Data asset comprehensive evaluation system based on artificial intelligence and block chain

Abstract

The invention relates to the field of data asset evaluation, in particular to a data asset comprehensive evaluation system based on artificial intelligence and a block chain, comprising a block monitoring module used for determining the category of each data storage block; the verification evaluation module is used for determining whether verification optimization analysis and verification association analysis are carried out or not based on a change risk state, and the change risk state is determined according to a first-class block proportion index and a change conduction proportion index; the optimization verification module is used for determining whether to carry out time sequence verification analysis or effective verification analysis or not based on the change risk difference index of the auxiliary analysis set of each data storage block in one type of change risk state; and the association verification module is used for determining a conduction verification block based on the change risk index of the effective association block of each data storage block in the second-class change risk state. On the premise of ensuring the analysis efficiency of the data asset evaluation, the response timeliness of the change of the timeliness relationship of the block is ensured.

Description

Technical Field

[0001] This invention relates to the field of data asset valuation, and in particular to a comprehensive data asset valuation system based on artificial intelligence and blockchain. Background Technology

[0002] Because the time-sensitivity of data assets is prone to change, timely tracking and response to these changes are crucial during data asset valuation. While blockchain's immutability allows for the confirmation and tracking of data asset time-sensitivity, analyzing these changes often requires traversing the relationships between different blocks storing the data. As data volume increases, this leads to significant data analysis pressure. Therefore, a key challenge is finding a way to specifically monitor changes in data asset time-sensitivity, ensuring rapid response while reducing the overall data analysis burden.

[0003] Chinese Patent Publication No. CN119006165A discloses a data asset valuation method and system based on big data, relating to the field of data processing technology. The method includes collecting multi-source data, storing it in a central database, and uploading it to a blockchain for data ownership confirmation and recording; constructing a graph network of data assets based on the central database, capturing the temporal changes in data relationships within the graph network, and extracting node features from the graph network; identifying factors affecting the value of data assets based on the extracted node features, and constructing an asset valuation model to assess the value of the data assets. This invention constructs a graph network of data assets by collecting multi-source data and extracting node features from the graph network to identify factors affecting the value of data assets, and then constructs an asset valuation model for asset valuation. However, the above solution has the following drawbacks: it fails to make timely and effective assessments of the changes in the temporal relationships between different blocks, resulting in a high data analysis burden during the data asset valuation process, thus affecting the efficiency of generating actual valuation results. Summary of the Invention

[0004] To address this issue, the present invention provides a comprehensive data asset evaluation system based on artificial intelligence and blockchain, which overcomes the problem in existing technologies that fail to make timely and effective assessments of changes in the timeliness relationship between different blocks in light of actual circumstances, resulting in a large data analysis burden during the data asset evaluation process and thus affecting the efficiency of generating actual evaluation results.

[0005] To achieve the above objectives, this invention provides a comprehensive data asset evaluation system based on artificial intelligence and blockchain, comprising: The block monitoring module is used to determine the category of each data storage block based on the change risk index, which is determined based on the update stability index and update limit index of each data storage block. The verification and evaluation module is connected to the block monitoring module and is used to determine whether to perform verification optimization analysis and verification correlation analysis for each data storage block based on the change risk status of each data storage block. The change risk status is determined based on the proportion index of a type of block and the change transmission proportion index. An optimized verification module, which is connected to the verification evaluation module, is used to determine whether to perform time-series verification analysis or effective verification analysis for each data storage block based on the change risk difference index of the auxiliary analysis set of each data storage block in a change risk state. The module determines the transmission verification block based on the time-series matching evaluation index, or determines the transmission verification block based on the direct link parameters or the target overlap transmission index. The associated verification module, which is connected to the verification evaluation module, is used to determine the transmission verification block based on the change risk index of the effective associated blocks of each data storage block in the second-class change risk state.

[0006] Furthermore, the data storage blocks are categorized into two types: Class I data storage blocks and Class II data storage blocks. The block monitoring module classifies data storage blocks whose change risk index is greater than the preset change risk index as a type of data storage block. The block monitoring module classifies data storage blocks whose change risk index is less than or equal to the preset change risk index as Class II data storage blocks.

[0007] Furthermore, the change risk status includes a first-class change risk status and a second-class change risk status; The verification and evaluation module records data storage blocks that have a Class I block proportion index greater than a preset Class I block proportion index or a change transmission proportion index greater than a preset change transmission proportion index as data storage blocks in a Class I change risk state. The verification and evaluation module records data storage blocks that have a Class I block proportion index less than or equal to a preset Class I block proportion index and a change transmission proportion index less than or equal to a preset change transmission proportion index as data storage blocks in a Class II change risk state.

