High-accuracy carbon emission prediction and early warning system and device

Abstract

The invention discloses a high-accuracy carbon emission prediction and early warning system and device, and relates to the technical field of carbon emission prediction and early warning systems, the high-accuracy carbon emission prediction and early warning system comprises a data collection and arrangement module and a carbon emission prediction model group, and the data collection and arrangement module is connected with the carbon emission prediction model group. According to the high-accuracy carbon emission prediction and early warning system and device, missing parts of acquired data are reasonably supplemented, data error parts are corrected in a threshold value according to rules of data types, and the context of the error parts is adapted for undertaking transition, so that missing data points and error data points do not need to be directly removed, and the accuracy of carbon emission prediction and early warning is improved. The collected data content is rich and accurate so as to improve the accuracy of subsequent prediction and early warning, the carbon emission prediction model is divided according to the industry so that each sub-model is correspondingly adapted to one specific industry, and the data participates in the transportation of each model after being subjected to sub-entry so as to improve the accuracy of subsequent prediction and early warning. Therefore, interference caused by the fact that parameters irrelevant to the industry participate in operation can be reduced, and accuracy is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of carbon emission prediction and early warning systems, and in particular to a highly accurate carbon emission prediction and early warning system and device. Background Art

[0002] Carbon emissions refer to the average greenhouse gas emissions generated during the production, transportation, use and recycling of the product. Carbon emissions is a general term or abbreviation for greenhouse gas emissions, which will have huge negative impacts. Therefore, it is necessary to monitor carbon emissions in real time and predict and warn through satellite monitoring, sensor monitoring and other methods.

[0003] The existing carbon emission forecasting and early warning system needs to collect industrial emission data, traffic data, energy consumption data and other data when forecasting and warning carbon emissions. In order to improve the accuracy of forecasting and early warning, the data will be processed to remove duplicate, missing or abnormal data points. If the data set contains a large number of missing or abnormal data points, after removing these data points, the data content will be thin, affecting the data quality and causing the final forecasting and early warning results to be inaccurate.

[0004] Therefore, in view of this, the existing structure and deficiencies are studied and improved, and a highly accurate carbon emission prediction and early warning system and device are proposed. Summary of the invention

[0005] In view of the deficiencies of the prior art, the present invention provides a highly accurate carbon emission prediction and early warning system and device, which solves the problems raised in the above-mentioned background technology.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a highly accurate carbon emission prediction and early warning system, comprising a data collection and collation module and a carbon emission prediction model group, the data collection and collation module is connected to the carbon emission prediction model group, and the carbon emission prediction model group is connected to a warning threshold setting module, the warning threshold setting module is connected to a report output module, the data collection and collation module comprises a real-time data unit, a data checking unit, a data missing unit, an incorrect data error unit, a problem processing unit, a historical data unit and a re-verification module, the real-time data unit is connected to the data checking unit, and the data checking unit is connected to the data missing unit and the incorrect data error unit, the data missing unit and the incorrect data error unit are connected to the problem processing unit, and the problem processing unit is connected to the historical data unit and the re-verification module.

[0007] Furthermore, the real-time data unit is used to collect meteorological data, industrial emission data, and energy consumption data in real time through satellite monitoring or sensor detection, and the data checking unit is used to check whether the collected data has any missing or erroneous parts, and classify the erroneous data into a data missing unit or a data error incorrect unit according to the data error type.

[0008] Furthermore, the historical data unit is used to store historical data that has been verified to be error-free and missing, and the problem processing unit is used to search for content with high similarity in the historical data based on the contextual content of the missing real-time data location, and to obtain the missing data at the missing real-time data location based on the data points in the historical data corresponding to the missing real-time data location combined with contextual analysis.

[0009] Furthermore, the problem processing unit is also used to correct the errors in the real-time data in combination with the context and the rules of the data therein within the scope allowed by the rules, and the re-verification module re-verifies the data processed by the problem processing unit.

