Transaction information determination method and device, computer equipment, readable storage medium and program product
By obtaining and analyzing the data asset information of transaction users, calculating their completeness, scarcity and accuracy indicators, and combining historical transaction information to evaluate transaction evaluation information, the problem of poor accuracy of power data asset transaction information in the existing technology is solved, and higher transaction reliability and fairness are achieved.
Patent Information
- Application Number
- CN202411656104.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-19
- Publication Date
- 2025-02-28
AI Technical Summary
The method of determining power data asset transaction information based on the cost method in the prior art has poor accuracy, resulting in low reliability of power data asset transactions.
By obtaining the data asset information of each transaction user, including identity information and load data packets, the integrity, scarcity and accuracy indicators of the data assets are calculated, and the transaction evaluation information of the transaction user is evaluated in combination with historical transaction information, and finally the transaction information is determined based on these indicators.
It improves the accuracy and fairness of transaction information, thereby improving the reliability and user participation of power data asset transactions, and avoiding resource waste.
Smart Images
Figure CN119539949A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of data processing technology, and in particular to a transaction information determination method, apparatus, computer equipment, computer-readable storage medium, and computer program product. Background Art
[0002] Power data assets refer to data resources that improve the efficiency of electricity production and consumption through integration and iteration with other production factors in the links of electricity production, storage, transmission, trading and consumption.
[0003] In the prior art, the transaction information of the power data assets is mostly determined by the cost method, so as to trade the power data assets according to the determined transaction information.
[0004] However, this method, which is based on the cost method to determine the transaction information of power data assets, has the problem of poor accuracy, which in turn leads to poor reliability of power data asset transactions. Summary of the invention
[0005] Based on this, it is necessary to provide a transaction information determination method, device, computer equipment, computer readable storage medium and computer program product to address the above technical problems, which can effectively improve the accuracy of transaction information and thereby improve the reliability of power data asset transactions.
[0006] In a first aspect, the present application provides a method for determining transaction information, comprising:
[0007] Acquire data asset information of each transaction user in the target data asset transaction, the data asset information including the identity information of the transaction user and the load data packet of the transaction user;
[0008] Determine the data asset integrity index, data asset scarcity index and data asset accuracy index of each transaction user based on the data asset information, and determine the transaction evaluation information of each transaction user based on the historical transaction information of each transaction user;
[0009] The transaction information of each transaction user is determined according to the data asset integrity index, the data asset scarcity index, the data asset accuracy index and the transaction evaluation information.
[0010] In one of the embodiments, the data asset integrity index, data asset scarcity index and data asset accuracy index of each transaction user are determined based on the data asset information, including: determining the data point information of the load data packet of each transaction user based on the data asset information, and determining the data asset integrity index of each transaction user based on the data point information; determining the load type of the data asset of each transaction user based on the data asset information, and determining the data asset scarcity index of each transaction user based on the load type; determining the data asset accuracy index of each transaction user based on the data asset information and the load type.
[0011] In one of the embodiments, the data asset integrity index of each transaction user is determined based on the data point information, including: determining the data point quantity information and the missing data point quantity information of the load data packet of each transaction user based on the data point information; determining the data asset integrity index of each transaction user based on the data point quantity information and the missing data point quantity information.
[0012] In one of the embodiments, the load type of the data assets of each transaction user is determined based on the data asset information, including: inputting the load data packet in the data asset information into a pre-trained load type determination model to obtain the load type of the data assets of each transaction user output by the load type determination model.
[0013] In one embodiment, the transaction evaluation information of each transaction user is determined based on the historical transaction information of each transaction user, including: determining the number of participations in data asset transactions and the number of successful transactions in data asset transactions of each transaction user based on the historical transaction information; determining the historical data asset transaction success rate of each transaction user based on the number of participations and the number of successful transactions, and determining the historical data asset transaction success rate as the transaction evaluation information of each transaction user.
[0014] In one of the embodiments, the transaction information of each transaction user is determined based on the data asset integrity index, the data asset scarcity index, the data asset accuracy index and the transaction evaluation information, including: determining the data asset quality information of each transaction user based on the data asset integrity index, the data asset scarcity index, the data asset accuracy index and the transaction evaluation information; determining the transaction information of each transaction user based on the data asset quality information and a Nash equilibrium algorithm.
[0015] In a second aspect, the present application further provides a transaction information determination device, comprising:
[0016] An acquisition module, used to acquire data asset information of each transaction user in the target data asset transaction, the data asset information including the identity information of the transaction user and the load data packet of the transaction user;
[0017] A determination module, used to determine the data asset integrity index, data asset scarcity index and data asset accuracy index of each transaction user according to the data asset information, and to determine the transaction evaluation information of each transaction user according to the historical transaction information of each transaction user;
[0018] An execution module is used to determine the transaction information of each transaction user based on the data asset integrity index, the data asset scarcity index, the data asset accuracy index and the transaction evaluation information.