[0008] Furthermore, the optimization verification module performs verification optimization analysis on data storage blocks in a state of risk of change to determine the transmission verification blocks for those data storage blocks. The change risk difference index of any auxiliary analysis set is determined based on the change risk index of each data storage block within the auxiliary analysis set; The configuration of the auxiliary analysis set is determined based on the reference conduction cross index of the data storage block; The verification validity index of any of the aforementioned transmission verification blocks is greater than the preset verification validity index.

[0009] Furthermore, the optimization verification module performs time-series verification analysis on the auxiliary analysis set where the change risk difference index is greater than the preset change risk difference index; The validation validity index of the data storage block corresponding to this auxiliary analysis set is determined based on the time-series matching evaluation index.

[0010] Furthermore, the optimization verification module performs effective verification analysis on the auxiliary analysis set where the change risk difference index is less than or equal to the preset change risk difference index, wherein, Based on the direct link parameters of each change transmission block within the auxiliary analysis set, determine whether to determine the verification validity index according to the target overlap transmission index of the corresponding change transmission block; The optimization verification module determines the verification validity index of the change transmission block whose direct link parameter is less than or equal to the preset direct link parameter based on the target overlap transmission index. The optimization verification module determines the verification validity index of change transmission blocks whose direct link parameters are greater than the preset direct link parameters based on the direct link parameters.

[0011] Furthermore, the optimization verification module determines an auxiliary analysis set of data storage blocks whose reference cross-index is greater than a preset reference cross-index based on the set conduction cross-index. The optimization verification module determines an auxiliary analysis set of data storage blocks whose reference conduction cross-index is less than or equal to a preset reference conduction cross-index based on the target conduction index of the set.

[0012] Furthermore, the association verification module performs verification association analysis on data storage blocks in a Class II change risk state, and determines the transmission verification block of the data storage block based on the effective reference risk index; The transmission verification block is a valid associated block whose effective reference risk index is greater than the preset effective reference risk index. The effective reference risk index is determined based on the change risk index of the valid associated blocks of the data storage block.

[0013] Furthermore, the association verification module determines the valid associated blocks of each data storage block in the Class II change risk state based on the overlap transmission index; The overlap transmission index of any valid associated block to its corresponding data storage block is greater than the preset overlap transmission index.

[0014] Furthermore, the change risk index of any data storage block is positively correlated with the update stability index and update limit index of the corresponding data storage block.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: the technical solution of the present invention determines the category of each data storage block according to the change risk index to initially determine the change risk of the timeliness relationship of each data storage block, and determines the change risk status according to the block proportion index of each data storage block and the change transmission proportion index, so as to determine the targeted verification and evaluation of each data storage block, and timely determine the direct or potential change transmission relationship between the data storage blocks. This provides an auxiliary judgment on the change of timeliness relationship in the data asset assessment analysis process. The present invention ensures the efficiency of data asset assessment analysis and the timeliness of response to changes in the timeliness relationship of data storage blocks.

[0016] Furthermore, in this invention, the change risk status is determined based on the proportion index of a type of block and the change propagation proportion index of each data storage block. This characterizes the analytical burden of the correlation between the initially determined change propagation block and the timeliness relationship change of the data storage block, thereby achieving differentiated evaluation, ensuring the effectiveness of the evaluation scheme for the data storage block, avoiding uniform analysis of all blocks, and ensuring the effectiveness of the propagation verification block determined for each data storage block.

[0017] Furthermore, during the verification and optimization analysis in this invention, since there are relatively many change transmission blocks or change transmission blocks with poor regularity in the timeliness of changes in data storage blocks in a certain change risk state, the analysis burden of analyzing the transmission correlation between the initially determined change transmission blocks and the timeliness changes of the data storage blocks is relatively heavy. Therefore, it is necessary to ensure the efficiency of data analysis in the actual analysis process. Based on the reference transmission cross index, the setting scheme of the auxiliary analysis set is determined to ensure that the setting process of the determined auxiliary analysis set is more in line with the actual situation, and further ensures the degree of temporal correlation between data storage blocks within the auxiliary analysis set. According to the change risk difference index of each auxiliary analysis set, the screening process of transmission verification blocks for each auxiliary analysis set is set in a targeted manner, so that the determined transmission verification blocks are more in line with the actual situation, thereby ensuring the timeliness of response to changes in the timeliness of data storage blocks.