[0010] Furthermore, the carbon emission prediction model group includes a data sub-item unit, a meteorological impact prediction model, an industrial impact prediction model and a life impact prediction model, and the data sub-item unit is connected to the meteorological impact prediction model, the industrial impact prediction model and the life impact prediction model.

[0011] Furthermore, the data sub-item unit classifies the verified data according to the types of data required by the meteorological impact prediction model, the industrial impact prediction model, and the life impact prediction model.

[0012] Furthermore, the meteorological impact prediction model is used to predict future meteorological changes based on the input data, the industrial impact prediction model is used to predict future industrial carbon emissions based on the input data, and the life impact prediction model predicts future changes in residents' life-related factors based on the input data, and residents' life-related factors include but are not limited to regional temperature and air quality.

[0013] Furthermore, the report output module includes an initial report template unit, an association unit, a report template library, a template conversion unit and a template format output unit, wherein the initial report template unit is connected to the report template library via the association unit, and the association unit is also connected to the template conversion unit, and the template conversion unit is connected to the template format output unit.

[0014] Furthermore, the initial template content of the initial report template unit contains the content of all templates in the report template library, the association unit associates the initial template format with each template format in the report template library, and the template conversion unit converts the content in the initial template based on the selected template format in the report template library to make it compatible with the selected report template format.

[0015] A carbon emission prediction and early warning device, which is applied with the above-mentioned high-accuracy carbon emission prediction and early warning system, includes a server component, the server component includes an air distribution pipe, an electronic valve, a server frame, a layer plate, an injection end, an exhaust end, a server body, a sandwich sleeve, a plug, a three-way valve, a return air pipe, an exhaust pipe and a circulation fan, the bottom of the air distribution pipe is connected to the server frame through the electronic valve, and the layer plates are equidistantly arranged inside the server frame, the server frame and the layer plates are provided with connected cavities, and the middle of the layer plate surface is sequentially provided with an injection end and an exhaust end from left to right, the injection end and the exhaust end are plugged with plugs, and the top of the plug is connected with the sandwich sleeve, the server body is arranged inside the sandwich sleeve, the top of the server frame is provided with a three-way valve on the side of the top of the server frame away from the electronic valve, and the side of the three-way valve is connected with the return air pipe, the top of the three-way valve is connected with the exhaust pipe, the circulation fan is arranged inside the server frame just below the electronic valve, and the server frame is provided with a temperature sensor.

[0016] The present invention provides a highly accurate carbon emission prediction and early warning system and device, which has the following beneficial effects:

[0017] 1. The highly accurate carbon emission prediction and early warning system and device reasonably supplements the missing parts of the collected data, corrects the data errors within the threshold according to the rules of the data type, and adapts the context transition of the errors. There is no need to directly remove missing data points and erroneous data points, so that the collected data content is substantial and accurate, so as to improve the accuracy of subsequent predictions and early warnings. The carbon emission prediction model is divided according to the industry so that each sub-model corresponds to a specific industry. The data participates in the transportation of each model after itemization, thereby reducing the interference caused by the participation of parameters unrelated to the industry in the calculation, so as to improve accuracy.

[0018] 2. This highly accurate carbon emission prediction and early warning system and device, the cold air exhausted by the central air conditioner enters the inside of one side of the server frame along the air distribution pipe, and the cold air flows along the inside of the layer plate and the interlayer sleeve to absorb the heat of the server body. Compared with air cooling and water cooling, firstly, there is no noise and the cooling effect is better, and secondly, there is no hidden danger of coolant leakage. If the temperature of the cold air after absorbing heat is still within the preset range, the cold air will be discharged to the people's activity area through the multi-way valve at the end of the exhaust pipe to avoid waste of cold air. If the temperature of the cold air after absorbing heat is higher than the threshold, it will be directly discharged through the multi-way valve.

