Intelligent matching method and system for pollution discharge right transaction and electronic equipment

Abstract

The embodiment of the invention provides a pollution discharge right transaction intelligent matching method and system and electronic equipment. According to the technical scheme provided by the embodiment of the invention, the supply-demand relationship model corresponding to the pollution discharge right index is utilized to predict the transaction price interval of the target pollution discharge right index for user reference; the invention further provides a transaction matching algorithm for matching at least one transaction object suitable for matching for the user, so that the pollution discharge right transaction is changed into an efficient matching mode from a listing or registration long-period searching and waiting mode. In addition, at least one transaction matching scheme is generated for the user, the user transaction target is higher, the transaction period is shortened, the efficiency is high, and the transaction rate of the discharge right transaction can be improved. Visibly, according to the scheme provided by the embodiment of the invention, the intelligent degree of the pollution discharge right transaction platform is high, the user can be assisted to make a transaction decision, and the method has a positive effect on maximizing the value of the pollution discharge right on the premise of meeting the duration demand.

Description

Technical Field

[0001] This application relates to the field of computer technology, and in particular, to an intelligent matching method, system and electronic device for emissions trading rights. Background Art

[0002] Emissions trading rights, also known as emission rights, are the rights to emit pollutants. It refers to the rights that emitters enjoy to emit pollutants into the environment within the quota allocated by the environmental protection supervision and management department and on the premise that the exercise of such rights does not damage the environmental rights and interests of other members of the public.

[0003] Emissions trading means that within a certain area, on the premise that the total amount of pollutant emissions does not exceed the allowable emissions, the internal pollution sources can adjust the emissions volume through currency exchange with each other, so as to reduce pollution and protect the environment. As a market-based economic system arrangement, emissions trading encourages enterprises economically in that the seller of emissions trading rights has surplus emissions trading rights due to excessive emission reduction, and then obtains economic returns by selling or leasing the surplus emissions trading rights. This is essentially the compensation of the market for the environmental protection behavior of enterprises. The buyer or lessee has to pay a price due to the newly added emissions trading rights, and the expenses they pay are essentially the price of environmental pollution.

[0004] Each enterprise user can conduct subscription, listing, transaction approval, etc. on the emissions trading rights platform. The transaction parties need to go through a long process such as signing up, scheduling sessions, bidding, auctioning, etc. to complete the transaction. It can be seen that the efficiency of the existing emissions trading rights still needs to be improved, and its degree of intelligence is not high, and it is only used as a platform. Summary of the Invention

[0005] To solve or improve the above problems, an embodiment of this application provides an intelligent matching method, system and electronic device for emissions trading rights.

[0006] In the first embodiment of this application, an intelligent matching method for emissions trading rights is provided. This method is applicable to the server corresponding to the emissions trading rights platform, and emissions trading includes transfer and lease; the method includes: Respond to a first request sent by a user corresponding to a first client, and obtain a supply-demand relationship model corresponding to the target emissions trading rights index specified by the user; Collect historical transaction information of the target emissions trading rights index in the same period within the area where the user is located or within the tradable area of the target emissions trading rights index; wherein, the tradable area includes the area where the user is located; Input the collected historical transaction information into the supply-demand relationship model to predict the trading price range of the target emissions trading rights index; Send the predicted transaction price range to the first client for the user to refer to and determine the transaction data; the transaction data includes: the trading volume of the target emission rights index, the validity period corresponding to the target emission rights index, and the expected transaction price range. In response to a second request sent by the first client corresponding to the user, obtain the transaction data. Collect the trading intentions released by at least one seller and at least one buyer in the area where the user belongs or within the tradable geographical range on the trading platform. According to the transaction data and the trading intentions released on the trading platform, use a trading matching algorithm to match at least one trading object. Generate at least one set of trading matching plans for the at least one trading object. Send the at least one set of trading matching plans to the first client for the user to refer to.

[0007] In the second embodiment of the present application, a method for intelligent matching of emission rights trading is provided. This method is applicable to the first client. Specifically, the method includes: In response to the input operation of the user on the trading page corresponding to the emission rights trading platform, obtain the target emission rights index, trading volume, and validity period input by the user. Receive and display the prediction information fed back by the server, where the prediction information includes the trading price range of the target emission rights index. Obtain the transaction data determined by the user after referring to the trading price range; the transaction data includes the trading volume of the target emission rights index, the validity period corresponding to the target emission rights index, and the expected transaction price range. In response to the user's operation of uploading the transaction data, send the transaction data to the server; the server uses a trading matching algorithm to find at least one trading object suitable for matching on the emission rights trading platform, and generate at least one set of trading matching plans for the at least one trading object. Receive and display the at least one trading object and at least one set of trading matching plans fed back by the server.

[0008] In the third embodiment of the present application, an emission rights trading system is provided. The emission rights trading system includes: A server that provides an emission rights trading platform, and the emission rights trading includes transfer and lease; the server is used to implement the method for intelligent matching of emission rights trading provided in the first embodiment above. A first client corresponding to a user on the emission rights trading platform, and the first client is used to implement the method for intelligent matching of emission rights trading provided in the second embodiment above.

[0009] In a fourth embodiment of the present application, an electronic device is provided. The electronic device includes a processor and a memory, wherein the memory is used to store one or more computer instructions; the processor is coupled to the memory and is used to execute the one or more computer instructions to implement the steps in the above method embodiments.

[0010] In a fifth embodiment of the present application, a computer program product is provided, which includes a computer program or instructions, and when the computer program or instructions are executed by a processor, the processor is enabled to implement the steps in the above-mentioned method embodiments.

[0011] A sixth embodiment of the present application provides a computer-readable storage medium storing a computer program, and when the computer program is executed by a computer, the method steps or functions provided in the above embodiments can be implemented.

[0012] The technical solution provided in the embodiment of the present application uses the supply and demand relationship model corresponding to the pollution emission rights index to predict the transaction price range of the target pollution emission rights index for user reference; it also provides a transaction matching algorithm to match the user with at least one transaction object suitable for matching, so that the pollution emission rights trading has changed from a long-term search and waiting method such as listing or registration to an efficient matching mode. In addition, the solution of the embodiment of the present application also generates at least one set of transaction matching solutions for users, which makes user transactions more targeted, shortens the transaction cycle, is highly efficient, and helps to improve the transaction rate of pollution emission rights. It can be seen that the solution provided in the embodiment of the present application has a high degree of intelligence in the pollution emission rights trading platform, which can assist users in making trading decisions, and has a positive effect on maximizing the value of pollution emission rights while meeting the time requirements. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings: Figure 1 A schematic diagram of the structure of a pollution emission rights trading system provided for an exemplary embodiment of the present application; Figure 2 A schematic diagram of a process flow of an intelligent matching method for emission rights trading provided by an embodiment of the present application is shown; Figure 3 An exemplary schematic diagram showing the operation of the transaction page on the client side of the emission rights transaction; Figure 4 A schematic diagram of a flow chart of an intelligent matching method for emission rights trading provided by another embodiment of the present application is shown; Figure 5Schematic diagram of signaling interaction among various ends of the system in the intelligent matching method for emissions trading rights when the organizational reserve volume is transferred in an exemplary embodiment of the present application; Figures 6a - 6b Schematic diagram of signaling interaction among various ends of the system in the intelligent matching method for emissions trading rights during transactions between enterprises provided in another exemplary embodiment of the present application; Figure 7 Another exemplary diagram showing the client - side interface of emissions trading rights; Figure 8 Schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Detailed implementation manners

[0014] To make the objectives, technical solutions, and advantages of the present application clearer, the technical solutions of the present application will be clearly and completely described below in conjunction with specific embodiments of the present application and the corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present application.