[0019] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the method described in any embodiment of the first aspect when executing the computer program.
[0020] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in any embodiment of the first aspect above.
[0021] In a fifth aspect, the present application further provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the method described in any embodiment of the first aspect above.
[0022] The above-mentioned transaction information determination method, device, computer equipment, computer-readable storage medium and computer program product first obtain the data asset information of each transaction user in the target data asset transaction, and the data asset information includes the identity information of the transaction user and the load data packet of the transaction user; then determine the data asset integrity index, data asset scarcity index and data asset accuracy index of each transaction user according to the data asset information, and determine the transaction evaluation information of each transaction user according to the historical transaction information of each transaction user; finally, determine the transaction information of each transaction user according to the data asset integrity index, the data asset scarcity index, the data asset accuracy index and the transaction evaluation information. The transaction information determination method provided in the present application first determines various indicators of the data assets of each transaction user and the transaction evaluation information of each transaction user according to the data asset information of each transaction user, and then determines the transaction information of each transaction user according to the above content, which can effectively improve the accuracy and fairness of the determined transaction information, and thus effectively improve the reliability of power data asset transactions. BRIEF DESCRIPTION OF THE DRAWINGS
[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments of the present application or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.
[0024] Figure 1 A schematic diagram of a flow chart of a method for determining transaction information in one embodiment;
[0025] Figure 2 A flowchart of a method for determining the data asset integrity index, the data asset scarcity index and the data asset accuracy index of each transaction user according to the data asset information in one embodiment;
[0026] Figure 3 It is a flowchart of a method for determining the data asset integrity index of each transaction user according to the data point information in one embodiment;
[0027] Figure 4 It is a flowchart of a method for determining transaction evaluation information of each transaction user according to historical transaction information of each transaction user in one embodiment;
[0028] Figure 5 A flowchart of a method for determining the transaction information of each transaction user according to the data asset integrity index, the data asset scarcity index, the data asset accuracy index and the transaction evaluation information in one embodiment;
[0029] Figure 6 It is a flowchart of a method for determining transaction information in another embodiment;
[0030] Figure 7 is a structural block diagram of a transaction information determination device in one embodiment;
[0031] Figure 8 is an internal structure diagram of a computer device in one embodiment;
[0032] Fig. 9 A schematic diagram of the internal structure of a computer device in another embodiment;
[0033] Fig.10 A schematic diagram of a reference load curve of a lighting device in one embodiment;
[0034] Fig.11 A schematic diagram of a reference load curve of a bedroom socket in one embodiment;
[0035] Fig.12 A schematic diagram of a benchmark load curve of a living room socket in one embodiment;
[0036] Fig.13 A schematic diagram of a reference load curve of a kitchen socket in one embodiment;
[0037] Fig.14 A schematic diagram of a benchmark load curve of a household charging pile in one embodiment;
[0038] Fig.15 This is a schematic diagram of data asset quality information results in one embodiment;
[0039] Fig.16 A schematic diagram of the trajectory of the equilibrium profit share of both transaction users changing with the number of games in one embodiment;
[0040] Fig.17 This is a schematic diagram of the trajectory of the equilibrium profit share changing with the number of games after the commission collection ratio is adjusted in one embodiment. DETAILED DESCRIPTION
[0041] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.
[0042] Power data assets refer to data resources that improve the efficiency of electricity production and consumption through integration and iteration with other production factors in the links of electricity production, storage, transmission, trading and consumption.
[0043] In the prior art, the transaction information of the power data assets is mostly determined by the cost method, so as to trade the power data assets according to the determined transaction information.
[0044] However, this method, which is based on the cost method to determine the transaction information of power data assets, has the problem of poor accuracy, which in turn leads to poor reliability of power data asset transactions.
[0045] Furthermore, due to the poor reliability of power data asset transactions, users have low interest in participating in power data asset transactions, which also leads to a waste of power data asset resources.
[0046] In view of this, the present application provides a method for determining transaction information, which can effectively improve the accuracy of transaction information, thereby improving the reliability and fairness of power data assets, so as to stimulate users to participate in power data asset transactions and avoid waste of power data asset resources.
[0047] The transaction information determination method provided in the present application can be executed by a computer device, which can be a terminal or a server. The transaction information determination method can be used by a power data asset transaction controller to determine transaction information for each transaction user.
[0048] In an exemplary embodiment, Figure 1 As shown, a transaction information determination method is provided, the method comprising the following steps:
[0049] Step 101: Obtain data asset information of each transaction user in the target data asset transaction.