[0019] 3. This highly accurate carbon emission prediction and early warning system and device, if the internal temperature of a server frame is significantly higher than that of other server frames, select the server frame with the lowest temperature from other server frames and temporarily close the electronic valve on its top, thereby increasing the amount of cold air inside the server frame with a higher temperature, and strengthening the cooling of the interior of the server frame with a higher temperature. After the electronic valve is closed, the circulation fan below the electronic valve is started, and at the same time, the three-way valve opens the return air duct and closes the exhaust duct. At this time, the cold air inside the server frame with a lower temperature circulates in the server frame, layer plate, interlayer sleeve, and return air duct under the guidance of the circulation fan. Therefore, when the cold air is temporarily introduced, the residual cold air circulation is used to continue to maintain the cooling and heat dissipation effect to suppress the rapid increase in the temperature of the server body with a lower temperature. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a schematic diagram of the operation flow structure of the present invention;

[0021] Figure 2 It is a schematic diagram of the server framework structure of the present invention;

[0022] Figure 3 It is a schematic diagram of the layer plate structure of the present invention;

[0023] Figure 4 It is a schematic diagram of the bottom structure of the interlayer sleeve of the present invention;

[0024] Figure 5 It is a schematic diagram of the circulation fan structure of the present invention.

[0025] In the figure: 1. Data collection and sorting module; 101. Real-time data unit; 102. Data checking unit; 103. Data missing unit; 104. Data error unit; 105. Problem handling unit; 106. Historical data unit; 107. Revalidation module; 2. Carbon emission prediction model group; 201. Data sub-item unit; 202. Meteorological impact prediction model; 203. Industrial impact prediction model; 204. Life impact prediction model; 3. Warning threshold setting module; 4. Report output module Block; 401, initial report template unit; 402, association unit; 403, report template library; 404, template conversion unit; 405, template format output unit; 5, server component; 501, gas distribution pipe; 502, electronic valve; 503, server frame; 504, shelf; 505, gas injection end; 506, exhaust end; 507, server body; 508, interlayer sleeve; 509, plug; 510, three-way valve; 511, return air pipe; 512, exhaust pipe; 513, circulation fan. DETAILED DESCRIPTION

[0026] The following embodiments of the present invention are described in further detail in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0027] like Figure 1As shown, the present invention provides a technical solution: a highly accurate carbon emission prediction and early warning system, comprising a data collection and collation module 1 and a carbon emission prediction model group 2, the data collection and collation module 1 is connected to the carbon emission prediction model group 2, and the carbon emission prediction model group 2 is connected to the early warning threshold setting module 3, the early warning threshold setting module 3 is connected to the report output module 4, the data collection and collation module 1 comprises a real-time data unit 101, a data checking unit 102, a data missing unit 103, a data error incorrect unit 104, a problem processing unit 105, a historical data unit 106 and a re-verification module 107, the real-time data unit 101 is connected to the data checking unit 102, and the data checking unit 102 is connected to the data missing unit 103, The data error incorrect unit 104, the data missing unit 103, and the data error incorrect unit 104 are connected to the problem processing unit 105, and the problem processing unit 105 is connected to the historical data unit 106 and the re-verification module 107. The real-time data unit 101 is used to collect meteorological data, industrial emission data, and energy consumption data in real time through satellite monitoring or sensor detection. The data inspection unit 102 is used to check whether the collected data has missing or errors, and classify the erroneous data into the data missing unit 103 or the data error incorrect unit 104 according to the data error type. The historical data unit 106 is used to store historical data that has been verified to have no errors or missing. The problem processing unit 105 is used to The context content searches for highly similar content in historical data, and obtains the missing data at the missing real-time data location according to the data points in the historical data corresponding to the missing real-time data location combined with the context analysis. The problem processing unit 105 is also used to correct the error in the real-time data in combination with the context and the rules of the data at that location within the rules allowed. The re-verification module 107 re-verifies the data processed by the problem processing unit 105. The carbon emission prediction model group 2 includes a data sub-item unit 201, a meteorological impact prediction model 202, an industrial impact prediction model 203 and a life impact prediction model 204. The data sub-item unit 201 is connected to the meteorological impact prediction model 202, the industrial impact prediction model 203, and the life impact prediction model 204. 04, the data sub-item unit 201 classifies the verified data according to the data types required by the meteorological impact prediction model 202, the industrial impact prediction model 203, and the life impact prediction model 204. The meteorological impact prediction model 202 is used to predict future meteorological changes based on the input data, the industrial impact prediction model 203 is used to predict future industrial carbon emissions based on the input data, and the life impact prediction model 204 predicts future changes in residents' life-related factors based on the input data, and the residents' life-related factors include but are not limited to regional temperature and air quality. The report output module 4 includes an initial report template unit 401, an association unit 402, a report template library 403, a template conversion unit 404 and a template format output unit 405.The initial report template unit 401 is connected to the report template library 403 through the association unit 402, and the association unit 402 is also connected to the template conversion unit 404, the template conversion unit 404 is connected to the template format output unit 405, the initial template content of the initial report template unit 401 contains the content of all templates in the report template library 403, the association unit 402 associates the initial template format with each template format in the report template library 403, and the template conversion unit 404 converts the content in the initial template based on the selected template format in the report template library 403 to make it compatible with the selected report template format;