[0015] It should be noted that in the case where the present application embodiments involve user information, the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the present application embodiments are all information and data authorized by the user or fully authorized by all parties. And the collection, use, and processing of relevant data need to comply with relevant laws, regulations, and standards of relevant countries and regions, and corresponding operation entrances are provided for users to choose to authorize or refuse. In addition, various models (including but not limited to language models or large models) involved in the present application comply with relevant laws and standards.

[0016] The artificial intelligence tools mentioned in the embodiments of the present application may be specifically implemented as machine learning models (such as neural network models). Of course, the artificial intelligence tools may also be language parsing models based on artificial intelligence, and the language parsing model may be a language model (Language Model, LM) based on artificial intelligence. The embodiments of the present application do not limit the amount of model parameters supported by the language model, aiming to meet application requirements.

[0017] In addition, the trading volume of emissions trading rights in the trading data mentioned herein has been reviewed by an organization (such as an environmental protection department or organization) and a surplus emissions volume certificate has been obtained. Or it is the emissions trading rights that can be sold reserved by an organization (such as an environmental protection department or organization).

[0018] In view of the problem that the existing trading parties need to sign up, make an appointment for a session, bid, auction, etc. on the trading platform to facilitate transactions, resulting in low trading efficiency, the embodiments of this application provide a solution. The basic idea is: construct a corresponding supply-demand relationship model for different pollutant discharge right indicators. Through the supply-demand relationship model, the difference between the current supply and demand corresponding to the indicator can be predicted, thereby assisting in pricing. The trading matching algorithm is also used to match the potential buyer and seller of the transaction plan; changing from the existing fishing-net method in the form of announcement and sign-up to the method of targeted invitation helps to improve the transaction success rate and reduce the transaction cost.

[0019] The following will, with reference to the accompanying drawings, elaborate on the technical solutions provided by the embodiments of this application.

[0020] Figure 1 It is a schematic structural diagram of a pollutant discharge right trading system provided by an exemplary embodiment of this application. As Figure 1 shown, the system includes: a server 1, a first client 2, and a second client 3. Among them, the first client and the second client are general terms, representing the clients corresponding to all trading parties on the pollutant discharge right trading platform respectively.

[0021] The server 1 provides a pollutant discharge right trading platform, and the pollutant discharge right trading includes transfer and lease; the server 1 is used to respond to a first request sent by a user corresponding to the first client 2 to obtain the supply-demand relationship model corresponding to the target pollutant discharge right indicator specified by the user; collect the historical trading information of the target pollutant discharge right indicator in the same period within the area where the user is located or within the tradable area of the target pollutant discharge right indicator; where the tradable area includes the area where the user is located; input the collected historical trading information into the supply-demand relationship model to predict the trading price range of the target pollutant discharge right indicator; send the predicted trading price range to the first client 2 for the user to refer to and determine the trading data; the trading data includes: the trading volume of the target pollutant discharge right indicator, the validity period corresponding to the target pollutant discharge right indicator, and the expected trading price range; respond to a second request sent by the user corresponding to the first client 2 to obtain the trading data; collect the trading intentions released by at least one seller and at least one buyer in the area where the user is located or within the tradable area of the trading platform; according to the trading data and the trading intentions released on the trading platform, use the trading matching algorithm to match at least one trading object; for at least one trading object, generate at least one set of trading matching plans; send at least one set of trading matching plans to the first client 2 for the user to refer to.

[0022] The first client 2 is used to respond to the input operation of the user on the trading page corresponding to the emission rights trading platform, obtain the target emission rights index, trading volume, and expiration date input by the user; receive and display the prediction information fed back by the server 1, where the prediction information includes the trading price range of the target emission rights index; obtain the trading data determined by the user after referring to the trading price range; the trading data includes the trading volume of the target emission rights index, the expiration date corresponding to the target emission rights index, and the expected trading price range; respond to the operation of the user uploading the trading data, and send the trading data to the server 1; the server 1 uses a trading matching algorithm to find at least one tradable object suitable for matching on the emission rights trading platform, and generate at least one set of trading matching plans for the at least one tradable object; receive and display at least one tradable object and at least one set of trading matching plans fed back by the server 1.

[0023] The second client 3, if it is a tradable object in the trading matching plan, receives the trading matching plan sent by the server 1 for the user to view.

[0024] In each embodiment of this application, the design of the emission rights trading platform can be based on the Browser / Server information framework in the Internet environment, adopting a three-tier architecture of a browser, a Web server, and a background database. The emission rights trading platform architecture, under the B / S three-tier architecture, includes a user presentation layer, a Web service layer, and a data service layer.

[0025] The user presentation layer is located on the client side, and its main task is to send service requests to the Web server and return results. Users mainly consist of polluting enterprises, organizations, trading centers, and the public, etc. Polluting enterprises purchase indexes, trade indexes, and maintain their own information through this platform. Government departments review the application information of polluting enterprises through this platform, summarize and statistically analyze pollution source information, etc. The trading center organizes transactions through this platform. The public supervises the trading information and the trading process.

[0026] The Web server layer is located on the Web server side, and its main task is to receive the requests of users, execute corresponding operations, send data processing requests to the database server, and transmit the obtained results to the client.

[0027] The data service layer is located on the data server side, and can share a computer with the Web server, or can be a separate data server, and is connected to the Web server through a network. The main task of the data service layer is to accept the requests of the Web server for database operations, implement functions such as querying, modifying, and updating the database, and submit the running results to the Web server. The databases included in the data service layer include the basic information database of polluting enterprises, the application index database, the trading information database, the pollution discharge permit database, the quota tracking and detection data, the index configuration database, the user permission database, and so on.

[0028] The technical solution provided in the embodiment of the present application can use the supply and demand relationship model corresponding to the pollution emission rights index to predict the transaction price range of the target pollution emission rights index for user reference; it also provides a transaction matching algorithm to match the user with at least one transaction object suitable for matching, so that the pollution emission rights trading has changed from a long-term search and waiting method such as listing or registration to an efficient matching mode. In addition, the solution of the embodiment of the present application also generates at least one set of transaction matching solutions for users, which makes user transactions more targeted, shortens the transaction cycle, is highly efficient, and helps to improve the transaction rate of pollution emission rights. It can be seen that the solution provided in the embodiment of the present application has a high degree of intelligence in the pollution emission rights trading platform, which can assist users in making trading decisions, and has a positive effect on maximizing the value of pollution emission rights while meeting the time requirements.