[0050] The data asset information includes the identity information of the transaction user and the load data packet of the transaction user.
[0051] Optionally, the data asset transaction refers to the act of buying, selling, exchanging or sharing power data assets, and the target data asset transaction refers to the data asset transaction of transaction information of a transaction user to be determined.
[0052] Optionally, the load data packet includes instantaneous values of voltage, current, active power, power consumption and power factor of each trading user at different preset measurement time points.
[0053] In some exemplary embodiments, the intelligent measurement terminal at the user side of the distribution network can be used to obtain all types of load data packets of each trading user, and the data asset information of each trading user can be determined based on the load data packet and the identity information of each trading user. Specifically, taking the jth trading user among all trading users as an example, the data asset information of the jth trading user can be expressed as ,in, Represents the data asset information of the jth transaction user, which consists of the identity information J of transaction user j and multiple types of load data packets of transaction user j composition, Numbers the payload packets.
[0054] Furthermore, the payload data packet It is composed of multi-attribute measurement values of the power load, that is, the instantaneous values of voltage, current, active power, power consumption and power factor at different preset measurement time points. The load data packet can be expressed as:
[0055] ,in, represents the column vector of preset measurement time points, Represents a column vector consisting of instantaneous voltage values at a preset measurement time point, Represents the column vector of instantaneous current values at the preset measurement time point, Represents a column vector consisting of instantaneous values of active power at a preset measurement time point, Represents a column vector consisting of instantaneous values of power consumption at a preset measurement time point, Represents a column vector of instantaneous values of power factor at preset measurement time points, where the interval between preset measurement time points is t and the total duration is T. is the number of preset measurement time points, .
[0056] Furthermore, the data asset information of all transaction users constitutes the distribution network user-side data asset data set , which is the data asset information of each transaction user. The data asset information of each transaction user can be expressed as .
[0057] Step 102: determine the data asset integrity index, data asset scarcity index and data asset accuracy index of each transaction user based on the data asset information, and determine the transaction evaluation information of each transaction user based on the historical transaction information of each transaction user.
[0058] In some exemplary embodiments, the data asset information can be input into pre-trained data asset integrity index determination models, data asset scarcity index determination models, and data asset accuracy index determination models, respectively, to obtain the data asset integrity index of each transaction user output by the data asset integrity index determination model, the data asset scarcity index of each transaction user output by the data asset scarcity index determination model, and the data asset accuracy index of each transaction user output by the data asset accuracy index determination model.
[0059] In other exemplary embodiments, the data point information of the load data packet of each transaction user may be determined based on the data asset information, and the data asset integrity index of each transaction user may be determined based on the data point information. The load type of the data asset of each transaction user may be determined based on the data asset information, and the data asset scarcity index of each transaction user may be determined based on the load type. The data asset accuracy index of each transaction user may be determined based on the data asset information and the load type.
[0060] As described above, when determining the data asset integrity index, data asset scarcity index and data asset accuracy index of each transaction user based on the data asset information, the transaction evaluation information of each transaction user can also be determined based on the historical transaction information of each transaction user.
[0061] In some exemplary embodiments, the historical transaction information of each transaction user may be input into a pre-trained transaction evaluation information determination model to obtain the transaction evaluation information of each transaction user output by the transaction evaluation information determination model.
[0062] In some other exemplary embodiments, the transaction evaluation information of each transaction user may also be determined based on a transaction evaluation information algorithm and historical transaction information of each transaction user.
[0063] Step 103: Determine the transaction information of each transaction user according to the data asset integrity index, the data asset scarcity index, the data asset accuracy index and the transaction evaluation information.
[0064] Optionally, the transaction information may be used to characterize the pricing of each transaction user's data asset in the target data asset transaction.
[0065] In some exemplary embodiments, the data asset integrity index, the data asset scarcity index, the data asset accuracy index and the transaction evaluation information may be input into a pre-trained transaction information determination model to obtain the transaction information of each transaction user.
[0066] In other exemplary embodiments, the data asset quality information of each transaction user may be determined based on the data asset integrity index, the data asset scarcity index, the data asset accuracy index and the transaction evaluation information; and the transaction information of each transaction user may be determined based on the data asset quality information and the Nash equilibrium algorithm.