[0028] The specific operation is as follows: the real-time data unit 101 obtains real-time data by satellite monitoring, sensor detection, etc. The real-time data includes meteorological data, industrial emission data, energy consumption data, etc., and the data inspection unit 102 checks whether the collected data has missing or erroneous parts, and classifies the erroneous data into the data missing unit 103 or the data error incorrect unit 104 according to the data error type;

[0029] The problem processing unit 105 searches for highly similar content in the historical data based on the context content at the missing real-time data location, and performs context analysis based on the data points in the historical data corresponding to the missing real-time data location to obtain the missing data at the missing real-time data location. The problem processing unit 105 also corrects the error in the real-time data based on the context and the rules of the data at that location within the scope allowed by the rules, wherein the specific rules are as follows: Taking the date as an example, the whole year is divided into twelve months, and the number of days in each month is fixed. If the date above is August 15, 2024, and the date below is August 18, 2024, according to the context and date rules, the date in the middle is 1 If the data is on the 9th, then the date is definitely wrong and needs to be corrected. The 16th or 17th can be selected as the corrected data. The same is true for other data. If the data obviously exceeds the threshold according to the data rule, it means that the data error needs to be corrected. The corrected data is within the threshold and conforms to the transition of the context data. By reasonably supplementing the missing parts of the collected data, and correcting the data errors within the threshold according to the rules of the data type and adapting to the transition of the context of the errors, there is no need to directly remove the missing data points and the wrong data points, so that the collected data content is substantial and accurate, so as to improve the accuracy of subsequent prediction and warning;

[0030] The re-verification module 107 re-verifies the data processed by the problem processing unit 105, so that the processed data is re-detected for problems to prevent problems from being missed. The data that pass the detection enters the data sub-item unit 201, and the data sub-item unit 201 classifies the received data according to the various required data types of the meteorological impact prediction model 202, the industrial impact prediction model 203, and the life impact prediction model 204. One type of data can be classified and participate in the operation of the three models at the same time. The meteorological impact prediction model 202 predicts future meteorological changes based on the input data, and the industrial impact prediction model 203 predicts future meteorological changes based on the input data. According to the input data, future industrial carbon emissions and temperature changes are predicted. The life impact prediction model 204 predicts the changes in residents' life-related factors in the future according to the input data. The residents' life-related factors include but are not limited to regional temperature, air quality, and rainwater acidity content. Therefore, various industries closely related to carbon emissions can quickly predict subsequent carbon emissions changes and the corresponding industry impacts according to the corresponding models. Since the carbon emission prediction model is divided according to the industry, each sub-model corresponds to a specific industry, thereby reducing the interference caused by the participation of parameters unrelated to the industry in the calculation, so as to improve accuracy;