[0029] The following will explain the corresponding methods for each end from the perspective of each end in the system.

[0030] like Figure 2 A flow chart of an intelligent matching method for emission rights trading provided by an embodiment of the present application is shown. The method provided by this embodiment is applicable to the server corresponding to the emission rights trading platform. Among them, emission rights trading includes transfer and lease. Specifically, the method includes: 101. Responding to a first request sent by a user corresponding to a first client, obtaining a supply and demand relationship model corresponding to a target pollution discharge right indicator specified by the user; 102. Collect historical transaction information of the target emission rights indicator in the region to which the user belongs or in the tradable geographical area of ​​the target emission rights indicator in the same period; wherein the tradable geographical area includes the region to which the user belongs; 103. Input the collected historical transaction information into the supply and demand relationship model to predict the transaction price range of the target emission rights index; 104. Send the predicted transaction price range to the first client for the user to refer to and determine transaction data; the transaction data includes: the transaction volume of the target emission rights indicator, the validity period corresponding to the target emission rights indicator, and the expected transaction price range; 105. Respond to a second request sent by the first client corresponding to the user, and obtain the transaction data; 106. Collecting transaction intentions published by at least one seller and at least one buyer in the region to which the user belongs or in the tradable region on the transaction platform; 107. Match at least one transaction object using a transaction matching algorithm according to the transaction data and the transaction intention published on the transaction platform; 108. Generate at least one transaction matching plan for the at least one transaction object; 109. Send the at least one set of trading matching plans to the first client for the user's reference.

[0031] In the above 101, the pollutant discharge right indicators may include but are not limited to, for example, chemical oxygen demand, ammonia nitrogen, sulfur dioxide, nitrogen oxides, etc. For each pollutant discharge right indicator, a corresponding supply-demand relationship model is pre-constructed.

[0032] The supply-demand relationship model can be a model constructed based on neural network algorithms, with learning ability, and needs to be trained with training samples. The supply-demand relationship model has the ability to predict the supply-demand relationship, and can predict the relationship between the supply volume and demand volume of a certain indicator of pollutant discharge rights in the future period, which has guiding significance for estimating market prices and how organizations reasonably sell reserves, etc.

[0033] Correspondingly, in this embodiment, in addition to predicting the trading price range in 103, it can also give prediction suggestions for the pollutant discharge right transfer time range, transfer volume, etc.

[0034] In the above 106, the database on the server side stores the current seller's trading demands and the buyer's trading demands. The server can directly obtain from the database the trading intentions released by at least one seller and at least one buyer within the area where the user belongs or within the tradable area range on the trading platform. For the seller, the seller's trading intention may include but is not limited to: the volume to be transferred, the validity period of the pollutant discharge right, the price range, etc. For the buyer, the buyer's trading intention may include but is not limited to: the volume to be purchased, the validity period of the pollutant discharge right, the price range, etc.

[0035] The solution provided by the embodiment of the present application can, after the transferor applies to transfer the pollutant discharge right, assist the transferor in pricing, matching trading objects, and generating trading matching plans; it can also, after the transferor creates a session and the transferee signs up, assist the transferor in pricing, matching trading objects, and generating trading matching plans.

[0036] In the above 107, the trading matching algorithm may include multiple matching rules, and these multiple matching rules can be pre-configured on the server. The multiple matching rules may include but are not limited to: The regions where the two trading parties belong are within the range set to allow trading; The trading price is within the set deviation; The trading volumes match; The pollutant discharge right indicators are the same; The validity period of the seller's pollutant discharge right matches the buyer's demand period; And so on.

[0037] The matched trading partners can be one or more. If there are multiple matched trading partners, the trading matching plans generated for the multiple trading partners include: the tradable volume and trading price of each trading partner. For example, when the volume to be transferred by the seller is large and the volumes to be purchased by the buyers are all small, multiple buyers can be combined for the purchase. The volume to be transferred by the seller is A; the demand volume of the first trading partner is a1, and the demand volume of the second trading partner is a2; a1 + a2 is exactly equal to A. In this way, the seller can split the transfer volume and generate corresponding trading matching sub-plans for the first trading partner and the second trading partner respectively. These two trading matching sub-plans constitute a set of trading matching plans for the seller's reference. The trading matching sub-plan generated for the first trading partner can be sent to the first trading partner for its reference. The trading matching sub-plan generated for the second trading partner can be sent to the second trading partner for its reference.

[0038] The generated trading matching plans can be one set or two sets. For example, the volume to be transferred by the seller is A, and the demand volumes of the third trading partner and the fourth trading partner are both A during the same period. At this time, one set of trading matching plans can be generated for the third trading partner and another set of trading matching plans can be generated for the fourth trading partner for the seller's reference.

[0039] For another example, the transfer volume of the seller can be split into a1 and a2. One set of trading matching plans generated in this way is: split A into a1 and a2, trade the a1 volume with the first trading partner, and trade the a2 volume with the second trading partner.

[0040] Through the above matching, the seller's transfer volume can also be split into a3 and a4. Another set of trading matching plans generated in this way is to split A into a3 and a4, trade the a3 volume with the fifth trading partner, and trade the a4 volume with the sixth trading partner.

[0041] As above, when multiple sets of trading matching plans are generated in this embodiment, the trading partners in different sets of trading matching plans can be different, and the tradable volume and trading price of each corresponding trading partner can also be different.

[0042] For example, the trading price is the price negotiated by the buyer and the seller, which includes market factors, industry factors, regional factors, etc. Therefore, it is possible that the prices for the same pollution discharge right index are different for different buyers.

[0043] Furthermore, in the solution provided in this embodiment, when multiple sets of trading matching plans are generated, the method further includes: 110. Determine the trading plan preference of the user, and sort the multiple sets of trading matching plans based on the trading plan preference; and / or 111. Use artificial intelligence tools to analyze each set of transaction matching solutions to generate corresponding information on the advantages and disadvantages of the solutions for each set of transaction matching solutions; 112. When sending the at least one set of transaction matching solutions to the first client, send the sorted multiple sets of the transaction matching solutions and / or the multiple sets of the transaction matching solutions and the information on the advantages and disadvantages of each solution corresponding to each solution to the first client.

[0044] In the above 110, the user's preference for the transaction solution can be filled in by the user independently, or the server analyzes the user's transaction solution preference based on the user's historical transaction information. For example, the user is more inclined to trade with a trading partner in the same district or county, or is inclined to trade with a trading partner in the same industry, etc. Another example is that the user prefers to trade with one trading partner rather than multiple trading partners; at this time, the matching solutions including multiple trading partners can be ranked in a relatively later position.