[0018] Furthermore, during the verification correlation analysis in this invention, since the differences in the suddenness of the update of the timeliness relationship among the change transmission blocks of the data storage blocks in the second-class change risk state are small, it indicates that some change transmission blocks have timeliness relationship changes that conform to the actual change rules. It is necessary to further analyze whether there is a clear transmission situation between each change transmission block and the change of the timeliness relationship of the data storage block, and to rule out the possibility of normal execution of timeliness relationship changes. The correlation verification module mines effective correlation blocks through the overlap transmission index and filters transmission verification blocks in combination with the effective reference risk index to ensure the effective correlation between the determined transmission verification blocks and the corresponding data storage blocks. Attached Figure Description

[0019] Figure 1 This is a module connection diagram of the data asset comprehensive evaluation system based on artificial intelligence and blockchain of the present invention; Figure 2 This is a flowchart illustrating how the present invention determines the category of each data storage block based on a change risk index; Figure 3 This is a flowchart illustrating the process of determining whether to perform verification optimization analysis and verification correlation analysis for each data storage block based on the change risk status of each data storage block in this invention. Figure 4 This is a flowchart illustrating how the present invention determines whether to perform time-series verification analysis or effective verification analysis on each data storage block based on the change risk difference index. Detailed Implementation

[0020] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0021] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0022] It should be noted that in the description of this invention, the terms "upper", "lower", "left", "right", "inner", "outer", etc., which indicate directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and is not intended to indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0023] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0024] Please see Figures 1 to 4 As shown, this invention provides a comprehensive data asset evaluation system based on artificial intelligence and blockchain, comprising: The block monitoring module is used to determine the category of each data storage block based on the change risk index, which is determined based on the update stability index and update limit index of each data storage block. The verification and evaluation module is connected to the block monitoring module and is used to determine whether to perform verification optimization analysis and verification correlation analysis for each data storage block based on the change risk status of each data storage block. The change risk status is determined based on the proportion index of a type of block and the change transmission proportion index. An optimized verification module, which is connected to the verification evaluation module, is used to determine whether to perform time-series verification analysis or effective verification analysis for each data storage block based on the change risk difference index of the auxiliary analysis set of each data storage block in a change risk state. The module determines the transmission verification block based on the time-series matching evaluation index, or determines the transmission verification block based on the direct link parameters or the target overlap transmission index. The associated verification module, which is connected to the verification evaluation module, is used to determine the transmission verification block based on the change risk index of the effective associated blocks of each data storage block in the second-class change risk state.

[0025] This invention is used to monitor changes in the timeliness of data assets to be assessed during the data asset evaluation process. Since the timeliness of data assets has a significant impact on the actual evaluation results, it is necessary to ensure timely response to changes in the timeliness of data assets. Therefore, it is necessary to continuously analyze the transmission relationship of changes in the timeliness of data assets corresponding to each block in order to reduce the data burden of the actual analysis process. In this invention, data assets are stored based on blockchain technology, and there are several data storage blocks. Each data storage block corresponds to the storage of some data assets whose timeliness changes need to be monitored. This invention utilizes several change assessment records. Each change assessment record records at least one change risk index, change propagation correlation index, first-class block proportion index, change propagation proportion index, verification validity index, direct link parameter, set propagation cross index, set target propagation index, reference propagation cross index, overlap propagation index, and effective reference risk index during the change assessment process for the timeliness relationship of the target analysis asset. Each change assessment record also has a corresponding qualification mark. The qualification mark records whether the timeliness and analysis efficiency of the response process to the change in the timeliness relationship of the target analysis asset meet the user's needs. It can be understood that the user can determine whether the timeliness and analysis efficiency of the response process to the change in the timeliness relationship of the target analysis asset meet the user's needs based on self-defined indicators.

[0026] Specifically, the data storage blocks are categorized into two types: Class I data storage blocks and Class II data storage blocks. The block monitoring module classifies data storage blocks whose change risk index is greater than the preset change risk index as a type of data storage block. The block monitoring module classifies data storage blocks whose change risk index is less than or equal to the preset change risk index as Class II data storage blocks.

[0027] In this invention, a cyclical risk assessment cycle is applied. The duration of the risk assessment cycle can be determined by the user. The higher the user's requirements for the timeliness of the response process to changes in the timeliness of the target analysis asset's relationship and the efficiency of the analysis, the shorter the duration of the risk assessment cycle. One possible duration of the risk assessment cycle is 12 hours. At the end of each risk assessment cycle, the change risk index of each data storage block is detected to determine the category of each data storage block and the change risk status of each data storage block. For a single data storage block, the change risk index is used to characterize whether the update process of the timeliness relationship of the data storage block has an update pattern or a clear update direction. If the change risk index of the data storage block is greater than the preset change risk index, it indicates that the update stability index or update limit index of the data storage block is larger, that is, the update process of the data storage block does not have a time pattern or a clear update direction. The data storage block is recorded as a Class I data storage block. Otherwise, it is recorded as a Class II data storage block. The value of the preset change risk index can be determined by the user based on the actual work scenario. For example, the user can set it based on the change assessment record. The higher the user's requirements for the timeliness of the response process to changes in the timeliness of the target asset's relationship with the change and the efficiency of the analysis, the smaller the value of the preset change risk index. A method for determining the value of the preset change risk index is provided, which is the minimum value of the change risk index of a type of data storage block in the change assessment record that meets the user's requirements for the timeliness of the response process to changes in the timeliness of the target asset's relationship with the change and the efficiency of the analysis.

