicators; and, receiving an economic indicator time-domain characteristic analysis response message from the server, the indicator analysis response message including a first time-domain characteristic analysis result of the macroeconomic indicator of the target area in the first time period, a first correlation relationship in the first time-domain characteristic analysis result and a second correlation relationship in the second time-domain characteristic analysis result being consistent, the first correlation relationship or the second correlation relationship refers to an intrinsic correlation relationship between the macroeconomic indicator and the electricity consumption indicator, the second time-domain characteristic analysis result is a time-domain characteristic analysis result of the macroeconomic indicator of the target area in the second time period, the second time period is a historical time period that has already occurred, and the first time period is not completely the same as the second time period; Parsing the economic indicator time domain feature analysis response message to obtain the first time domain feature analysis result; The first time domain characteristic analysis result of the macroeconomic indicator is displayed on the economic indicator analysis function interface.

2. The method according to claim 1, characterized in that The process of determining the first time domain feature analysis result comprises the following steps: Acquire power consumption index data corresponding to the power consumption index according to the identification information of the target area and the time period description information of the first time period; Performing a target operation on the electricity consumption index data to obtain electricity consumption feature data, wherein the target operation includes a preprocessing operation and a feature engineering operation; Determining a first correlation relationship between the power consumption characteristic data and the macroeconomic indicator; The changing trend of the macroeconomic indicator is analyzed according to the first correlation relationship to obtain the first time domain feature analysis result.

3. The method according to claim 1, characterized in that The economic indicator analysis function interface further includes a power analysis control. After the economic indicator analysis function interface displays the first time domain characteristic analysis result of the macroeconomic indicator, the method further includes: Detecting a triggering operation of the power analysis control, displaying a power analysis interface, the power analysis interface including a screening partition for power consumption data, a display partition for power consumption data, a verification control, and an abnormality detection control; Detecting a triggering operation of a verification control of the power analysis interface; Acquire the target power consumption data displayed in the display partition of the power consumption data, wherein the target power consumption data is obtained after the user enters the power consumption data time period, power consumption data category and power consumption data region through the screening partition of the power consumption data; In response to the triggering operation of the verification control, creating and sending a verification request message carrying the target power usage data and the first time domain feature analysis result; and, receiving a verification response message from the server, wherein the verification response message includes a verification result, and the verification result is used to indicate the accuracy of the first time domain feature analysis result; Parsing the verification response message to obtain the verification result; The verification result is displayed on the power analysis interface.

4. The method according to claim 3, characterized in that After the verification result is displayed on the power analysis interface, the method further includes: Detecting a triggering operation of the abnormality detection control; In response to the triggering operation of the anomaly detection control, creating and sending an anomaly detection request message carrying the verification result, the target power usage data and the first time domain feature analysis result; and, receiving an abnormality detection response message from the server, the abnormality detection response message including an abnormality detection result, the abnormality detection result being used to indicate that outlier data exists in the target power consumption data, and the abnormality detection result including an analysis result for the outlier data; Parsing the anomaly detection response message to obtain the anomaly detection result; The abnormality detection result is displayed on the power analysis interface.

5. The method according to claim 1, characterized in that: Before detecting a triggering operation on an indicator analysis control of an economic indicator analysis function interface, the method further includes: Display the economic indicator analysis function interface, which includes a region selection partition, a key indicator parameter selection partition, and an economic cycle characteristic analysis control; After the triggering operation of the indicator analysis control on the economic indicator analysis function interface is detected, the method further includes: The identification information of the target area entered by the user through the area selection partition is obtained, and the power consumption index entered by the user through the key index parameter selection partition is obtained.

6. The method according to claim 5, characterized in that The first time domain feature analysis result includes at least one of the following: a trend analysis result, a seasonal analysis result, and a cycle analysis result.

7. The method according to claim 2, characterized in that The process of determining the power consumption characteristic data comprises the following steps: Performing a preprocessing operation on the electricity consumption index data to obtain preprocessed reference data; Performing feature extraction on the preprocessed reference data to obtain a plurality of reference features, and determining the correlation between each of the plurality of reference features and a target variable, wherein the target variable is used to indicate a key performance indicator or an outcome variable in an economic activity; Screening the multiple reference features according to the correlation between each reference feature and the target variable to obtain multiple target features; Constructing new features according to the target variable to obtain multiple cross features, where the cross features are used to indicate a combined feature of any target features among the multiple target features; The multiple target features and the multiple cross features are sequentially subjected to feature conversion processing, feature dimension reduction processing and feature encoding processing to obtain the power consumption feature data.

8. A device for processing time-domain characteristic data of economic indicators, characterized in that: Applied to a terminal device, the terminal device is connected to a server for communication, and the device comprises: A detection unit, used to detect a triggering operation of an indicator analysis control on an economic indicator analysis function interface; a processing unit, configured to respond to a trigger operation of the indicator analysis control, create and send an economic indicator time domain feature analysis request message carrying identification information of a target region, time period description information of a first time period, and an electricity consumption indicator; and a receiving unit, configured to receive an economic indicator time-domain characteristic analysis response message from the server, the indicator analysis response message including a first time-domain characteristic analysis result of the macroeconomic indicator of the target area in the first time period, a first correlation relationship existing in the first time-domain characteristic analysis result and a second correlation relationship existing in the second time-domain characteristic analysis result being consistent, the first correlation relationship or the second correlation relationship refers to an intrinsic correlation relationship between the macroeconomic indicator and the electricity consumption indicator, the second time-domain characteristic analysis result is a time-domain characteristic analysis result of the macroeconomic indicator of the target area in the second time period, the second time period is a historical time period that has already occurred, and the first time period is not completely the same as the second time period; A parsing unit, configured to parse the economic indicator time domain feature analysis response message to obtain the first time domain feature analysis result; A display unit is used to display the first time domain characteristic analysis result of the macroeconomic indicator on the economic indicator analysis function interface.

9. An electronic device, characterized in that: The method comprises a processor and a memory storing execution instructions, wherein the memory stores one or more programs; when the processor executes the execution instructions stored in the memory, the processor executes the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: An energy data management program is stored, including execution instructions. When a processor of an electronic device executes the execution instructions, the processor executes the method according to any one of claims 1-7.

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