[0045] Or in other feasible examples, without relying on user preferences, score each set of transaction matching solutions respectively based on a scoring strategy, with the ones with higher scores ranked in the front and the ones with lower scores ranked in the back.

[0046] In the above 111, the artificial intelligence tool can be a language model based on artificial intelligence technology deployed on the server side and having functions such as intelligent search, reasoning, and analysis. The form of the artificial intelligence tool on the client side can be: an intelligent agent that can interact with the user in a conversation interface or page. The form of the artificial intelligence tool on the server side is a language model, and this language model has been trained with a large amount of data. The user communicates with the intelligent agent through the client, and the intelligent agent can determine the user's intention through the conversation, and then collect materials based on the user's intention and generate a reply message as a response.

[0047] In this embodiment, the artificial intelligence tool can be called after being triggered by the user on the client side. For example, after multiple sets of transaction matching solutions are displayed on the client interface, the user can click on the target control (such as the "Generate Suggestions" control) on the interface after viewing to trigger the server to call the corresponding model of the artificial intelligence tool to analyze each set of transaction matching solutions. Of course, on the interface, each set of transaction matching solutions corresponds to a displayed control, and when the user touches the control corresponding to one set of transaction matching solutions, the server retrieves the corresponding model of the artificial intelligence tool to only analyze this set of transaction matching solutions. Or the artificial intelligence tool can also be automatically called by the server after generating multiple transaction matching solutions to analyze each solution and generate information on the advantages and disadvantages of the solutions.

[0048] The model corresponding to the artificial intelligence tool can analyze the risks of the user's transaction with the trading object by searching for the basic information of the trading object involved in the transaction matching solution (industry, region, historical transaction information, etc.) and combining the user's own information. The pros and cons information of the output solution may include, but is not limited to: risk level information (such as low risk, high risk, etc.), advice information on whether to adopt the solution, and so on.

[0049] Figure 3 The example diagram of the transaction page showing the matching solution is shown. Figure 3 In, multiple matching solutions are shown on the upper page, and each matching solution corresponds to a target control 7. Assuming that the user clicks on the target control 7 corresponding to "matching solution 1" on the page, a window such as Figure 3 shown in the lower part of the page will appear (of course, it may not be a window, such as it can jump to another page). The pros and cons information of the solution generated by the server-side artificial intelligence tool will be displayed in the window. Of course, the user can also enter text or voice in the input box 8 of the window to trigger the server-side artificial intelligence tool to generate more accurate pros and cons information of the solution through at least one round of conversation.

[0050] Or, after the user clicks on the target control 7 corresponding to "matching solution 1" on the page, a window in the page as shown in Figure 3 below does not appear or the page does not perform a page jump, and the pros and cons information of the solution generated by the server-side artificial intelligence tool is displayed in the pros and cons information display box corresponding to "matching solution 1".

[0051] Figure 3 It is shown that each matching solution corresponds to a target control. In fact, in specific implementation, there can be only one target control. After the user clicks on this target control, the pros and cons information of all matching solutions are respectively displayed in their corresponding display boxes.

[0052] As mentioned above, one type of pollutant discharge right index corresponds to one type of pollutant; different pollutant discharge right indexes correspond to different supply-demand relationship models. The supply-demand relationship model can be a model constructed based on neural network algorithms. The method provided in this embodiment may also include the process of model training. That is, the method provided in this embodiment further includes: 113. Obtain sample data, where the sample data includes transaction information within a region or within a tradable geographical area; among them, the transaction information includes: transaction time, transaction volume, transaction price, and the industries corresponding to the two trading parties respectively; 114. Use the sample data to train a preset model to obtain the supply-demand relationship model.

[0053] In actual applications, emission rights can be traded within the same district or county. Furthermore, some indicators can be traded within a larger scope, such as within a city; some indicators can be expanded to cross-city transactions; different emission rights indicators have different corresponding tradable geographical scopes, and cross-provincial transactions are not common at present.

[0054] Furthermore, the method provided in this embodiment may also include the following steps: 115. Based on the at least one set of transaction matching schemes, generate a transaction matching sub-scheme for any transaction object; the transaction matching sub-scheme only includes the transaction volume and transaction price related to the single transaction object; 116. Send the transaction matching sub-plan as recommendation information to the second client corresponding to the transaction object.

[0055] The technical solution provided in the embodiment of the present application can use the supply and demand relationship model corresponding to the pollution emission rights index to predict the transaction price range of the target pollution emission rights index for user reference; it also provides a transaction matching algorithm to match the user with at least one transaction object suitable for matching, so that the pollution emission rights trading has changed from a long-term search and waiting method such as listing or registration to an efficient matching mode. In addition, the solution of the embodiment of the present application also generates at least one set of transaction matching solutions for users, which makes user transactions more targeted, shortens the transaction cycle, is highly efficient, and helps to improve the transaction rate of pollution emission rights. It can be seen that the solution provided in the embodiment of the present application has a high degree of intelligence in the pollution emission rights trading platform, which can assist users in making trading decisions, and has a positive effect on maximizing the value of pollution emission rights while meeting the time requirements.

[0056] like Figure 4 A flow chart of an intelligent matching method for emission rights trading provided by another embodiment of the present application is shown. The method provided by this embodiment is applicable to a first client. Specifically, the method includes: 201. Respond to the user's input operation on the transaction page corresponding to the emission rights trading platform, and obtain the target emission rights index, transaction volume and validity period input by the user; 202. Receive and display the forecast information fed back by the server, wherein the forecast information includes the transaction price range of the target emission rights index; 203. Acquire transaction data determined by the user after referring to the transaction price range; the transaction data includes the transaction volume of the target emission rights indicator, the validity period corresponding to the target emission rights indicator, and the expected transaction price range; 204. In response to the user's operation of uploading the transaction data, send the transaction data to the server; the server uses a transaction matching algorithm to find at least one tradable object suitable for matching on the emission rights trading platform, and generate at least one set of transaction matching plans for the at least one tradable object; 205. Receive and display the at least one tradable object and at least one set of transaction matching plans fed back by the server.

[0057] In the above 202, the prediction information fed back by the server may include, in addition to the predicted transaction price range, predicted transaction time period information, trading volume, etc. This embodiment does not make specific limitations on this.

[0058] Further, the method provided in this embodiment may further include the following steps: 206. In response to the confirmation operation triggered by the user for one set of transaction matching plans on the transaction page, obtain one set of target transaction matching plans confirmed by the user; wherein, the target transaction matching plan includes the object identifiers of at least one tradable object and the trading volume corresponding to each tradable object; 207. Based on the object identifiers of at least one tradable object, send targeted invitation information to each tradable object in the target transaction matching plan through the emission rights trading platform.

