Risk early warning system based on carbon credit intelligent contract transaction

Abstract

The invention discloses a carbon credit intelligent contract transaction-based risk early warning system, which relates to the field of carbon credit transaction risk early warning and comprises a historical transaction information acquisition module, a data analysis module, a preliminary evaluation early warning module and a comprehensive early warning module, data acquisition and analysis are carried out on each successful transaction order in the carbon credit transaction platform to obtain system information and user information in the carbon credit transaction platform, and data analysis is carried out on the system information and the user information in the carbon credit transaction platform to obtain a first carbon credit transaction risk influence coefficient of each carbon credit transaction user; user information in a carbon credit transaction platform is subjected to multi-processing, data of a single historical transaction time period and data of a continuous historical transaction time period are analyzed in detail, and the accuracy and effectiveness of carbon credit transaction early warning are improved.

Description

Technical Field

[0001] This application relates to the field of carbon credit trading risk warning, and particularly to a risk warning system based on carbon credit smart contract trading. Background Art

[0002] As an important tool for addressing climate change, the healthy development of the carbon credit market is of great significance for promoting the global green economic transformation. The risk warning system can monitor and warn against abnormal trading behaviors in the market, prevent the occurrence of illegal behaviors such as market manipulation and insider trading, and maintain the fairness, justice, and transparency of the market; The sound development of the carbon credit market needs to be based on a perfect risk management mechanism. As an important part of risk management, the risk warning system can provide timely and accurate risk information for market participants, help them make rational investment decisions, and avoid blind following or excessive speculation behaviors. At the same time, the risk warning system can also provide a basis for supervision for regulatory authorities, help them discover and dispose of market risks in a timely manner, and ensure the sound operation of the market. The existing technologies still have the following deficiencies; When the existing technologies conduct risk warning for carbon credit trading, they usually judge by the abnormal price or abnormal trading volume of a single transaction order, lacking a scientific analysis of the historical trading status of carbon credit trading users, resulting in a lack of reasonable data basis for risk warning in carbon credit trading, thereby reducing the accuracy and effectiveness of risk warning judgment, and being unfavorable for ensuring the sound operation of the market. Summary of the Invention

[0003] The purpose of the present invention is to provide a risk warning system based on carbon credit smart contract trading to solve the problems raised in the above background art.

[0004] To achieve the above purpose, the present invention provides the following technical solution: A risk warning system based on carbon credit smart contract trading, including: Historical transaction information acquisition module: used to acquire the historical trading status of carbon credits to obtain the historical transaction information of carbon credit trading; Data analysis module: used to conduct data statistical analysis on the historical transaction information of carbon credit trading to obtain a data comparison set and the influence coefficient of the supply-demand relationship on the carbon credit trading price within each historical trading time period; Preliminary evaluation and warning module: used to conduct a preliminary evaluation according to the data comparison set to obtain the comprehensive trading risk influence coefficient of each carbon credit trading user; Comprehensive warning module: used to conduct warning analysis according to the comprehensive trading risk influence coefficient of each carbon credit trading user to obtain the warning result of carbon credit trading.

[0005] In a preferred embodiment of this solution, the specific implementation manner of the transaction information acquisition module is as follows: Obtain each successful transaction order and the number of orders within each historical transaction period through the carbon credit trading platform, extract data from each successful transaction order within each transaction period, and obtain the carbon credit selling user, carbon credit buying user, carbon credit trading quantity, and carbon credit trading unit price corresponding to each successful transaction order. Denote the carbon credit selling user, carbon credit buying user, carbon credit trading quantity, and carbon credit trading unit price corresponding to each successful transaction order within each transaction period as the historical transaction information of carbon credit trading.