[0031] Based on the calculation prediction results of each model, in conjunction with the carbon emission threshold value pre-set by the warning threshold setting module 3, a warning is issued if the prediction result exceeds the threshold value;

[0032] The initial template content of the initial report template unit 401 contains the content of all templates in the report template library 403, and only one duplicate content is retained. The association unit 402 associates the initial template format with each template format in the report template library 403, and then the template conversion unit 404 converts the content in the initial template based on the selected template format in the report template library 403 to make it compatible with the selected report template format, as shown in the following example:

[0033] If the weight unit in the initial template content is different from the weight unit of the template in the report template library 403, the association unit 402 associates the weight units in the two templates, and the template conversion unit 404 converts the specific weight in the initial template content into the specific weight of the template in the report template library 403 based on the conversion factor of the two weight units;

[0034] Finally, the report content is output according to the selected template format through the template format output unit 405, so that the system can quickly adapt to different report templates when used in different institutions and countries.

[0035] like Figure 2-Figure 5As shown, a carbon emission prediction and early warning device is applied with the above-mentioned high-accuracy carbon emission prediction and early warning system, including a server component 5, the server component 5 includes a gas distribution pipe 501, an electronic valve 502, a server frame 503, a layer plate 504, a gas injection end 505, an exhaust end 506, a server body 507, a sandwich sleeve 508, a plug 509, a three-way valve 510, a return air pipe 511, an exhaust pipe 512 and a circulation fan 513, the bottom of the gas distribution pipe 501 is connected to the server frame 503 through the electronic valve 502, and the server frame 503 is equidistantly arranged with layer plates 504 inside, and the server frame 503 and the layer plates 504 are connected inside. A through cavity is formed, and a gas injection end 505 and an exhaust end 506 are sequentially arranged in the middle of the surface of the layer plate 504 from left to right, a plug 509 is inserted into the gas injection end 505 and the exhaust end 506, and a sandwich sleeve 508 is connected to the top of the plug 509, a server body 507 is arranged inside the sandwich sleeve 508, a three-way valve 510 is arranged on the side of the top of the server frame 503 away from the electronic valve 502, and a return air pipe 511 is connected to the side of the three-way valve 510, and an exhaust pipe 512 is connected to the top of the three-way valve 510, a circulation fan 513 is arranged inside the server frame 503 just below the electronic valve 502, and a temperature sensor is arranged inside the server frame 503;

[0036] The specific operation is as follows: the server body 507 often generates heat accumulation due to the need to run a large amount of data. The cooling methods currently used mainly include air cooling and water cooling. Air cooling mainly removes heat by rotating the fan but generates noise, which is suitable for occasions where multiple servers exist. Water cooling often has the hidden danger of coolant leakage, which can easily cause the server to be damaged by water.

[0037] In the present invention, the server body 507 is located inside the interlayer sleeve 508, and the interlayer sleeve 508 is plugged with the gas injection end 505 and the exhaust end 506 through the plug 509 at the bottom thereof, so that the internal cavity of the interlayer sleeve 508 is connected with the internal cavity of the server frame 503 and the layer plate 504, and the end of the air distribution pipe 501 is connected with the air outlet pipe of the indoor central air conditioner, so that the cold air discharged by the central air conditioner enters the inside of one side of the server frame 503 along the air distribution pipe 501, and the cold air flows along the layer plate 504 and the inside of the interlayer sleeve 508. The heat of the server body 507 is absorbed by the cooling system. Compared with air cooling and water cooling, firstly, there is no noise and the cooling effect is better. Secondly, there is no hidden danger of coolant leakage. The cold air enters the other side of the server frame 503 from the exhaust end 506 and rises to enter the three-way valve 510. The three-way valve 510 has a temperature sensor inside. If the temperature of the cold air after absorbing heat is still within the preset range, the cold air is discharged to the people's activity area through the multi-way valve at the end of the exhaust pipe 512 to avoid the waste of cold air. If the temperature of the cold air after absorbing heat is higher than the threshold, it is directly discharged through the multi-way valve.