[0028] Specifically, the change risk status includes a first-class change risk status and a second-class change risk status; The verification and evaluation module records data storage blocks that have a Class I block proportion index greater than a preset Class I block proportion index or a change transmission proportion index greater than a preset change transmission proportion index as data storage blocks in a Class I change risk state. The verification and evaluation module records data storage blocks that have a Class I block proportion index less than or equal to a preset Class I block proportion index and a change transmission proportion index less than or equal to a preset change transmission proportion index as data storage blocks in a Class II change risk state.

[0029] Wherein, if the current moment is the end of a risk assessment cycle, the risk assessment cycle is recorded as the analysis execution cycle, the category of each data storage block and its change risk status are determined, and for a single data storage block, the proportion index of the first type of block is... , This represents the number of change propagation blocks present in this data storage block. The change propagation ratio index represents the number of one type of data storage block within the change propagation blocks of this data storage block. , This represents the number of change propagation blocks present in this data storage block. The number of existing data storage blocks is defined as follows: the change propagation block is a data storage block whose change propagation correlation index is less than or equal to a preset change propagation correlation index. For any data storage block other than the aforementioned data storage block, the change propagation correlation index is the average of the time intervals corresponding to each change in the timeliness relationship between the two data storage blocks during the analysis and evaluation phase. If a change in the timeliness relationship occurs in one data storage block, the time interval between the time of the change in the timeliness relationship of the other data storage block and that time is recorded as the time interval corresponding to the change in the timeliness relationship. The end time of the analysis and evaluation phase is the end time of the analysis execution cycle. The duration of the analysis and evaluation phase can be determined by the user according to the actual work scenario. One analysis and evaluation phase duration is provided, which is 15 days. The value of the preset change transmission correlation index can be determined by the user based on the actual work scenario. For example, the user can set it based on the change assessment record. The higher the user's requirements for the timeliness and efficiency of the response process to changes in the timeliness of the target analysis asset, the larger the value of the preset change transmission correlation index. A method for determining the value of the preset change transmission correlation index is provided, which is the average value of the change transmission correlation index of the change transmission block in the change assessment record that meets the user's requirements for the timeliness and efficiency of the response process to changes in the timeliness of the target analysis asset. The values ​​of the preset Class I block proportion index and the preset change transmission proportion index can be determined by the user based on the actual work scenario. For example, the user can set them based on change assessment records. The higher the user's requirements for the timeliness and efficiency of the response process to changes in the timeliness relationship of the target analyzed asset, the smaller the value of the preset Class I block proportion index and the preset change transmission proportion index. A method for determining the value of the preset Class I block proportion index is provided, which is the maximum value of the Class I block proportion index of data storage blocks in the change assessment record that meets the user's requirements for the timeliness and efficiency of the response process to changes in the timeliness relationship of the target analyzed asset and is in a Class II change risk state. A method for determining the value of the preset change transmission proportion index is provided, which is the maximum value of the change transmission proportion index of data storage blocks in the change assessment record that meets the user's requirements for the timeliness and efficiency of the response process to changes in the timeliness relationship of the target analyzed asset and is in a Class II change risk state.

[0030] Specifically, the optimization verification module performs verification optimization analysis on data storage blocks in a state of risk of change to determine the transmission verification blocks for that data storage block. The change risk difference index of any auxiliary analysis set is determined based on the change risk index of each data storage block within the auxiliary analysis set; The configuration of the auxiliary analysis set is determined based on the reference conduction cross index of the data storage block; The verification validity index of any of the aforementioned transmission verification blocks is greater than the preset verification validity index.

[0031] Specifically, for a single data storage block, if the data storage block is in a Class I change risk state, it indicates that the data storage block has a large number of change propagation blocks or that a large proportion of the change propagation blocks are Class I data storage blocks. In the process of analyzing the correlation between the timeliness changes of data storage blocks for this data storage block, the analysis of the correlation between the initially identified change propagation blocks and the timeliness changes of this data storage block is quite burdensome because there are a relatively large number of change propagation blocks with rich change propagation blocks or relatively poor regularity in the change of timeliness. Therefore, verification and optimization analysis is performed on this data storage block to ensure the data analysis efficiency in the actual analysis process. For a single data storage block in a change risk state, an auxiliary analysis set is created based on the change propagation blocks present in that data storage block. This is used to verify the effectiveness of the propagation correlation between the timeliness of changes in the data storage block and its existing change propagation blocks, aiming to identify change propagation blocks with strong propagation correlations between timeliness changes and improve actual analysis efficiency. For a single auxiliary analysis set, the change risk difference index... , This represents the standard deviation among the change risk indices of each change propagation block within this auxiliary analysis set. This is the average change risk index of each change propagation block within this auxiliary analysis set; The value of the preset verification validity index can be determined by the user based on the actual work scenario. For example, the user can set it based on the change assessment record. The higher the user's requirements for the timeliness and efficiency of the response process to changes in the timeliness of the target analysis asset's relationship, the larger the value of the preset verification validity index. A method for determining the value of the preset verification validity index is provided, which is the minimum value of the verification validity index of the transmission verification block in the change assessment record that meets the user's requirements for the timeliness and efficiency of the response process to changes in the timeliness of the target analysis asset's relationship.