[0006] In a preferred embodiment of this solution, the specific implementation manner of the data analysis module is as follows: Perform data statistics on the historical transaction information of carbon credit trading to obtain the total carbon credit selling volume and total carbon credit buying volume within each historical transaction period; Through the calculation formula , calculate the influence coefficient of the supply-demand relationship on the carbon credit trading price within each historical transaction period , where represents the number of each historical transaction period, , respectively represent the total carbon credit selling volume and total carbon credit buying volume within each historical transaction period, represents the carbon credit trading price influence factor; Perform data statistics on each successful transaction order within each historical transaction period to obtain a data comparison set, where the data comparison set includes system information and user information; System information refers to the average carbon credit buying unit price for a single carbon credit purchase and the average carbon credit selling price of carbon credits for a single carbon credit sale within each historical transaction period obtained by performing data statistics and calculations on the carbon credit selling user, carbon credit buying user, carbon credit trading quantity, and carbon credit trading unit price of each successful transaction order within each historical transaction period; User information refers to the number of purchases, the carbon credit purchase quantity corresponding to each carbon credit purchase, the carbon credit purchase unit price of each carbon credit purchase, the number of sales, the carbon credit sale quantity corresponding to each carbon credit sale, and the carbon credit sale unit price of each carbon credit sale obtained by performing data statistics on the carbon credit selling user, carbon credit buying user, carbon credit trading quantity, and carbon credit trading unit price corresponding to each successful transaction order within each historical transaction period for each carbon credit trading user; Perform data statistics and calculations on the user information to obtain the average carbon credit selling price, average carbon credit buying price, average carbon credit selling volume, average carbon credit buying volume, average carbon credit buying times, and average carbon credit selling times of each carbon credit trading user within each historical transaction period.

[0007] In a preferred embodiment of this solution, the specific implementation method of the preliminary evaluation and early warning module is as follows: Through the calculation formula , calculate the impact coefficient of the carbon credit selling price difference on the carbon credit trading risk for each carbon credit trading user in each historical trading period ; Through the calculation formula , calculate the impact coefficient of the carbon credit purchase price difference on the carbon credit trading risk for each carbon credit trading user in each historical trading period ; Through the calculation formula , calculate the first carbon credit trading risk impact coefficient for each carbon credit trading user ; Wherein , respectively represent the average carbon credit purchase unit price for a single carbon credit purchase and the average carbon credit selling price for a single carbon credit sale, , respectively represent the average carbon credit selling price and the average carbon credit purchase price for each carbon credit trading user in each historical trading period, , respectively represent the selling price difference impact factor and the purchase price difference impact factor, represents the first carbon credit trading risk impact coefficient impact factor, represents the number of the historical trading period; Compare and analyze the first carbon credit trading risk impact coefficient of each carbon credit trading user with the preset first carbon credit trading risk impact coefficient threshold. If the first carbon credit trading risk impact coefficient of the carbon credit trading user is less than the preset first carbon credit trading risk impact coefficient threshold, the trading risk of the carbon credit trading user is within the safe range. If the first carbon credit trading risk impact coefficient of the carbon credit trading user is equal to or greater than the preset first carbon credit trading risk impact coefficient threshold, the trading risk of the carbon credit trading user is within the dangerous range. Record the carbon credit trading users in the dangerous range as the preliminary warning result of carbon credit trading; Through the calculation formula , calculate the impact coefficient of the selling price difference between adjacent carbon credit sales on the carbon credit trading risk for each carbon credit trading user in each historical trading period ; Through the calculation formula , calculate the impact coefficient of the purchase price difference between adjacent carbon credit purchases on the carbon credit trading risk for each carbon credit trading user in each historical trading period ; Through the calculation formula , the second carbon credit trading risk impact coefficient of each carbon credit trading user is calculated , where 、 respectively represent the carbon credit selling unit price of each carbon credit sale and the carbon credit purchasing unit price of each carbon credit purchase for each carbon credit trading user during each historical trading period, represents the number of each carbon credit sale, represents the number of carbon credit sales, represents the number of each carbon credit purchase, represents the number of carbon credit purchases, represents the impact factor of the second carbon credit trading risk impact coefficient; Through the calculation formula; , the trading price difference of each carbon credit trading user corresponding to each historical trading period on the carbon credit trading risk impact coefficient is calculated ; Through the calculation formula , the trading volume difference of each carbon credit trading user corresponding to each historical trading period on the carbon credit trading risk impact coefficient is calculated ; Through the calculation formula , the trading times difference of each carbon credit trading user corresponding to each historical trading period on the carbon credit trading risk impact coefficient is calculated ; Through the calculation formula , the third carbon credit trading risk impact coefficient of each carbon credit trading user is calculated , where 、 、 、 、 、 respectively represent the average carbon credit selling unit price, average carbon credit purchasing unit price, average carbon credit selling volume, average carbon credit purchasing volume, average carbon credit purchasing times and average carbon credit selling times of each carbon credit trading user during each historical trading period; Through the calculation formula , the comprehensive trading risk impact coefficient of each carbon credit trading user is obtained .