[0059] Further, the first client is connected to the management system of the user's enterprise. Correspondingly, the method further includes: 208. When receiving the transaction demand triggered by the management system, send a notification message to the first client so that the user can learn about the enterprise's emission rights trading demand; Wherein, the management system is connected to the monitoring system, and the monitoring system collects the enterprise's pollutant emissions in real time; when the management system determines that the emissions of one type of pollutant are close to the quota threshold based on the pollutant emissions monitored by the monitoring system in real time, trigger a purchase demand for the pollutant, and / or when the management system predicts that the emissions of one type of pollutant need to be increased based on the pollutant emissions monitored by the monitoring system in real time and the enterprise's development plan, trigger a purchase demand for the pollutant, and / or when the management system evaluates that there is a surplus of the emission rights corresponding to one type of pollutant based on the pollutant emissions monitored by the monitoring system in real time and in combination with the enterprise's pollution control upgrade and transformation plan, estimate the surplus amount and trigger a transfer demand for the pollutant; The transfer demand includes assignment by agreement, sale and lease.

[0060] In summary, based on the characteristics of online transactions and emission rights, this application proposes an emission rights trading solution. The system (i.e., the server) can match both parties according to the data in the supply and demand information database and the requirements and preferences of the buyer and seller, and provide a reasonable matching solution. Among them, the supply and demand relationship model empowers users to propose trading intentions. The supply and demand relationship model can predict the supply and demand relationship at the current or future time periods, predict the emission rights price, the quantity transferred by the seller, and the quantity purchased by the buyer, and assist users in making decisions. The configuration of the trading matching algorithm improves the intelligence level of the trading platform, can actively facilitate the transactions between the buyer and the seller, and helps to change the trading methods, such as changing from the original methods of announcement, registration, bidding, and offering prices to the method of targeted invitation.

[0061] Matching refers to matching the supply and demand of emission rights and providing an appropriate trading solution. It follows certain principles, such as the price priority principle, the regional priority principle, etc. Bargaining negotiation refers to the transaction parties negotiating on specific transaction matters in the feasible solutions to try to optimize the interests of both parties. After the transaction is submitted, the information in the corresponding user information database, buy order database, sell order database, and supply and demand information database also needs to be modified and updated.

[0062] In this embodiment, according to the emission rights trading demand conditions of the buyer and the seller, and according to certain rules, a suitable trading object is selected, and through a trading matching algorithm (or called a matching algorithm), the proposed trading object, trading price, and trading volume are calculated to provide an ideal trading matching solution for the buyer or the seller. The buyer and the seller can refer to the matching solution provided by the system to determine the trading party, trading price, and trading volume.

[0063] As mentioned above, the trading matching algorithm in this embodiment can be a rule algorithm, such as including multiple matching rules. In addition, the trading matching algorithm in this embodiment can also be an emission rights trading matching model, and this matching model can be a multi-objective decision-making model. This multi-objective decision-making model needs to input relevant matching conditions, specifically including the net income of the enterprise's products, the emission volume, the buyer or seller, the industry to which it belongs, the required trading volume, etc.; on this basis, according to the matching rules, the matching model is used to give the proposed trading volume, trading price, and proposed trading party.

[0064] This matching model can be a model constructed based on an artificial intelligence (AI) matching algorithm, or a model constructed by other algorithms, and this embodiment does not make specific limitations on this.

[0065] After the technical solutions provided by the embodiments of this application generate a trading matching solution, the transferor can quickly determine the trading object and can quickly reach a consensus with the trading object to complete the transaction. Next, a simple introduction will be made to the trading process between the transferor and the transferee on the emission rights trading platform after the transferor and the transferee are determined based on the trading matching solution in combination with several specific application scenarios.

[0066] Furthermore, the embodiments of the present application also provide a solution. The basic idea is to connect multiple platforms. For example, connect the emission rights trading platform with the tax service platform. In this way, the emission rights trading parties can enter the tax service platform through the emission rights trading platform to pay taxes. After tax payment, without the operation of the taxpayer, the emission rights trading platform will automatically obtain the tax payment information. Of course, in addition to connecting the emission rights trading platform and the tax service platform, the financial open platform can also be connected with the emission rights trading platform, etc., to achieve multi-platform collaboration and intelligent full-link management.

[0067] The first server mentioned in the embodiments corresponding to the following scenarios is Figure 1 the server 1 in the illustrated embodiment, and the second server corresponds to the tax service platform.

[0068] Scenario 1: Transfer of organizational reserves The transferor is an organization (such as an environmental protection department or organization), and the transferee is an enterprise. After the transferor determines the transferee based on the transaction matching solution provided by the server, the process of creating a session and bidding can be omitted.

[0069] However, it should be noted here that the transferees who can be candidate trading objects and can enter the candidate pool have all been reviewed and approved by the competent department. Enterprises that have not been reviewed and approved cannot enter the candidate pool. For example, an enterprise with an application requirement logs in to the second client application and submits the purchase application materials through the first client. Among them, the purchase application materials may include, but are not limited to, the following contents: emission rights indicators (such as chemical oxygen demand, ammonia nitrogen, sulfur dioxide, or nitrogen oxides, etc.), purchase quantity, validity period, enterprise purchase qualification, etc. The first client can obtain the enterprise's purchase application materials through accessing the emission rights trading platform and approve them. If the approval is passed, the enterprise enters the enterprise buffer pool. After the first client creates a session, if there is an enterprise to be removed in the enterprise buffer pool, a removal application can be submitted at this stage. If the superior authority agrees to remove, it will be removed; if not, submit the removal application again. After determining the enterprises that can participate, confirm the session information and publicize it on the emission rights trading platform through the first server. Of course, if the system provided in this embodiment also connects the financial open platform, the first server can also send the session information to the third server to synchronously announce the session information on the financial open platform.

[0070] See Figure 5 As shown, the information interaction process among the second client of the enterprise side, the first client of the organizational side, and the server corresponding to the emission rights trading platform includes: S16. The first server sends a transaction and payment notice to the enterprise.

[0071] Among them, the payment notice can be a notice to notify the successful enterprise to pay the platform service fee.

[0072] After the enterprise receives the notice through the second client, it pays the platform service fee online, signs the contract and uploads it.

[0073] The organizational entity can obtain the contract signed by the enterprise from the first server through the first client and sign on the contract on which a consensus can be reached.

[0074] It should be supplemented here that the contract signed by the two trading parties can be drafted by either party. Of course, the emission rights trading platform provided in the embodiment of the present application, that is, the first server, has the function of automatically drafting contracts for the two trading parties, and the drafted contracts are applicable to emission rights trading. The two parties can adjust the drafted contract online or offline to reach an agreement. For the contract on which an agreement is reached, one party of the two parties can initiate the signing of the contract, and the other party can obtain the contract already signed by one party from the first server through the corresponding client, then sign the signature of its own party, and click submit (or upload) through the corresponding client (such as an application) to complete the signing of the contract by both parties.