[0032] Specifically, the optimization verification module performs time-series verification analysis on the auxiliary analysis set where the change risk difference index is greater than the preset change risk difference index; The validation validity index of the data storage block corresponding to this auxiliary analysis set is determined based on the time-series matching evaluation index.

[0033] Specifically, for any auxiliary analysis set of a single data storage block in a Class I change risk state, if the change risk difference index of the auxiliary analysis set is greater than the preset change risk difference index, it indicates that although there is a certain time correlation between the time-related changes that occur among the data storage blocks in the auxiliary analysis set during the analysis and evaluation phase, there is a significant difference in the degree of suddenness of the update of the time-related relationship among the actual change transmission blocks. This indicates that some change transmission blocks that have experienced time-related changes may be due to changes in the time-related relationships of their corresponding data storage blocks. By performing time-series verification analysis on the auxiliary analysis set, the data storage blocks that actually have a strong change transmission correlation with the data storage block in the Class I change risk state are further identified, ensuring the effective identification of direct or potential correlations. The time-series matching evaluation index characterizes the degree of difference between the time-series intervals corresponding to each time-related change, thereby characterizing the effective persistence of the change transmission correlation. For any change propagation block within a single auxiliary analysis set, the time-series matching evaluation index , This represents the average time interval for each occurrence of a time-related change in the data storage block corresponding to the auxiliary analysis set during the analysis and evaluation phase. The standard deviation between the time intervals corresponding to each change in the time relationship of the data storage block corresponding to the auxiliary analysis set during the analysis and evaluation phase of the change transmission block is normalized for the determined time-series matching evaluation index. The normalized time-series matching evaluation index is recorded as the verification validity index of the change transmission block.

[0034] Specifically, the optimization verification module performs effective verification analysis on the auxiliary analysis set where the change risk difference index is less than or equal to the preset change risk difference index, wherein, Based on the direct link parameters of each change transmission block within the auxiliary analysis set, determine whether to determine the verification validity index according to the target overlap transmission index of the corresponding change transmission block; The optimization verification module determines the verification validity index of the change transmission block whose direct link parameter is less than or equal to the preset direct link parameter based on the target overlap transmission index. The optimization verification module determines the verification validity index of change transmission blocks whose direct link parameters are greater than the preset direct link parameters based on the direct link parameters.

[0035] Specifically, for any auxiliary analysis set of a single data storage block in a Class I change risk state, if the change risk difference index of the auxiliary analysis set is less than or equal to the preset change risk difference index, it indicates that there is a certain time correlation between the timeliness relationship changes that occur between the data storage blocks in the auxiliary analysis set during the analysis and evaluation phase, and the difference in the degree of update regularity of the timeliness relationship between the change transmission blocks is also small. Further effective verification analysis is conducted to ensure the effectiveness of the transmission verification block determined for the data storage block in a Class I change risk state. For any change transmission block within a single auxiliary analysis set, if the change transmission block and the corresponding data storage block of the auxiliary analysis set are not cross-chain (i.e., belong to the same blockchain), the direct link parameter is the reciprocal of the number of data storage blocks between the change transmission block and the data storage block. If the change transmission block and the corresponding data storage block of the auxiliary analysis set are cross-chain (i.e., belong to different blockchains), the direct link parameter is set to 0. The value of the preset direct link parameter can be determined by the user based on the actual work scenario. For example, the user can set it based on the change assessment record. The higher the user's requirements for the timeliness and analysis efficiency of the response process to changes in the timeliness relationship of the target analyzed asset, the larger the value of the preset direct link parameter. A method for setting the value of the preset direct link parameter is provided, in which the change assessment record that determines the verification validity index based on the target overlap transmission index of the change transmission block is recorded as the link reference record, and the minimum value of the direct link parameter in the link reference record that meets the user's requirements for the timeliness and analysis efficiency of the response process to changes in the timeliness relationship of the target analyzed asset is recorded as the preset direct link parameter. For any change propagation block within a single auxiliary analysis set, if the direct link parameter of the change propagation block is less than or equal to a preset direct link parameter, it indicates that there is no direct correlation or a weak direct correlation between it and the data storage block corresponding to the auxiliary analysis set. Therefore, the validity of the change propagation block is verified by the target overlap propagation index. , This refers to the number of change propagation blocks that coexist with the data storage blocks corresponding to the corresponding auxiliary analysis set. To determine the number of change transmission blocks in the given change transmission block, the determined target overlap transmission index is normalized. The normalized target overlap transmission index is recorded as the verification validity index of the change transmission block. If the direct link parameter of the change transmission block is greater than the preset direct link parameter, it indicates that there is a strong direct correlation between it and the data storage block corresponding to the auxiliary analysis set. The validity of the change transmission block is verified by the direct link parameter. The determined direct link parameter is normalized, and the normalized direct link parameter is recorded as the verification validity index of the change transmission block.