[0008] In the preferred solution of this scheme, the specific execution method of the comprehensive early warning module is as follows: Compare and analyze the comprehensive transaction risk impact coefficient of each carbon credit trading user with the preset threshold of the comprehensive transaction risk impact coefficient. If the comprehensive transaction risk impact coefficient of the requesting carbon credit trading user is less than the preset threshold of the comprehensive transaction risk impact coefficient, it indicates that the carbon credit trading of the requesting carbon credit trading user is within the safe range and no risk warning is issued. If the comprehensive transaction risk impact coefficient of a certain requesting carbon credit trading user is greater than or equal to the preset threshold of the comprehensive transaction risk impact coefficient, it indicates that the carbon credit trading of the requesting carbon credit trading user is not within the safe range and a risk warning is issued. Count the carbon credit trading users who have received risk warnings, and record the carbon credit trading users who have received risk warnings as the warning results of carbon credit trading.

[0009] Compared with the prior art, the beneficial effects of the present invention are: By obtaining and analyzing data of each successful transaction order in the carbon credit trading platform, the present invention obtains system information and user information in the carbon credit trading platform. Through systematic analysis between the system information and user information in the carbon credit trading platform and among the user information itself, it provides a reliable data basis for carbon credit trading warning in the carbon credit trading platform, which is conducive to timely discovering and disposing of market risks and ensuring the stable operation of the market. By performing data analysis on the system information and user information in the carbon credit trading platform, the present invention obtains the first carbon credit trading risk impact coefficient of each carbon credit trading user. By performing multiple processes on the user information in the carbon credit trading platform and analyzing in detail the data of the single historical transaction time period and the continuous historical transaction time period, it is beneficial to improve the accuracy and effectiveness of carbon credit trading warning. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] The present invention is further described with reference to the accompanying drawings. However, the embodiments in the drawings do not constitute any limitation to the present invention. For those of ordinary skill in the art, other drawings can also be obtained according to the following drawings without creative efforts.

[0011] Figure 1 It is a schematic diagram of module connection for an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0012] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0013] Please refer to Figure 1, the present invention provides a risk warning system based on carbon credit smart contract transactions, which includes a historical transaction information acquisition module, a data analysis module, a preliminary evaluation and warning module, and a comprehensive warning module; The historical transaction information acquisition module is connected to the data analysis module, the data analysis module is connected to the preliminary evaluation and warning module, and the preliminary evaluation and warning module is connected to the comprehensive warning module.

[0014] Historical transaction information acquisition module: used to obtain the historical transaction status of carbon credits and obtain the historical transaction information of carbon credit transactions; Further, the specific implementation method of the transaction information acquisition module is as follows: Obtain each successful transaction order and the number of orders in each historical transaction time period through the carbon credit trading platform, extract data from each successful transaction order in each transaction time period, and obtain the carbon credit selling user, carbon credit buying user, carbon credit transaction quantity, and carbon credit transaction unit price corresponding to each successful transaction order. Record the carbon credit selling user, carbon credit buying user, carbon credit transaction quantity, and carbon credit transaction unit price corresponding to each successful transaction order in each transaction time period as the historical transaction information of carbon credit transactions.

[0015] Data analysis module: used to perform data statistical analysis on the historical transaction information of carbon credit transactions to obtain a data comparison set and the influence coefficient of the supply and demand relationship on the carbon credit transaction price in each historical transaction time period; Further, the specific implementation method of the data analysis module is as follows: Perform data statistics on the historical transaction information of carbon credit transactions to obtain the total carbon credit selling volume and total carbon credit buying volume in each historical transaction time period; Through the calculation formula , calculate the influence coefficient of the supply and demand relationship on the carbon credit transaction price in each historical transaction time period , where represents the number of each historical transaction time period, , respectively represent the total carbon credit selling volume and total carbon credit buying volume in each historical transaction time period, represents the carbon credit transaction price influence factor; Perform data statistics on each successful transaction order in each historical transaction time period to obtain a data comparison set, where the data comparison set includes system information and user information; System information refers to performing data statistical calculations on the carbon credit selling user, carbon credit buying user, carbon credit transaction quantity, and carbon credit transaction unit price of each successful transaction order in each historical transaction time period to obtain the average carbon credit buying unit price for a single carbon credit purchase and the average carbon credit selling price of a single carbon credit sale in each historical transaction time period; User information refers to the data statistics of the carbon credit selling users, carbon credit purchasing users, carbon credit transaction quantities, and carbon credit transaction unit prices corresponding to each successful transaction order within each historical transaction time period, obtaining the number of purchase times corresponding to each carbon credit trading user within each historical transaction time period, the carbon credit purchase quantity corresponding to each carbon credit purchase, the carbon credit purchase unit price for each carbon credit purchase, the number of sale times, the carbon credit sale quantity corresponding to each carbon credit sale, and the carbon credit sale unit price for each carbon credit sale; Perform data statistical calculations on the user information to obtain the average carbon credit sale unit price, average carbon credit purchase unit price, average carbon credit sale quantity, average carbon credit purchase quantity, average carbon credit purchase times, and average carbon credit sale times of each carbon credit trading user within each historical transaction time period.