[0075] S19. The first server determines the target emission rights index and tax information and sends a tax payment notice to the second client.

[0076] In specific implementation, the organizational entity can fill in the source of the emission rights index and tax information for this transaction through the first client. Of course, the first server can also calculate the tax information based on the transaction data (emission rights index, trading volume, etc.) of this transaction. Or, the first server sends the transaction data of this transaction and the enterprise identifier (i.e., the transferee identifier) to the tax service platform, and the third server calculates the tax information. The third server returns the tax information to the first server, and then the first server sends it to the second client.

[0077] S20. After receiving the tax payment notice, the enterprise enters the tax service platform through the second client and performs tax payment operations according to the tax payment process. The second server sends the tax payment information of the enterprise to the first server, or the first server obtains the tax payment information of the enterprise from the second server.

[0078] S21. After the first server determines that the enterprise has paid the tax, it judges whether the enterprise has paid the platform service fee. If it has been paid, the index transfer is executed. The first server sends an index quantity credit notice to the second client and at the same time sends an index quantity debit notice to the first client. In this way, the enterprise can view the index quantity credit notice, and the organizational entity can view the index quantity debit notice.

[0079] After the transfer of the emission rights from the transferor to the transferee, the first server can update the emission rights information corresponding to the organizational entity (i.e., the transferor) and the emission rights information corresponding to the enterprise (i.e., the transferee) in the emission rights information management database; and trigger the emission rights tracking and early warning system to update the emission rights early warning benchmarks corresponding to the transferor and the emission rights early warning benchmarks corresponding to the transferee.

[0080] Scenario 2: Transactions between enterprises The transaction methods for transactions between enterprises include: transfer and lease. Transfer includes: listed transaction, auction transaction and agreement transfer. Lease includes: agreement lease and listed lease. Among them, a listed transaction is that an enterprise lists for sale or purchase of emission rights on the emission rights trading platform, and the price is negotiated by the market. An auction transaction is organized by an organizational entity (such as an environmental protection department or organization) or an exchange for a public auction. An agreement transfer is a direct negotiation and transaction between enterprises, and it is necessary to file with the regulatory department.

[0081] This scenario is an agreement transfer or agreement lease between enterprises, and there is a cross-city transaction in this scenario. In an agreement transfer or agreement lease, there is no need for the supply-demand relationship model and transaction matching provided by the embodiments of the present application. This scenario belongs to the situation where both the transferor and the transferee have reached a consensus offline. In this scenario, the client corresponding to the transferor is called the first client, and the client corresponding to the transferee is the second client. The transferor and the transferee can be different factories of the same enterprise, or two different enterprises, etc. Specifically, such as Figure 6a and 6b , including the following steps: S21. The transferor completes the login through the first client, and then submits an agreement transfer or lease application to the first server through the first client.

[0082] Among them, the application may include but is not limited to: emission rights agreement transfer or lease indicators, indicator quantities, expiration dates, transferable qualifications of the transferor, etc. Obtain That is, for the transfer or lease of emission rights, approval is required. After the approval is passed, relevant qualifications can be obtained.

[0083] S22. The transferee completes the login through the second client, and then can obtain the agreement transfer or lease application submitted by the transferor from the first server through the second client. The transferee can supplement the application materials through the second client, such as supplementing the information of the area where the transferee is located, the relationship with the transferor, the qualifications that can undertake the agreement transfer or lease, etc.

[0084] After the transferee completes the supplementation of the application materials through the second client, it uploads them to the first server for approval by the competent unit.

[0085] S23. The co-competent unit can obtain the application materials through the third client and approve them.

[0086] It should be supplemented here that this scenario is a cross-city transaction. Assume that the transferor and the transferee are located in different cities but belong to the same province. Therefore, during the approval process, multi-level approvals are required, which are not detailedly drawn in the attached drawings corresponding to this embodiment. Specifically, it may include: S231. The district or county-level competent unit under the city where the transferor is located obtains the application materials from the first server through its corresponding client and approves them.

[0087] S232. The district or county-level competent unit under the city where the transferee is located obtains the application materials from the first server through its corresponding client and approves them.

[0088] S233. After the application materials pass the approval of the district or county-level competent unit under the city where the transferor is located and pass the approval of the district or county-level competent unit under the city where the transferee is located, the two district or county-level competent units conduct the first-level joint signature.

[0089] S234. After the two district or county-level competent units complete the joint signature, the first server triggers the approval by the municipal-level competent unit where the transferor is located and triggers the approval by the municipal-level competent unit where the transferee is located.

[0090] S235. The municipal-level competent unit where the transferor is located obtains the application materials after the first-level joint signature from the first server through its corresponding client and approves them.

[0091] S236. The municipal-level competent unit where the transferee is located obtains the application materials after the first-level joint signature from the first server through its corresponding client and approves them.

[0092] S237. After the application materials pass the approval of the municipal-level competent unit where the transferor is located and pass the approval of the municipal-level competent unit where the transferee is located, the two municipal-level competent units conduct the second-level joint signature.

[0093] S238. After the two municipal-level competent units complete the joint signature, the first server triggers the approval by the common competent unit (i.e., the provincial-level competent unit) of the transferor and the transferee.

[0094] As Figure 6a shown, the common competent unit of the transferor and the transferee obtains the application materials after the second-level joint signature from the first server through the third client and approves them.

[0095] S24. After the approval by the common competent unit, the first server responds to the approval passed instruction triggered by the third client and sends notifications to the transferor and the transferee respectively.

[0096] During specific implementation, the notifications can be sent by means of instant messaging applications, text messages or emails.

[0097] S25. After receiving the notification, the transferor can select the session time and create the session on the emission rights trading platform through the first client. The first server responds to the session creation event of the first client and generates session announcement information to be published on the emission rights trading platform.

[0098] S26. After the transferee views the announcement information of the session through the second client, he can pay a deposit online through the second client to participate in the transfer or lease session created by the transferor and make a bid.

[0099] S27. After the transferee pays the deposit and successfully bids, the first server determines the session result corresponding to the session created by the transferor.

[0100] In an implementable solution, the first server determines the result of the match, and when determining the result of the match, it is necessary to determine whether the transferee has breached the contract, whether the bid needs to be cancelled, etc. After the above judgment, the final match result is confirmed and announced.

[0101] In another feasible solution, the joint competent authority determines the results of the competition, and when determining the results of the competition, it is necessary to determine whether the transferee has breached the contract, whether the bid needs to be cancelled, etc. After the above judgment, the joint competent authority confirms the final results of the competition through the third client and triggers the first server to publicize it.

[0102] If the transferee breaches the contract, the first server sends a notification to the second client to notify the transferee to deduct the service fee from its deposit and impose a fine. If the transferee has a bid cancellation, the transferee is notified to cancel the bid and return the deposit. If the transferee has neither breached the contract nor has a bid cancellation, the transferee can receive a confirmation notification.