[0036] Specifically, the optimization verification module determines an auxiliary analysis set of data storage blocks whose reference cross-index is greater than a preset reference cross-index based on the set conduction cross-index. The optimization verification module determines an auxiliary analysis set of data storage blocks whose reference conduction cross-index is less than or equal to a preset reference conduction cross-index based on the target conduction index of the set.

[0037] Specifically, for a single data storage block, the reference transmission cross-index is the average of the transmission cross-indexes of all change transmission blocks existing in that data storage block. For a single change transmission block, the transmission cross-index... , This refers to the number of change-transfer blocks that exist within the change-transfer blocks of this data storage block. The number of change propagation blocks in the data storage block is used as the reference propagation cross index to characterize the temporal correlation between the time-related changes of the change propagation blocks in the data storage block. This determines the setting method of the targeted auxiliary analysis set and ensures the temporal correlation of the time-related changes of the data storage blocks in each of the determined auxiliary analysis sets. For a single data storage block, if the reference conduction cross-index of the data storage block is greater than a preset reference conduction cross-index, it indicates a strong temporal correlation between the change times of the change conduction blocks within that data storage block. An auxiliary analysis set for the data storage block is determined based on the set conduction cross-index. This auxiliary analysis set is a collection of some change conduction blocks of the data storage block. The set conduction cross-index of each auxiliary analysis set for the data storage block is greater than a preset set conduction cross-index. For a single auxiliary analysis set, the set conduction cross-index is the average of the set cross-indexes of each change conduction block within the auxiliary analysis set relative to that auxiliary analysis set. For a single change conduction block within the auxiliary analysis set, the set cross-index... , This refers to the number of change propagation blocks present in the auxiliary analysis set. This represents the number of change propagation blocks present in this auxiliary analysis set; The value of the preset set transmission cross index can be determined by the user according to the actual work scenario. For example, the user can set it according to the change assessment record. The higher the user's requirements for the timeliness and analysis efficiency of the response process to changes in the timeliness relationship of the target analysis asset, the larger the value of the preset set transmission cross index. A method for determining the value of the preset set transmission cross index is provided, which is the minimum value of the set transmission cross index of the auxiliary analysis set in the cross reference record that meets the user's requirements for the timeliness and analysis efficiency of the response process to changes in the timeliness relationship of the target analysis asset. For a single data storage block, if the reference transmission cross-index of that data storage block is less than or equal to a preset reference transmission cross-index, it indicates that the temporal correlation between the change times of the temporal relationships of the change transmission blocks existing in that data storage block is weak. Based on the set target transmission index, an auxiliary analysis set for that data storage block is determined. The set target transmission index of each determined auxiliary analysis set is greater than the preset set target transmission index. For a single auxiliary analysis set, the set target transmission index is the reciprocal of the average of the set reference transmission indices corresponding to each change in the temporal relationship of that data storage block during the analysis and evaluation phase. When a single change in the temporal relationship occurs for that data storage block, the set reference transmission index... , This is the standard deviation of the time interval between each change propagation block within the auxiliary analysis set and the time-series interval corresponding to the change in the timeliness relationship of the data storage block. This is the average time interval for each change propagation block within the auxiliary analysis set to correspond to the timeliness relationship change of the data storage block in this time. The value of the preset set target transmission index can be determined by the user based on the actual work scenario. For example, the user can set it based on change assessment records. The higher the user's requirements for the timeliness and efficiency of the response process to changes in the timeliness relationship of the target analyzed assets, the larger the value of the preset set target transmission index. A method for determining the value of the preset set target transmission index is provided, which records the change assessment records of the auxiliary analysis set determined based on the set target transmission index as the set reference records. The minimum value of the set target transmission index of the auxiliary analysis set in the set reference records that meets the user's requirements for the timeliness and efficiency of the response process to changes in the timeliness relationship of the target analyzed assets is recorded as the preset set target transmission index.

[0038] The value of the preset reference transmission cross index can be determined by the user according to the actual work scenario. For example, the user can set it according to the change assessment record. A method for determining the value of the preset transmission cross index is provided, in which the change assessment record of the auxiliary analysis set that determines the data storage block based on the set transmission cross index is recorded as the cross reference record, and the minimum value of the reference transmission cross index of the data storage block in the cross reference record that meets the user's requirements for the timeliness of the change response process and the analysis efficiency of the timeliness relationship of the target analysis asset is recorded as the preset reference transmission cross index.