[0067] The above-mentioned transaction information determination method first obtains the data asset information of each transaction user in the target data asset transaction, and the data asset information includes the identity information of the transaction user and the load data packet of the transaction user; then determines the data asset integrity index, data asset scarcity index and data asset accuracy index of each transaction user based on the data asset information, and determines the transaction evaluation information of each transaction user based on the historical transaction information of each transaction user; finally, determines the transaction information of each transaction user based on the data asset integrity index, the data asset scarcity index, the data asset accuracy index and the transaction evaluation information. The transaction information determination method provided in the present application first determines various indicators of the data assets of each transaction user and the transaction evaluation information of each transaction user based on the data asset information of each transaction user, and then determines the transaction information of each transaction user based on the above content, which can effectively improve the accuracy and fairness of the determined transaction information, and thus effectively improve the reliability of power data asset transactions.
[0068] In an exemplary embodiment, Figure 2As shown, determining the data asset integrity index, data asset scarcity index and data asset accuracy index of each transaction user according to the data asset information includes the following steps:
[0069] Step 201: Determine the data point information of the load data packet of each transaction user according to the data asset information, and determine the data asset integrity index of each transaction user according to the data point information.
[0070] Optionally, the data asset integrity indicator is used to characterize the integrity of each transaction user's data assets.
[0071] As mentioned above, the load data packet contains the instantaneous values of voltage, current, active power, power consumption and power factor of each trading user at different preset measurement time points. That is, the load data packet contains multiple instantaneous measurement values of different attributes, and each instantaneous measurement value can be used as a data point.
[0072] Optionally, the data point information includes data point quantity information and missing data point quantity information of each transaction user load data packet.
[0073] In some exemplary embodiments, the data point information of the load data packet of each transaction user can be first determined based on the data asset information. After the data point information is determined, the data point information can be input into a pre-trained data asset integrity indicator determination model to obtain the data asset integrity indicator of each transaction user output by the data asset integrity indicator determination model.
[0074] In other exemplary embodiments, the data point quantity information and the missing data point quantity information of each transaction user's load data packet can be first determined based on the data point information; and then the data asset integrity index of each transaction user can be determined based on the data point quantity information and the missing data point quantity information.
[0075] Step 202: Determine the load type of the data asset of each transaction user based on the data asset information, and determine the data asset scarcity index of each transaction user based on the load type.
[0076] In an optional embodiment of the present application, the load type of the data assets of each transaction user is determined based on the data asset information, including: inputting the load data packet in the data asset information into a pre-trained load type determination model to obtain the load type of the data assets of each transaction user output by the load type determination model.
[0077] Optionally, the load type determination model may be a long short-term neural network (Long Short-Term Memory, LSTM).
[0078] Exemplarily, the load type determination model can be trained based on the historical data of the data assets of each trading user. The training process of the load type determination model can be to use the historical data of the data assets as a training set, the model input is the preset measurement time point in the load data packet and the measured value of the active power, and the output is the load type.
[0079] Optionally, the data asset scarcity index can be used to characterize the scarcity of data assets of each trading user.
[0080] In some exemplary embodiments, after determining the load type of the data assets of each trading user, for each trading user, the scarcity index of the data assets of the trading user can be determined according to the load type of the trading user. Take the load data packet as an example to illustrate that the transaction user The scarcity index of payload data packets can be expressed as ,in, is the total number of load packets of all trading users, Load data packages and load data packages for all trading users The number of payload data packets with the same payload type. The above method is used to determine the scarcity index of data assets of each trading user.
[0081] Step 203: Determine the data asset accuracy index of each transaction user according to the data asset information and the load type.
[0082] In some exemplary embodiments, based on preset voltage threshold, current threshold, power factor threshold, abnormal voltage, current and power factor data points are determined from the load data packet, and the formula The abnormal data points of active power and power consumption are determined from the load data packet by accumulating power consumption. It should be noted that different load types correspond to different preset voltage thresholds, current thresholds, and power factor thresholds, which can be pre-set by technicians according to actual needs.
[0083] Furthermore, after the abnormal data point is determined, the data asset accuracy index of each trading user can be determined based on the abnormal data point. Take this as an example to illustrate that the load data packet The data asset accuracy index can be expressed as ,in, is the number of outliers.
[0084] In an exemplary embodiment, Figure 3As shown, determining the data asset integrity index of each transaction user according to the data point information includes the following steps:
[0085] Step 301, determining the data point quantity information and the missing data point quantity information of each transaction user load data packet according to the data point information;
[0086] Step 302: Determine the data asset integrity index of each transaction user according to the data point quantity information and the missing data point quantity information.
[0087] In some exemplary embodiments, after determining the data point quantity information and the missing data point quantity information of each transaction user's load data packet according to the data point information, the data asset integrity index of each transaction user can be determined according to the data point quantity information and the missing data point quantity information. Take this as an example to illustrate that the load data packet The data asset integrity index can be expressed as ,in, is the number of missing data points in the payload data packet.