[0016] Preliminary evaluation and warning module: used to perform a preliminary evaluation based on the data comparison set to obtain the comprehensive transaction risk impact coefficient of each carbon credit trading user; Furthermore, the specific implementation method of the preliminary evaluation and warning module is as follows: Through the calculation formula , calculate the carbon credit sale price difference impact coefficient on the carbon credit transaction risk of each carbon credit trading user within each historical transaction time period ; Through the calculation formula , calculate the carbon credit purchase price difference impact coefficient on the carbon credit transaction risk of each carbon credit trading user within each historical transaction time period ; Through the calculation formula , calculate the first carbon credit transaction risk impact coefficient of each carbon credit trading user ; Where , respectively represent the average carbon credit purchase unit price for a single carbon credit purchase and the average carbon credit sale unit price for a single carbon credit sale, , respectively represent the average carbon credit sale unit price and the average carbon credit purchase unit price of each carbon credit trading user within each historical transaction time period, , respectively represent the sale price difference impact factor and the purchase price difference impact factor, represents the first carbon credit transaction risk impact coefficient impact factor, represents the number of the historical transaction time period; Compare and analyze the first carbon credit trading risk impact coefficient of each carbon credit trading user with the preset first carbon credit trading risk impact coefficient threshold. If the first carbon credit trading risk impact coefficient of the carbon credit trading user is less than the preset first carbon credit trading risk impact coefficient threshold, the trading risk of the carbon credit trading user is within the safe range. If the first carbon credit trading risk impact coefficient of the carbon credit trading user is equal to or greater than the preset first carbon credit trading risk impact coefficient threshold, the trading risk of the carbon credit trading user is within the dangerous range. Record the carbon credit trading users in the dangerous range as the preliminary carbon credit trading warning results; Through the calculation formula , calculate the impact coefficient of the selling price difference between adjacent carbon credit sales of each carbon credit trading user in each historical trading period on the carbon credit trading risk ; Through the calculation formula , calculate the impact coefficient of the purchase price difference between adjacent carbon credit purchases of each carbon credit trading user in each historical trading period on the carbon credit trading risk ; Through the calculation formula , calculate the second carbon credit trading risk impact coefficient of each carbon credit trading user , where 、 respectively represent the carbon credit selling unit price of each carbon credit trading user corresponding to each carbon credit sale and the carbon credit purchase unit price of each carbon credit purchase in each historical trading period, represents the number of each carbon credit sale, represents the number of carbon credit sales, represents the number of each carbon credit purchase, represents the number of carbon credit purchases, represents the impact factor of the second carbon credit trading risk impact coefficient; Through the calculation formula; , calculate the impact coefficient of the trading price difference of each carbon credit trading user corresponding to each historical trading period on the carbon credit trading risk ; Through the calculation formula , calculate the impact coefficient of the trading volume difference of each carbon credit trading user corresponding to each historical trading period on the carbon credit trading risk ; Through the calculation formula , calculate the impact coefficient of the trading times difference of each carbon credit trading user corresponding to each historical trading period on the carbon credit trading risk ; Through the calculation formula , the third carbon credit trading risk impact coefficient of each carbon credit trading user is calculated , where 、 、 、 、 、 respectively represent the average selling unit price of carbon credits, the average buying unit price of carbon credits, the average selling volume of carbon credits, the average buying volume of carbon credits, the average buying times of carbon credits, and the average selling times of carbon credits of each carbon credit trading user in each historical trading time period; Through the calculation formula , the comprehensive trading risk impact coefficient of each carbon credit trading user is obtained .