[0038] Secondly, a temperature sensor is provided inside the server frame 503. If the internal temperature of a server frame 503 is significantly higher than that of other server frames 503, the server frame 503 with the lowest temperature is selected from the other server frames 503 and the electronic valve 502 on its top is temporarily closed, thereby increasing the amount of cold air inside the server frame 503 with a higher temperature, and strengthening the cooling inside the server frame 503 with a higher temperature. After the electronic valve 502 is closed, the circulating fan 513 below the electronic valve 502 is started, and at the same time, the three-way valve 510 opens the return air pipe 511 and closes the exhaust pipe 512. At this time, the cold air inside the server frame 503 with a lower temperature circulates inside the server frame 503, the layer plate 504, the interlayer sleeve 508, and the return air pipe 511 under the guidance of the circulating fan 513. Therefore, when the cold air is temporarily introduced, the residual cold air circulation is used to continue to maintain the cooling and heat dissipation effect to suppress the rapid increase in the temperature of the server body 507 with a lower temperature.

[0039] In summary, when the highly accurate carbon emission prediction and early warning system and device is used, firstly, the real-time data unit 101 obtains real-time data by satellite monitoring, sensor detection, etc., and the real-time data includes meteorological data, industrial emission data, energy consumption data, etc., and the data checking unit 102 checks whether the collected data has missing or erroneous parts, and classifies the erroneous data into the data missing unit 103 or the data error incorrect unit 104 according to the data error type;

[0040] The problem processing unit 105 searches for highly similar content in the historical data based on the context content at the missing real-time data location, and performs context analysis based on the data points in the historical data corresponding to the missing real-time data location to obtain the missing data at the missing real-time data location. The problem processing unit 105 also corrects the error in the real-time data based on the context and the rules of the data at that location within the scope allowed by the rules, wherein the specific rules are as follows: Taking the date as an example, the whole year is divided into twelve months, and the number of days in each month is fixed. If the date above is August 15, 2024, and the date below is August 18, 2024, according to the context and date rules, the date in the middle is 1 If the data is on the 9th, then the date is definitely wrong and needs to be corrected. The 16th or 17th can be selected as the corrected data. The same is true for other data. If the data obviously exceeds the threshold according to the data rule, it means that the data error needs to be corrected. The corrected data is within the threshold and conforms to the transition of the context data. By reasonably supplementing the missing parts of the collected data, and correcting the data errors within the threshold according to the rules of the data type and adapting to the transition of the context of the errors, there is no need to directly remove the missing data points and the wrong data points, so that the collected data content is substantial and accurate, so as to improve the accuracy of subsequent prediction and warning;

[0041] The re-verification module 107 re-verifies the data processed by the problem processing unit 105, so that the processed data is again tested for problems to prevent problems from being missed. The data that pass the test enters the data sub-item unit 201, and the data sub-item unit 201 classifies the received data according to the various required data types of the meteorological impact prediction model 202, the industrial impact prediction model 203, and the life impact prediction model 204. One type of data can be classified and participate in the calculation of the three models at the same time. The meteorological impact prediction model 202 predicts future meteorological changes based on the input data, the industrial impact prediction model 203 predicts future industrial carbon emissions and temperature changes based on the input data, and the life impact prediction model 204 predicts future changes in residents' life-related factors based on the input data, and the residents' life-related factors include but are not limited to regional temperature, air quality, and rainwater acidity content;

[0042] Based on the calculation prediction results of each model, in conjunction with the carbon emission threshold value pre-set by the warning threshold setting module 3, a warning is issued if the prediction result exceeds the threshold; the initial template content of the initial report template unit 401 contains the content of all templates in the report template library 403, and only one duplicate content is retained, and the association unit 402 associates the initial template format with each template format in the report template library 403, and then the template conversion unit 404 converts the content in the initial template based on the selected template format in the report template library 403 to make it compatible with the selected report template format, and finally the report content is output according to the selected template format through the template format output unit 405, so that the system can quickly adapt to different report templates when used in different institutions and countries;