[0088] In an exemplary embodiment, Figure 4 As shown, the process of determining the transaction evaluation information of each transaction user according to the historical transaction information of each transaction user includes the following steps:
[0089] Step 401: Determine the number of times each transaction user has participated in data asset transactions and the number of successful transactions of data asset transactions according to the historical transaction information;
[0090] Step 402: Determine the historical data asset transaction success rate of each transaction user according to the number of participations and the number of successful transactions, and determine the historical data asset transaction success rate as the transaction evaluation information of each transaction user.
[0091] In an exemplary embodiment, the number of times each transaction user has participated in data asset transactions and the number of successful transactions of data asset transactions can be determined based on the historical transaction information. After the number of times each transaction user has participated in data asset transactions and the number of successful transactions of data asset transactions are determined, the historical data asset transaction success rate of each transaction user can be determined based on the number of participations and the number of successful transactions. Specifically, taking transaction user j among the transaction users as an example, the historical data asset transaction success rate of transaction user j can be expressed as ,in, is the number of times transaction user j participated in data asset transactions, is the number of successful transactions of data assets by trading user j. It should be noted that adding 1 to the numerator and 2 to the denominator ensures that the historical data asset transaction success rate of trading user j is equal to 0.5 when the number of data asset transactions is 0.
[0092] In an exemplary embodiment, Figure 5 As shown, the transaction information of each transaction user is determined according to the data asset integrity index, the data asset scarcity index, the data asset accuracy index and the transaction evaluation information, including the following steps:
[0093] Step 501: Determine the data asset quality information of each transaction user according to the data asset integrity index, the data asset scarcity index, the data asset accuracy index and the transaction evaluation information.
[0094] In some exemplary embodiments, after determining the data asset integrity index, the data asset scarcity index, the data asset accuracy index and the transaction evaluation information, the data asset quality information of each transaction user can be determined based on the data asset integrity index, the data asset scarcity index, the data asset accuracy index and the transaction evaluation information. Specifically, the data asset quality information of each transaction user can be determined based on the data asset quality evaluation model. Taking the data asset quality assessment model as an example, the data asset quality assessment model can be expressed as ,in, Payload Packet Data asset quality information, , , , The preset weights can be set by technicians according to actual needs, and .
[0095] Step 502: Determine the transaction information of each transaction user according to the data asset quality information and the Nash equilibrium algorithm.
[0096] In some exemplary embodiments, after determining the data asset quality information of each trading user, for each trading user, the lowest price for each load data packet can be obtained, and the highest price of each load data packet purchaser can be obtained, and then the Nash equilibrium algorithm is determined based on the bargaining game framework. The Nash equilibrium algorithm can be expressed as ,in, For transaction information, Minimum pricing for load data packages, For the highest price, , They are the commission ratios charged by the data asset transaction controller to both transaction users; ; Constitute the profit space of the game.
[0097] In an exemplary embodiment, Figure 6 As shown, another transaction information determination method is provided, the method comprising the following steps:
[0098] Step 601: Acquire data asset information of each transaction user in the target data asset transaction, where the data asset information includes the identity information of the transaction user and the load data packet of the transaction user;
[0099] Step 602: determine the data point information of the load data packet of each transaction user according to the data asset information, determine the data point quantity information and the missing data point quantity information of the load data packet of each transaction user according to the data point information; determine the data asset integrity index of each transaction user according to the data point quantity information and the missing data point quantity information;
[0100] Step 603: input the load data packet in the data asset information into a pre-trained load type determination model to obtain the load type of the data asset of each transaction user output by the load type determination model; determine the data asset scarcity index of each transaction user according to the load type; determine the data asset accuracy index of each transaction user according to the data asset information and the load type;
[0101] Step 604: Determine the number of times each transaction user has participated in data asset transactions and the number of successful transactions of data asset transactions based on the historical transaction information; determine the historical data asset transaction success rate of each transaction user based on the number of participations and the number of successful transactions, and determine the historical data asset transaction success rate as the transaction evaluation information of each transaction user;
[0102] Step 605: determine the data asset quality information of each transaction user based on the data asset integrity index, the data asset scarcity index, the data asset accuracy index and the transaction evaluation information; determine the transaction information of each transaction user based on the data asset quality information and the Nash equilibrium algorithm.