[0103] S28, the transferee pays the platform service fee through the second client. The first server responds to the transferee's completion of the platform service fee payment event, triggering the transferor and the transferee to sign a contract.

[0104] Among them, either the transferor or the transferee can initiate the drafting of the contract. This embodiment does not specifically limit this. In the embodiment shown in the figure, the transferor initiates the signing of the contract. In the specific implementation, it can be set that the contract can only be signed after the transferee has paid the platform service fee.

[0105] S29. The transferor signs the contract through the first client and uploads it.

[0106] S210: The transferee may obtain the contract signed by the transferor from the first server through the second client and sign the contract on which consensus can be reached.

[0107] S211. The transferor uploads the account voucher through the first client.

[0108] It should be noted here that: If the contract can only be signed after the transferee has paid the platform service fee, then the first server does not need to determine whether the transferee has paid the platform service fee. For example Figure 6b The example shown is when the system does not set the constraint of "the contract can only be signed after the transferee has paid the platform service fee", and the first server determines whether the transferee has paid the platform service fee. If so, it triggers the co-sponsoring unit to approve the vouchers uploaded by the transferor through the third client. After the approval, the co-sponsoring unit can use the third client to determine again whether to reject the bid. If not, the third client triggers the first server to refund the transferee's deposit and notify the transferee that the deposit has been withdrawn; if so, the third client triggers the first server to notify the transferee of the bid rejection and refund the deposit, and synchronously modify the public notice of the session results mentioned in step S16.

[0109] S212. The first server performs index transfer. The first server sends a notice of index quantity transfer into the second client, and at the same time sends a notice of index quantity transfer out to the first client. In this way, the transferee can view the notice of index quantity entry, and the transferor can view the notice of index quantity exit.

[0110] In the corresponding embodiment of this scenario, the emission rights are transferred or leased by agreement, and there is no tax payment. Therefore, the above steps do not involve tax payment content.

[0111] Scenario Three: Inter-enterprise Transactions This scenario is for enterprises to list for transfer, auction or list for lease. In this scenario, there are cross-city transactions. In this scenario, the client corresponding to the transferor is called the first client, and the client corresponding to the transferee is the second client. The process of this scenario is similar to Scenario One above. Based on the transaction matching scheme provided by the server, the transferor can already identify the transferee.

[0112] In this scenario, the transferor can complete the login through the first client, and then submit an application for agreement transfer or lease to the first server through the first client. The district or county-level competent unit of the transferor approves the application through the third client. After the approval, it enters the transaction database. The transferee can complete the login through the second client, and then submit an application for purchase or lease to the first server through the second client. The district or county-level competent unit of the transferee approves the application through the third client. After the approval, it enters the transaction database.

[0113] When the transferor and the transferee respectively clarify their intention to reach a transaction based on the transaction matching scheme, the co-sponsoring unit of the transferor and the transferee needs to approve both parties respectively to approve whether the transaction is compliant.

[0114] After the co-sponsoring unit approves, refer to the above in Scenario OneFigure 5 The first client corresponds to the transferor, and the second client corresponds to the transferee. For the specific process, please refer to the content above, which will not be elaborated here.

[0115] In this scenario, only the situation of the transferee paying taxes is shown. According to the actual situation, the transferor may also need to pay taxes, which needs to be determined according to relevant laws.

[0116] In this application, the pollutant discharge right trading platform is also connected to other platforms, such as the tax service platform, the financial open platform, etc. For example, data interaction is realized by calling the API provided by the pollutant discharge right trading platform. For cloud platform docking, a private network connection can be established through VPN, dedicated line (such as AWS Direct Connect) to realize data interaction between platforms.

[0117] In addition, in the solution provided by the embodiments of this application, the server can also provide a contract automatic generation function for the transferor or the transferee. Refer to Figure 7 the example shown. There is a control 9 of "generate contract" displayed on this interface, and this control 9 can also be called a contract generation control. When the user clicks this control 9, it can trigger the first server to call the artificial intelligence tool (such as an intelligent agent constructed and trained based on neural network algorithms) deployed on the server side to automatically generate contract information suitable for the transferor and the transferee and suitable for pollutant discharge right trading. In specific implementation, after the user clicks this control 9, a conversation page can be popped up or displayed on one side of the interface. The user can provide materials for the intelligent agent by means of text input, voice input or importing a draft. The intelligent agent can directly generate contract information based on the materials provided by the user. Of course, the user can also have multiple rounds of conversations with the intelligent agent to adjust and improve the contract information.

[0118] That is, each method embodiment of this application can include the following method steps: 301. After the transferor and the transferee reach a transaction intention and it is determined that the transferee has successfully paid the platform service fee, display a contract generation control on the transaction page corresponding to the pollutant discharge right trading platform; 302. Respond to the operation of the user (such as the transferor or the transferee) on the contract generation control, and display an artificial intelligence tool interaction page, so that the transferor can trigger the artificial intelligence tool to generate contract information that meets the user's needs and is suitable for pollutant discharge right trading by talking with the artificial intelligence tool on the interaction interface; 303. Respond to the confirmation instruction of the user on the contract information or the confirmation instruction after the user modifies and saves the contract information, and send the confirmed contract information to the client corresponding to the transaction object, so that the transaction object can review, adjust and confirm; 304. After the transferee and the transferor conduct at least one round of contract negotiation for the contract information through their respective corresponding clients, a target contract on which both parties reach an agreement is determined. 305. In response to the user's signing operation on the target contract, the signed target contract is sent to the first server, and the first server sends the target contract to the client corresponding to the trading partner for the trading partner to sign.

[0119] The solution provided in the embodiments of this application improves the intelligence of the pollution rights trading platform. The pollution rights trading platform not only serves as a trading platform for facilitating transactions, but also uses artificial intelligence tools to make the trading platform more intelligent, providing convenience for both trading parties.

[0120] In addition, in some of the processes described in the above embodiments and the accompanying drawings, there are multiple operations that appear in a specific order. However, it should be clearly understood that these operations may not be executed in the order in which they appear in this document or may be executed in parallel. The operation numbers such as 101, 102, etc. are only used to distinguish different operations, and the numbers themselves do not represent any execution order. In addition, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel. It should be noted that the descriptions such as "first" and "second" in this document are used to distinguish different messages, devices, modules, etc., and do not represent a sequence, nor do they limit that "first" and "second" are of different types.

[0121] Figure 8 It is a schematic structural diagram of an electronic device provided in the embodiments of this application. As Figure 8 shown, in practice, this electronic device includes a memory 54 and a processor 55.

[0122] The memory 54 is used to store computer programs and can be configured to store various other data to support operations on the electronic device. Examples of these data include instructions for any application program or method for operating on the electronic device, data structures, contact data, phone book data, messages, pictures, videos, etc.

[0123] The processor 55 is coupled to the memory 54 and is used to execute the computer programs in the memory 54 to implement the method steps in the above method embodiments. For the specific implementation steps, reference can be made to the above text and will not be elaborated here.