[0039] Specifically, the correlation verification module performs verification correlation analysis on data storage blocks that are in a Class II change risk state, and determines the transmission verification block of the data storage block based on the effective reference risk index; The transmission verification block is a valid associated block whose effective reference risk index is greater than the preset effective reference risk index. The effective reference risk index is determined based on the change risk index of the valid associated blocks of the data storage block.

[0040] Specifically, the association verification module determines the valid associated blocks of each data storage block in the Class II change risk state based on the overlap transmission index; The overlap transmission index of any valid associated block to its corresponding data storage block is greater than the preset overlap transmission index.

[0041] Specifically, for any auxiliary analysis set of a single data storage block in a Class II change risk state, if the change risk difference index of the auxiliary analysis set is less than or equal to the preset change risk difference index, it indicates that although there is a certain time correlation between the timeliness relationship changes occurring among the data storage blocks in the auxiliary analysis set during the analysis and evaluation phase, the difference in the suddenness of the update of the timeliness relationship among the change transmission blocks is small. This indicates that some change transmission blocks have timeliness relationship changes that conform to the actual change pattern. At this time, further analysis is conducted on whether there is a clear transmission situation between the existing change transmission blocks and the timeliness relationship changes of the data storage block, ensuring the effective identification of direct or potential correlations. The effective reference risk index is the average change risk index of the effectively related blocks of the data storage block, and the overlapping transmission index between any two data storage blocks is considered. , This refers to the number of change propagation blocks that coexist between the two data storage blocks mentioned above. The number of different change propagation blocks existing in the two data storage blocks mentioned above; The values ​​of the preset overlap transmission index and the preset effective reference risk index can be determined by the user based on the actual work scenario. For example, the user can set them based on change assessment records. The higher the user's requirements for the timeliness and efficiency of the response process to changes in the timeliness relationship of the target analyzed asset, the larger the value of the preset overlap transmission index and the larger the value of the preset effective reference risk index. A method for determining the value of the preset overlap transmission index is provided, in which the change assessment record for verifying the correlation analysis of the data storage block is recorded as the correlation reference record, and the minimum value of the overlap transmission index of the effective correlation block in the correlation reference record that meets the user's requirements for the timeliness and efficiency of the response process to changes in the timeliness relationship of the target analyzed asset to its respective data storage block is recorded as the preset overlap transmission index. A method for determining the value of the preset effective reference risk index is provided, in which the minimum value of the effective reference risk index of the transmission verification block in the correlation reference record that meets the user's requirements for the timeliness and efficiency of the response process to changes in the timeliness relationship of the target analyzed asset is recorded as the preset effective reference risk index.

[0042] Specifically, the change risk index of any data storage block is positively correlated with the update stability index and update limit index of the corresponding data storage block.

[0043] Specifically, for a single data storage block, the change risk index is the sum of the update stability index and the update limit index, wherein the update stability index... , This represents the standard deviation of the duration between each update interval during the analysis and evaluation phase for this data storage block. The absolute update index is the average duration of each update interval stage during the analysis and evaluation phase for this data storage block. The absolute update execution index is the average of the absolute update execution indices for each update interval stage during the analysis and evaluation phase for this data storage block. For a single update interval stage, the absolute update execution index... , This refers to the duration corresponding to this update interval phase. The absolute update duration is determined for the update interval stage. The absolute update duration is the effective duration of the data storage block for the timeliness relationship predefined for the update interval stage. If the data storage block does not determine the absolute update duration for the update interval stage, the absolute update execution index of the data storage block is recorded as 0. The update interval stage is the time range between any two adjacent times when the timeliness relationship changes for the data storage block. If the number of update interval stages corresponding to a data storage block is less than or equal to the preset update evaluation parameter, the update stability index of the data storage block is recorded as 1. The value of the preset update evaluation parameter can be determined by the user based on the actual working scenario. For example, the user can set it based on the change evaluation record. The higher the user's requirements for the timeliness and efficiency of the response process to changes in the timeliness of the target analysis asset's relationship, the larger the value of the preset update evaluation parameter. A method for determining the value of the preset update evaluation parameter is provided, which takes the minimum value of the number of update interval stages existing in the data storage blocks whose update stability index does not correspond to 1 in the change evaluation record that meets the user's requirements for the timeliness and efficiency of the response process to changes in the timeliness of the target analysis asset's relationship as the preset update evaluation parameter. A value of 8 is provided for the preset update evaluation parameter.