[0103] In some exemplary embodiments, the inventors of the present application have verified the transaction information determination method provided by the present application to prove the effectiveness of the transaction information determination method provided by the present application. The transaction user data assets are modeled using the simulation data method. Considering the actual electricity consumption of household users, five types of equipment scene power load models are established, namely: lighting equipment, bedroom sockets, living room sockets, kitchen sockets and home charging piles. Its electricity consumption data covers five attributes: voltage, current, active power, power factor, and electricity consumption. The intelligent measurement terminal collects data once an hour, generates a load data packet every day, and participates in data sharing in units of load data packets. The voltage value designed in the model is: a normally distributed random number with a mean of 220 and a standard deviation of 10; the power factor index is designed as a normally distributed random number with a mean of 0.9 and a standard deviation of 0.05, and the maximum value is 1; the electricity consumption index is obtained by superimposing the value of the previous period with an increment based on the instantaneous power of the previous period; the simulation data of current and active power are based on the load curve of the actual equipment, based on the benchmark value and adding random errors. The benchmark load curve of the lighting equipment can be as follows Fig.10 As shown, the base load curve of bedroom sockets can be Fig.11 As shown, the base load curve of the living room socket can be Fig.12 As shown, the base load curve of the kitchen socket can be Fig.13 As shown in Figure 2, the benchmark load curve of a household charging pile can be Fig.14 shown.
[0104] Furthermore, based on the above model, 500 pieces of equipment power consumption data can be generated and used as data asset information, and evaluated to determine the corresponding transaction information. Specifically, , the data asset quality information results can be Fig.15 As shown in Table 1, some data indicators can be shown in Table 1. The equilibrium profit share of both trading users changes with the number of games as shown in Table 1. Fig.16 As shown in the figure, after adjusting the commission collection ratio, the equilibrium profit share changes with the number of games as shown in the figure. Fig.17 shown.
[0105] Table 1
[0106]
[0107] Depend on Fig.15 It can be seen that the data asset quality information results are basically in line with the normal distribution. For data asset data with higher values of each indicator, the higher the data asset quality score is, the higher the pricing corresponding to the transaction information obtained is. Fig.16It can be seen that when the game is played only once, the party that bids first (the seller) will take all the profits. As the number of games increases, the buyers and sellers (both trading users) continue to make concessions, and the final pricing will converge to the Nash equilibrium solution. Fig.16 and Fig.17 , when the commission ratio paid by the seller increases, the room for concession in each game becomes larger, and the final share of the profit will decrease.
[0108] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.
[0109] Based on the same inventive concept, the embodiment of the present application also provides a transaction information determination device for implementing the transaction information determination method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more transaction information determination device embodiments provided below can refer to the limitations of the transaction information determination method above, and will not be repeated here.
[0110] In an exemplary embodiment, Figure 7 As shown, a transaction information determination device 700 is provided, comprising: an acquisition module 701, a determination module 702 and an execution module 703, wherein:
[0111] An acquisition module 701 is used to acquire data asset information of each transaction user in a target data asset transaction, where the data asset information includes the identity information of the transaction user and the load data packet of the transaction user;
[0112] A determination module 702 is used to determine the data asset integrity index, the data asset scarcity index and the data asset accuracy index of each transaction user according to the data asset information, and to determine the transaction evaluation information of each transaction user according to the historical transaction information of each transaction user;
[0113] The execution module 703 is used to determine the transaction information of each transaction user according to the data asset integrity index, the data asset scarcity index, the data asset accuracy index and the transaction evaluation information.
[0114] In one embodiment, the determination module 702 is specifically used to determine the data point information of the load data packet of each transaction user based on the data asset information, and determine the data asset integrity index of each transaction user based on the data point information; determine the load type of the data asset of each transaction user based on the data asset information, and determine the data asset scarcity index of each transaction user based on the load type; determine the data asset accuracy index of each transaction user based on the data asset information and the load type.
[0115] In one embodiment, the determination module 702 is specifically used to determine the data point quantity information and the missing data point quantity information of each transaction user's load data packet based on the data point information; and determine the data asset integrity index of each transaction user based on the data point quantity information and the missing data point quantity information.
[0116] In one embodiment, the determination module 702 is specifically used to input the load data packet in the data asset information into a pre-trained load type determination model to obtain the load type of the data asset of each transaction user output by the load type determination model.
[0117] In one embodiment, the determination module 702 is specifically used to determine the number of participations in data asset transactions of each transaction user and the number of successful transactions in data asset transactions based on the historical transaction information; determine the historical data asset transaction success rate of each transaction user based on the number of participations and the number of successful transactions, and determine the historical data asset transaction success rate as the transaction evaluation information of each transaction user.
[0118] In one embodiment, the execution module 703 is specifically used to determine the data asset quality information of each transaction user based on the data asset integrity index, the data asset scarcity index, the data asset accuracy index and the transaction evaluation information; and determine the transaction information of each transaction user based on the data asset quality information and the Nash equilibrium algorithm.
[0119] Each module in the transaction information determination device can be implemented in whole or in part by software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each module.
[0120] In an exemplary embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Figure 8As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for determining transaction information is implemented.