[0043] The server body 507 is located inside the interlayer sleeve 508, and the interlayer sleeve 508 is plugged with the gas injection end 505 and the exhaust end 506 through the plug 509 at the bottom thereof, so that the internal cavity of the interlayer sleeve 508 is connected with the internal cavity of the server frame 503 and the layer plate 504, and the end of the air distribution pipe 501 is connected to the air outlet pipe of the indoor central air conditioner, so that the cold air exhausted by the central air conditioner enters the inside of one side of the server frame 503 along the air distribution pipe 501, and the cold air flows along the layer plate 504 and the interlayer sleeve 508. At this time, in order to absorb the heat of the server body 507, the cold air enters the other side of the server frame 503 from the exhaust end 506 and rises to enter the three-way valve 510. The three-way valve 510 has a temperature sensor inside. If the temperature of the cold air after absorbing heat is still within the preset range, the cold air is discharged to the people's activity area through the multi-way valve at the end of the exhaust pipe 512 to avoid waste of cold air. If the temperature of the cold air after absorbing heat is higher than the threshold, it is directly discharged through the multi-way valve.

[0044] Secondly, a temperature sensor is provided inside the server frame 503. If the internal temperature of a server frame 503 is significantly higher than that of other server frames 503, the server frame 503 with the lowest temperature is selected from the other server frames 503 and the electronic valve 502 on its top is temporarily closed, thereby increasing the amount of cold air inside the server frame 503 with a higher temperature, and strengthening the cooling inside the server frame 503 with a higher temperature. After the electronic valve 502 is closed, the circulating fan 513 below the electronic valve 502 is started, and at the same time, the three-way valve 510 opens the return air pipe 511 and closes the exhaust pipe 512. At this time, the cold air inside the server frame 503 with a lower temperature circulates inside the server frame 503, the layer plate 504, the interlayer sleeve 508, and the return air pipe 511 under the guidance of the circulating fan 513. Therefore, when the cold air is temporarily introduced, the residual cold air circulation is used to continue to maintain the cooling and heat dissipation effect to suppress the rapid increase in the temperature of the server body 507 with a lower temperature.

[0045] The embodiments of the present invention are given for the purpose of illustration and description, and are not intended to be exhaustive or to limit the invention to the disclosed forms. Many modifications and variations will be apparent to those of ordinary skill in the art. The embodiments are selected and described in order to better illustrate the principles and practical applications of the present invention and to enable those of ordinary skill in the art to understand the present invention and thereby design various embodiments with various modifications suitable for specific uses.

Claims

1. A highly accurate carbon emission prediction and early warning system, comprising a data collection and sorting module (1) and a carbon emission prediction model group (2), characterized in that: The data collection and collation module (1) is connected to the carbon emission prediction model group (2), and the carbon emission prediction model group (2) is connected to the early warning threshold setting module (3), and the early warning threshold setting module (3) is connected to the report output module (4). The data collection and collation module (1) comprises a real-time data unit (101), a data checking unit (102), a data missing unit (103), a data error unit (104), a problem processing unit (105), a historical data unit (106) and a re-verification module (107). The real-time data unit (101) is connected to the data checking unit (102), and the data checking unit (102) is connected to the data missing unit (103) and the data error unit (104), the data missing unit (103) and the data error unit (104) are connected to the problem processing unit (105), and the problem processing unit (105) is connected to the historical data unit (106) and the re-verification module (107).

2. A highly accurate carbon emission prediction and early warning system according to claim 1, characterized in that: The real-time data unit (101) is used to collect meteorological data, industrial emission data, and energy consumption data in real time by means of satellite monitoring or sensor detection, and the data checking unit (102) is used to check whether the collected data has any missing or erroneous parts, and classify the erroneous data into a data missing unit (103) or a data error incorrect unit (104) according to the data error type.