[0044] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

Claims

1. A comprehensive data asset evaluation system based on artificial intelligence and blockchain, characterized in that, include: The block monitoring module is used to determine the category of each data storage block based on the change risk index, which is determined based on the update stability index and update limit index of each data storage block. The verification and evaluation module is connected to the block monitoring module and is used to determine whether to perform verification optimization analysis and verification correlation analysis for each data storage block based on the change risk status of each data storage block. The change risk status is determined based on the proportion index of a type of block and the change transmission proportion index. An optimized verification module, which is connected to the verification evaluation module, is used to determine whether to perform time-series verification analysis or effective verification analysis for each data storage block based on the change risk difference index of the auxiliary analysis set of each data storage block in a change risk state. The module determines the transmission verification block based on the time-series matching evaluation index, or determines the transmission verification block based on the direct link parameters or the target overlap transmission index. The associated verification module, which is connected to the verification evaluation module, is used to determine the transmission verification block based on the change risk index of the effective associated blocks of each data storage block in the second-class change risk state.

2. The data asset comprehensive evaluation system based on artificial intelligence and blockchain according to claim 1, characterized in that, The data storage blocks are categorized into two types: Type I data storage blocks and Type II data storage blocks. The block monitoring module classifies data storage blocks whose change risk index is greater than the preset change risk index as a type of data storage block. The block monitoring module classifies data storage blocks whose change risk index is less than or equal to the preset change risk index as Class II data storage blocks.

3. The data asset comprehensive evaluation system based on artificial intelligence and blockchain according to claim 1, characterized in that, The change risk status includes a Class I change risk status and a Class II change risk status; The verification and evaluation module records data storage blocks that have a Class I block proportion index greater than a preset Class I block proportion index or a change transmission proportion index greater than a preset change transmission proportion index as data storage blocks in a Class I change risk state. The verification and evaluation module records data storage blocks that have a Class I block proportion index less than or equal to a preset Class I block proportion index and a change transmission proportion index less than or equal to a preset change transmission proportion index as data storage blocks in a Class II change risk state.

4. The data asset comprehensive evaluation system based on artificial intelligence and blockchain according to claim 3, characterized in that, The optimization verification module performs verification optimization analysis on data storage blocks in a state of Class I change risk to determine the transmission verification blocks for that data storage block. The change risk difference index of any auxiliary analysis set is determined based on the change risk index of each data storage block within the auxiliary analysis set; The configuration of the auxiliary analysis set is determined based on the reference conduction cross index of the data storage block; The verification validity index of any of the aforementioned transmission verification blocks is greater than the preset verification validity index.

5. The data asset comprehensive evaluation system based on artificial intelligence and blockchain according to claim 4, characterized in that, The optimization verification module performs time-series verification analysis on the auxiliary analysis set where the change risk difference index is greater than the preset change risk difference index. The validation validity index of the data storage block corresponding to this auxiliary analysis set is determined based on the time-series matching evaluation index.

6. The data asset comprehensive evaluation system based on artificial intelligence and blockchain according to claim 5, characterized in that, The optimization verification module performs effective verification analysis on the auxiliary analysis set where the change risk difference index is less than or equal to the preset change risk difference index. Based on the direct link parameters of each change transmission block within the auxiliary analysis set, determine whether to determine the verification validity index according to the target overlap transmission index of the corresponding change transmission block; The optimization verification module determines the verification validity index of the change transmission block whose direct link parameter is less than or equal to the preset direct link parameter based on the target overlap transmission index. The optimization verification module determines the verification validity index of change transmission blocks whose direct link parameters are greater than the preset direct link parameters based on the direct link parameters.

7. The data asset comprehensive evaluation system based on artificial intelligence and blockchain according to claim 4, characterized in that, The optimization verification module determines the auxiliary analysis set of data storage blocks whose reference cross-index is greater than the preset reference cross-index based on the set conduction cross-index. The optimization verification module determines an auxiliary analysis set of data storage blocks whose reference conduction cross-index is less than or equal to a preset reference conduction cross-index based on the target conduction index of the set.

8. The data asset comprehensive evaluation system based on artificial intelligence and blockchain according to claim 3, characterized in that, The association verification module performs verification association analysis on data storage blocks that are in a Class II change risk state, and determines the transmission verification block of the data storage block based on the effective reference risk index. The transmission verification block is a valid associated block whose effective reference risk index is greater than the preset effective reference risk index. The effective reference risk index is determined based on the change risk index of the valid associated blocks of the data storage block.

9. The data asset comprehensive evaluation system based on artificial intelligence and blockchain according to claim 8, characterized in that, The association verification module determines the valid associated blocks of each data storage block in the Class II change risk state based on the overlap transmission index. The overlap transmission index of any valid associated block to its corresponding data storage block is greater than the preset overlap transmission index.

10. The data asset comprehensive evaluation system based on artificial intelligence and blockchain according to claim 1, characterized in that, The change risk index of any data storage block is positively correlated with the update stability index and update limit index of the corresponding data storage block.

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