[0121] In an exemplary embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as shown in FIG. Fig. 9 As shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, near field communication (NFC) or other technologies. When the computer program is executed by the processor, a method for determining transaction information is implemented. The display unit of the computer device is used to form a visually visible picture, which can be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.
[0122] Those skilled in the art will understand that Figure 8 and Fig. 9The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.
[0123] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:
[0124] Acquire data asset information of each transaction user in the target data asset transaction, the data asset information including the identity information of the transaction user and the load data packet of the transaction user;
[0125] Determine the data asset integrity index, data asset scarcity index and data asset accuracy index of each transaction user based on the data asset information, and determine the transaction evaluation information of each transaction user based on the historical transaction information of each transaction user;
[0126] The transaction information of each transaction user is determined according to the data asset integrity index, the data asset scarcity index, the data asset accuracy index and the transaction evaluation information.
[0127] In one embodiment, when the processor executes the computer program, the following steps are also implemented: determining the data point information of the load data packet of each transaction user based on the data asset information, and determining the data asset integrity index of each transaction user based on the data point information; determining the load type of the data asset of each transaction user based on the data asset information, and determining the data asset scarcity index of each transaction user based on the load type; determining the data asset accuracy index of each transaction user based on the data asset information and the load type.
[0128] In one embodiment, when the processor executes the computer program, the following steps are also implemented: determining the data point quantity information and the missing data point quantity information of each transaction user's load data packet based on the data point information; determining the data asset integrity index of each transaction user based on the data point quantity information and the missing data point quantity information.
[0129] In one embodiment, when the processor executes the computer program, the following steps are also implemented: the load data packet in the data asset information is input into a pre-trained load type determination model to obtain the load type of the data asset of each transaction user output by the load type determination model.
[0130] In one embodiment, when the processor executes the computer program, the following steps are also implemented: determining the number of participations in data asset transactions and the number of successful transactions in data asset transactions of each transaction user based on the historical transaction information; determining the historical data asset transaction success rate of each transaction user based on the number of participations and the number of successful transactions, and determining the historical data asset transaction success rate as the transaction evaluation information of each transaction user.
[0131] In one embodiment, when the processor executes the computer program, the following steps are also implemented: determining the data asset quality information of each transaction user based on the data asset integrity index, the data asset scarcity index, the data asset accuracy index and the transaction evaluation information; determining the transaction information of each transaction user based on the data asset quality information and the Nash equilibrium algorithm.
[0132] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:
[0133] Acquire data asset information of each transaction user in the target data asset transaction, the data asset information including the identity information of the transaction user and the load data packet of the transaction user;
[0134] Determine the data asset integrity index, data asset scarcity index and data asset accuracy index of each transaction user based on the data asset information, and determine the transaction evaluation information of each transaction user based on the historical transaction information of each transaction user;
[0135] The transaction information of each transaction user is determined according to the data asset integrity index, the data asset scarcity index, the data asset accuracy index and the transaction evaluation information.
[0136] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: determining the data point information of the load data packet of each transaction user based on the data asset information, and determining the data asset integrity index of each transaction user based on the data point information; determining the load type of the data asset of each transaction user based on the data asset information, and determining the data asset scarcity index of each transaction user based on the load type; determining the data asset accuracy index of each transaction user based on the data asset information and the load type.
[0137] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: determining the data point quantity information and the missing data point quantity information of each transaction user's load data packet based on the data point information; determining the data asset integrity index of each transaction user based on the data point quantity information and the missing data point quantity information.
[0138] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: the load data packet in the data asset information is input into a pre-trained load type determination model to obtain the load type of the data asset of each transaction user output by the load type determination model.
[0139] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: determining the number of participations in data asset transactions and the number of successful transactions in data asset transactions of each transaction user based on the historical transaction information; determining the historical data asset transaction success rate of each transaction user based on the number of participations and the number of successful transactions, and determining the historical data asset transaction success rate as the transaction evaluation information of each transaction user.
[0140] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented: determining the data asset quality information of each transaction user based on the data asset integrity index, the data asset scarcity index, the data asset accuracy index and the transaction evaluation information; determining the transaction information of each transaction user based on the data asset quality information and the Nash equilibrium algorithm.
[0141] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:
[0142] Acquire data asset information of each transaction user in the target data asset transaction, the data asset information including the identity information of the transaction user and the load data packet of the transaction user;
[0143] Determine the data asset integrity index, data asset scarcity index and data asset accuracy index of each transaction user based on the data asset information, and determine the transaction evaluation information of each transaction user based on the historical transaction information of each transaction user;
[0144] The transaction information of each transaction user is determined according to the data asset integrity index, the data asset scarcity index, the data asset accuracy index and the transaction evaluation information.