[0017] Furthermore, the specific implementation method of the comprehensive early warning module is as follows: Compare and analyze the comprehensive trading risk impact coefficient of each carbon credit trading user with the preset comprehensive trading risk impact coefficient threshold. If the comprehensive trading risk impact coefficient of the requested carbon credit trading user is less than the preset comprehensive trading risk impact coefficient threshold, it means that the carbon credit trading of the requested carbon credit trading user is within the safe range and no risk early warning is carried out; If the comprehensive trading risk impact coefficient of a certain requested carbon credit trading user is greater than or equal to the preset comprehensive trading risk impact coefficient threshold, it means that the carbon credit trading of the requested carbon credit trading user is not within the safe range and risk early warning is carried out. Count the carbon credit trading users who carry out risk early warning, and record the carbon credit trading users who carry out risk early warning as the early warning result of carbon credit trading.

[0018] The above are all preferred embodiments of this application, and the protection scope of this application is not limited accordingly. Therefore, all equivalent changes made according to the structure, shape, and principle of this application should be covered within the protection scope of this application.

Claims

1. A risk warning system based on carbon credit smart contract transactions, characterized in that: Including: Historical transaction information acquisition module: used to obtain the historical transaction status of carbon credits, and obtain the historical transaction information of carbon credit transactions; Data analysis module: used to perform data statistical analysis on the historical transaction information of carbon credit transactions, and obtain a data comparison set and the influence coefficient of the supply-demand relationship on the carbon credit transaction price within each historical transaction time period; Preliminary evaluation and warning module: used to perform a preliminary evaluation based on the data comparison set, and obtain the comprehensive transaction risk influence coefficient of each carbon credit trading user; Comprehensive warning module: used to perform warning analysis based on the comprehensive transaction risk influence coefficient of each carbon credit trading user, and obtain the warning result of carbon credit transactions.

2. The risk warning system based on carbon credit smart contract trading according to claim 1, wherein: The specific implementation method of the said transaction information acquisition module is as follows: Obtain each successful transaction order and the order number within each historical transaction time period through the carbon credit trading platform, extract data from each successful transaction order within each transaction time period, and obtain the carbon credit selling user, carbon credit buying user, carbon credit transaction quantity, and carbon credit transaction unit price corresponding to each successful transaction order. Record the carbon credit selling user, carbon credit buying user, carbon credit transaction quantity, and carbon credit transaction unit price corresponding to each successful transaction order within each transaction time period as the historical transaction information of carbon credit transactions.

3. The risk warning system based on carbon credit smart contract transactions according to claim 1 is characterized in that: The specific implementation method of the said data analysis module is as follows: Perform data statistics on the historical transaction information of carbon credit transactions to obtain the total carbon credit selling volume and total carbon credit buying volume within each historical transaction time period; By using the calculation formula , the influence coefficients of the supply-demand relationship on the carbon credit trading price in each historical trading period are calculated , where represents the number of each historical trading period, and respectively represent the total amount of carbon credits sold and the total amount of carbon credits purchased in each historical trading period, represents the carbon credit trading price impact factor; Perform data statistics on each successful transaction order within each historical transaction time period to obtain a data comparison set, where the data comparison set includes system information and user information; System information refers to the average carbon credit buying unit price for a single carbon credit purchase and the carbon credit average selling unit price for a single carbon credit sale within each historical transaction time period obtained by performing data statistical calculations on the carbon credit selling user, carbon credit buying user, carbon credit transaction quantity, and carbon credit transaction unit price of each successful transaction order within each historical transaction time period; User information refers to the number of purchases, the carbon credit purchase quantity corresponding to each carbon credit purchase, the carbon credit purchase unit price of each carbon credit purchase, the number of sales, the carbon credit sale quantity corresponding to each carbon credit sale, and the carbon credit sale unit price of each carbon credit sale corresponding to each carbon credit trading user within each historical transaction time period obtained by performing data statistics on the carbon credit selling user, carbon credit buying user, carbon credit transaction quantity, and carbon credit transaction unit price corresponding to each successful transaction order within each historical transaction time period; Perform data statistical calculations on the user information to obtain the average carbon credit selling unit price, average carbon credit buying unit price, average carbon credit selling volume, average carbon credit buying volume, average carbon credit purchase times, and average carbon credit sale times of each carbon credit trading user within each historical transaction time period.