3. A highly accurate carbon emission prediction and early warning system according to claim 1, characterized in that: The historical data unit (106) is used to store historical data that has been verified to be error-free and missing, and the problem processing unit (105) is used to search for content with high similarity in the historical data based on the context content of the missing real-time data location, and to obtain the missing data at the missing real-time data location based on the data points in the historical data corresponding to the missing real-time data location combined with the context analysis.

4. A highly accurate carbon emission prediction and early warning system according to claim 1, characterized in that: The problem processing unit (105) is also used to correct the errors in the real-time data in combination with the context and the rules of the data at that location within the scope allowed by the rules, and the re-verification module (107) re-verifies the data processed by the problem processing unit (105).

5. A highly accurate carbon emission prediction and early warning system according to claim 1, characterized in that: The carbon emission prediction model group (2) includes a data sub-item unit (201), a meteorological impact prediction model (202), an industrial impact prediction model (203) and a life impact prediction model (204), and the data sub-item unit (201) is connected to the meteorological impact prediction model (202), the industrial impact prediction model (203) and the life impact prediction model (204).

6. A highly accurate carbon emission prediction and early warning system according to claim 5, characterized in that: The data classification unit (201) classifies the verified data according to the data types required by the meteorological impact prediction model (202), the industrial impact prediction model (203), and the life impact prediction model (204).

7. A highly accurate carbon emission prediction and early warning system according to claim 5, characterized in that: The meteorological impact prediction model (202) is used to predict future meteorological changes based on input data, the industrial impact prediction model (203) is used to predict future industrial carbon emissions based on input data, and the life impact prediction model (204) is used to predict future changes in residents' life-related factors based on input data, and residents' life-related factors include but are not limited to regional temperature and air quality.

8. A highly accurate carbon emission prediction and early warning system according to claim 1, characterized in that: The report output module (4) comprises an initial report template unit (401), an association unit (402), a report template library (403), a template conversion unit (404) and a template format output unit (405); the initial report template unit (401) is connected to the report template library (403) via the association unit (402), and the association unit (402) is also connected to the template conversion unit (404); and the template conversion unit (404) is connected to the template format output unit (405).

9. A highly accurate carbon emission prediction and early warning system according to claim 8, characterized in that: The initial template content of the initial report template unit (401) contains the content of all templates in the report template library (403), the association unit (402) associates the initial template format with each template format in the report template library (403), and the template conversion unit (404) converts the content in the initial template based on the selected template format in the report template library (403) to make it compatible with the selected report template format.

10. A carbon emission prediction and early warning device, which is applied with a high-accuracy carbon emission prediction and early warning system as claimed in any one of claims 1 to 9, characterized in that: The server assembly (5) comprises an air distribution pipe (501), an electronic valve (502), a server frame (503), a layer plate (504), an air injection end (505), an exhaust end (506), a server body (507), an interlayer sleeve (508), a plug (509), a three-way valve (510), an air return pipe (511), an exhaust pipe (512) and a circulation fan (513); the bottom of the air distribution pipe (501) is connected to the server frame (503) via the electronic valve (502), and the layer plates (504) are equidistantly arranged inside the server frame (503); the server frame (503) and the layer plates (504) are provided with interconnected cavities inside, and the middle of the surface of the layer plates (504) is arranged from left to right in accordance with the present invention; A gas injection end (505) and an exhaust end (506) are provided, and a plug (509) is inserted into the gas injection end (505) and the exhaust end (506), and the top of the plug (509) is connected to an interlayer sleeve (508), and a server body (507) is provided inside the interlayer sleeve (508), and a three-way valve (510) is provided on the side of the top of the server frame (503) away from the electronic valve (502), and the side of the three-way valve (510) is connected to a return air pipe (511), and the top of the three-way valve (510) is connected to an exhaust pipe (512), and a circulation fan (513) is provided inside the server frame (503) just below the electronic valve (502), and a temperature sensor is provided inside the server frame (503).

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