[0145] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: determining the data point information of the load data packet of each transaction user based on the data asset information, and determining the data asset integrity index of each transaction user based on the data point information; determining the load type of the data asset of each transaction user based on the data asset information, and determining the data asset scarcity index of each transaction user based on the load type; determining the data asset accuracy index of each transaction user based on the data asset information and the load type.
[0146] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: determining the data point quantity information and the missing data point quantity information of each transaction user's load data packet based on the data point information; determining the data asset integrity index of each transaction user based on the data point quantity information and the missing data point quantity information.
[0147] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: the load data packet in the data asset information is input into a pre-trained load type determination model to obtain the load type of the data asset of each transaction user output by the load type determination model.
[0148] In one embodiment, when the computer program is executed by the processor, the following steps are also implemented: determining the number of participations in data asset transactions and the number of successful transactions in data asset transactions of each transaction user based on the historical transaction information; determining the historical data asset transaction success rate of each transaction user based on the number of participations and the number of successful transactions, and determining the historical data asset transaction success rate as the transaction evaluation information of each transaction user.
[0149] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented: determining the data asset quality information of each transaction user based on the data asset integrity index, the data asset scarcity index, the data asset accuracy index and the transaction evaluation information; determining the transaction information of each transaction user based on the data asset quality information and the Nash equilibrium algorithm.
[0150] It should be noted that the user information (including but not limited to user device information, user identity information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.
[0151] A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., but are not limited to this.
[0152] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.
[0153] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.
Claims
1. A method for determining transaction information, characterized in that: The method comprises: Acquire data asset information of each transaction user in the target data asset transaction, wherein the data asset information includes identity information of the transaction user and a load data packet of the transaction user; Determine the data asset integrity index, data asset scarcity index and data asset accuracy index of each of the transaction users based on the data asset information, and determine the transaction evaluation information of each of the transaction users based on the historical transaction information of each of the transaction users; The transaction information of each of the transaction users is determined according to the data asset integrity index, the data asset scarcity index, the data asset accuracy index and the transaction evaluation information.
2. The method according to claim 1, characterized in that The determining of the data asset integrity index, data asset scarcity index and data asset accuracy index of each transaction user according to the data asset information includes: Determine the data point information of the load data packet of each of the transaction users according to the data asset information, and determine the data asset integrity index of each of the transaction users according to the data point information; Determine the load type of the data assets of each of the transaction users according to the data asset information, and determine the scarcity index of the data assets of each of the transaction users according to the load type; The data asset accuracy index of each of the transaction users is determined according to the data asset information and the load type.
3. The method according to claim 2, characterized in that Determining the data asset integrity index of each transaction user according to the data point information includes: Determine the data point quantity information and missing data point quantity information of each transaction user load data packet according to the data point information; The data asset integrity index of each of the transaction users is determined according to the data point quantity information and the missing data point quantity information.
4. The method according to claim 2, characterized in that: The determining the load type of the data asset of each transaction user according to the data asset information includes: The load data packet in the data asset information is input into a pre-trained load type determination model to obtain the load type of the data asset of each of the transaction users output by the load type determination model.
5. The method according to claim 1, characterized in that The determining the transaction evaluation information of each transaction user according to the historical transaction information of each transaction user includes: Determine the number of times each of the transaction users has participated in data asset transactions and the number of successful transactions of data asset transactions according to the historical transaction information; The historical data asset transaction success rate of each transaction user is determined according to the number of participations and the number of successful transactions, and the historical data asset transaction success rate is determined as the transaction evaluation information of each transaction user.
6. The method according to claim 1, characterized in that The determining the transaction information of each transaction user according to the data asset integrity index, the data asset scarcity index, the data asset accuracy index and the transaction evaluation information includes: Determining the data asset quality information of each of the transaction users according to the data asset integrity index, the data asset scarcity index, the data asset accuracy index and the transaction evaluation information; The transaction information of each of the transaction users is determined according to the data asset quality information and the Nash equilibrium algorithm.
7. A transaction information determination device, characterized in that: The device comprises: An acquisition module, used to acquire data asset information of each transaction user in the target data asset transaction, wherein the data asset information includes identity information of the transaction user and a load data packet of the transaction user; A determination module, used to determine the data asset integrity index, data asset scarcity index and data asset accuracy index of each of the transaction users according to the data asset information, and to determine the transaction evaluation information of each of the transaction users according to the historical transaction information of each of the transaction users; An execution module is used to determine the transaction information of each of the transaction users based on the data asset integrity index, the data asset scarcity index, the data asset accuracy index and the transaction evaluation information.
8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.
9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.
10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.