4. The risk warning system based on carbon credit smart contract transactions according to claim 3, wherein: The specific implementation method of the said preliminary evaluation and warning module is as follows: By using the calculation formula , the influence coefficient of the carbon credit selling price difference of each carbon credit trading user in each historical trading period on the carbon credit trading risk is calculated ; By using the calculation formula , the impact coefficient of the carbon credit purchase price difference of each carbon credit trading user in each historical trading period on the carbon credit trading risk is calculated ; By using the calculation formula , the first carbon credit trading risk impact coefficient of each carbon credit trading user is calculated ; Among them and respectively represent the average carbon credit purchase unit price for a single carbon credit purchase and the average carbon credit selling unit price for a single carbon credit sale and respectively represent the average carbon credit selling unit price and the average carbon credit purchase unit price of each carbon credit trading user within each historical trading time period and respectively represent the selling price difference impact factor and the purchase price difference impact factor represents the first carbon credit trading risk impact coefficient impact factor represents the number of the historical trading time period Compare and analyze the first carbon credit trading risk impact coefficient of each carbon credit trading user with the preset first carbon credit trading risk impact coefficient threshold. If the first carbon credit trading risk impact coefficient of the carbon credit trading user is less than the preset first carbon credit trading risk impact coefficient threshold, the trading risk of the carbon credit trading user is within the safe range. If the first carbon credit trading risk impact coefficient of the carbon credit trading user is equal to or greater than the preset first carbon credit trading risk impact coefficient threshold, the trading risk of the carbon credit trading user is within the dangerous range, and the carbon credit trading users within the dangerous range are recorded as the preliminary carbon credit trading warning results; By using the calculation formula , calculate the influence coefficient of the selling price difference between adjacent carbon credit sales of each carbon credit trading user in each historical trading period on the carbon credit trading risk ; By using the calculation formula , the influence coefficient of the purchase price difference of adjacent carbon credit purchases by each carbon credit trading user in each historical trading period on the carbon credit trading risk is calculated ; By using the calculation formula , the second carbon credit trading risk impact coefficient of each carbon credit trading user is calculated , where 、 respectively represent the carbon credit selling unit price of each carbon credit sale and the carbon credit purchasing unit price of each carbon credit purchase corresponding to each carbon credit trading user within each historical trading time period, represents the number of each carbon credit sale, represents the number of carbon credit sales, represents the number of each carbon credit purchase, represents the number of carbon credit purchases, represents the impact factor of the second carbon credit trading risk impact coefficient; Through the calculation formula; Calculate the impact coefficient of the trading price difference of each carbon credit trading user corresponding to each historical trading period on the carbon credit trading risk ; Through the calculation formula Calculate the impact coefficient of the trading volume difference of each carbon credit trading user in each historical trading period on the carbon credit trading risk ; Through the calculation formula , the difference in the number of transactions of each carbon credit trading user corresponding to each historical trading period is calculated to obtain the carbon credit trading risk impact coefficient ; Through the calculation formula , the third carbon credit trading risk impact coefficient of each carbon credit trading user is calculated , where 、 、 、 、 、 respectively represent the average selling unit price, average purchasing unit price, average selling volume, average purchasing volume, average purchasing times and average selling times of carbon credits of each carbon credit trading user in each historical trading period; By using the calculation formula , the comprehensive trading risk impact coefficient of each carbon credit trading user is obtained .

5. The risk warning system based on carbon credit smart contract transactions according to claim 4, wherein: The specific execution method of the comprehensive warning module is as follows: Compare and analyze the comprehensive trading risk impact coefficient of each carbon credit trading user with the preset comprehensive trading risk impact coefficient threshold. If the comprehensive trading risk impact coefficient of the requesting carbon credit trading user is less than the preset comprehensive trading risk impact coefficient threshold, it indicates that the carbon credit trading of the requesting carbon credit trading user is within the safe range and no risk warning is carried out; If the comprehensive trading risk impact coefficient of a certain requesting carbon credit trading user is greater than or equal to the preset comprehensive trading risk impact coefficient threshold, it indicates that the carbon credit trading of the requesting carbon credit trading user is not within the safe range and a risk warning is carried out. Count the carbon credit trading users for whom risk warnings are carried out, and record the carbon credit trading users for whom risk warnings are carried out as the warning results of carbon credit trading.

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