[0124] Further, as Figure 8 shown, this electronic device may further include other components such as a communication component 56, a display 57, a power supply component 58, an audio component 59, etc.

[0125] The above-mentioned memory can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read only memory (EEPROM), erasable programmable read only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0126] Accordingly, an embodiment of the present application further provides a computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to be able to implement the steps in the above method embodiment. Among them, the computer-readable storage medium includes volatile or non-volatile or a combination thereof, and can be removable or non-removable.

[0127] Accordingly, an embodiment of the present application further provides a computer program product, the computer program product includes a computer program or instruction, which, when executed by a processor, causes the processor to be able to implement the steps in the above method embodiment. It should be understood that each process or the combination of multiple processes in the above method flow can be implemented by the computer program or instruction. In addition, these computer programs or instructions can be applied to the processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing devices, so that the processor of the general-purpose computer, the special-purpose computer, the embedded processor or other programmable data processing devices can be used as a device to implement the corresponding functions in the above method embodiment.

[0128] The above are only the embodiments of the present application and are not used to limit the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the scope of the claims of the present application.

Claims

1. An intelligent matching method for emissions trading rights, characterized in that, Applicable to the server corresponding to the emission rights trading platform, and the emission rights trading includes transfer and lease; the method includes: Respond to a first request sent by a user corresponding to a first client, and obtain a supply-demand relationship model corresponding to a target emission right index specified by the user; Collect historical trading information of the target emission right index in the same period within the area where the user belongs or within the tradable geographical range of the target emission right index; wherein, the tradable geographical range includes the area where the user belongs; Input the collected historical trading information into the supply-demand relationship model to predict the trading price range of the target emission right index; Send the predicted trading price range to the first client for the user to refer to and determine trading data; the trading data includes: the trading volume of the target emission right index, the expiration date corresponding to the target emission right index, and the expected trading price range; Respond to a second request sent by the first client corresponding to the user, and obtain the trading data; Collect trading intentions released by at least one seller and at least one buyer in the area where the user belongs or within the tradable geographical range on the trading platform; According to the trading data and the trading intentions released on the trading platform, use a trading matching algorithm to match at least one trading object; Generate at least one set of trading matching plans for the at least one trading object; Send the at least one set of trading matching plans to the first client for the user to refer to.

2. The method according to claim 1, characterized in that When there are multiple matched trading objects, the trading matching plans generated for the multiple trading objects include: the tradable volume and trading price of each trading object; When multiple sets of trading matching plans are generated, the trading objects in different sets of trading matching plans can be different, and the tradable volume and trading price of each corresponding trading object can also be different.

3. The method according to claim 2, wherein When multiple sets of trading matching plans are generated, the method further includes: Determine the user's trading plan preference, and sort the multiple sets of trading matching plans based on the trading plan preference; and / or Use an artificial intelligence tool to analyze each set of trading matching plans to generate corresponding plan pros and cons information for each set of trading matching plans; When sending the at least one set of trading matching plans to the first client, send the sorted multiple sets of trading matching plans and / or the multiple sets of trading matching plans and the corresponding plan pros and cons information of each plan to the first client.

4. The method according to any one of claims 1 to 3, characterized in that One type of emission right index corresponds to one type of pollutant; different emission right indexes correspond to different supply-demand relationship models; and The method further includes: Obtain sample data, where the sample data includes trading information within an area or within a tradable geographical range; wherein, the trading information includes: trading time, trading volume, trading price, and the industries corresponding to both trading parties; Use the sample data to train a preset model to obtain the supply-demand relationship model.

5. The method according to any one of claims 1 to 3, characterized in that, It also includes: Based on the at least one set of trading matching plans, generate a trading matching sub-plan for any one trading object; this trading matching sub-plan only includes the trading volume and trading price related to a single trading object; Send the transaction matching sub - solution as recommended information to the second client corresponding to the transaction object.

6. An intelligent matching method for emission rights trading, characterized in that, Applicable to the first client, the method includes: Respond to the input operation of the user on the transaction page corresponding to the emission rights trading platform, and obtain the target emission rights index, trading volume, and expiration date input by the user. Receive and display the prediction information fed back by the server, where the prediction information includes the trading price range of the target emission rights index. Obtain the transaction data determined by the user after referring to the trading price range; the transaction data includes the trading volume of the target emission rights index, the expiration date corresponding to the target emission rights index, and the expected trading price range. Respond to the operation of the user uploading the transaction data, and send the transaction data to the server; the server uses a transaction matching algorithm to find at least one transaction object suitable for matching on the emission rights trading platform, and generate at least one set of transaction matching solutions for the at least one transaction object. Receive and display the at least one transaction object and at least one set of transaction matching solutions fed back by the server.

7. The method according to claim 6, characterized in that, It further includes: Respond to the confirmation operation triggered by the user for one set of transaction matching solutions on the transaction page, and obtain one set of target transaction matching solutions confirmed by the user; where the target transaction matching solution includes the object identifier of at least one transaction object and the trading volume corresponding to each transaction object. Based on the object identifiers of at least one transaction object, send targeted invitation information to each transaction object in the target transaction matching solution through the emission rights trading platform respectively.

8. The method according to claim 6, wherein The first client is connected to the management system of the user's enterprise, and the method further includes: When receiving the transaction demand triggered by the management system, send a notification message to the first client so that the user can learn about the enterprise's emission rights trading demand. Among them, the management system is connected to the monitoring system, and the monitoring system collects the enterprise's pollutant emissions in real - time; when the management system determines that the emission volume of one of the pollutants is close to the quota threshold based on the pollutant emissions monitored by the monitoring system in real - time, trigger the purchase demand for the pollutant, and / or when the management system predicts that the emission volume of one of the pollutants needs to be expanded based on the pollutant emissions monitored by the monitoring system in real - time and the enterprise's development plan, trigger the purchase demand for the pollutant, and / or when the management system evaluates that there is a surplus of the emission rights corresponding to one of the pollutants based on the pollutant emissions monitored by the monitoring system in real - time and in combination with the enterprise's pollution control upgrade and transformation plan, estimate the surplus amount and trigger the transfer demand for the pollutant; The transfer demand includes agreement transfer, sale, and lease.

9. A pollution rights trading system, characterized in that, It includes: A server that provides an emission rights trading platform, and the emission rights trading includes transfer and lease; the server is used to implement the emission rights trading intelligent matching method described in any one of claims 1 - 5 above. A first client corresponding to a user on the emission rights trading platform, and the first client is used to implement the emission rights trading intelligent matching method described in any one of claims 6 - 8 above.

10. An electronic device, characterized in that, It includes a memory and a processor, where, A memory for storing a computer program; A processor coupled to the memory for executing the computer program to implement the steps in the intelligent matching method for emissions trading rights according to any one of claims 1 to 8.

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