Intelligent data optimization processing system for intelligent station
By designing an intelligent data optimization processing system in a smart site, dynamically compute and adjusting data priority processing factors, the problem that traditional methods cannot adapt to dynamic changes and complex scenarios is solved, and efficient data priority management and computing resource allocation are achieved.
Patent Information
- Application Number
- CN202510194005.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-02-20
- Publication Date
- 2025-05-23
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
The diversity, real-time and complexity of data in smart stations put higher requirements on data processing systems, especially in determining data priorities. Traditional static priority rules cannot adapt to dynamic changes and complex scenario requirements, resulting in inefficient allocation of computing resources.
An intelligent data optimization processing system is designed, including a factor generation module, a set division module, a first calculation module, a second calculation module and a data processing module. By dynamically generating initial data priority processing factors, dividing the data processing impact parameter set, calculating the data processing coefficients and adjusting the comprehensive data processing coefficients, and finally determining the priority order of data processing.
It realizes dynamic and accurate data priority judgment, improves the accuracy of data priority setting, and improves the overall operating efficiency and intelligence level of smart stations.
Smart Images
Figure CN120031253A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of smart station technology, and in particular to an intelligent data optimization processing system for a smart station. Background Art
[0002] With the rapid development of the Internet of Things, 5G communications, and artificial intelligence technologies, smart stations (such as smart factories, smart warehouses, smart energy stations, etc.) have become an important part of modern industry and service industries. Smart stations collect and process massive amounts of data in real time through a large number of sensors, devices, and systems to achieve intelligent monitoring, scheduling, and decision-making. However, the diversity, real-time nature, and complexity of data in smart stations place higher demands on data processing systems, especially in terms of data priority determination. How to efficiently allocate computing resources and ensure the timely execution of key tasks has become a technical problem that needs to be solved urgently.
[0003] Traditional data priority determination methods are usually based on fixed rules or simple weight allocation, such as classification and processing according to data source, data type or preset priority tags. However, these methods show obvious shortcomings in the dynamic environment of smart stations. The data of smart stations are multi-source, heterogeneous and real-time. Traditional static priority rules cannot adapt to the dynamic changes of data and complex scenario requirements. Summary of the invention
[0004] The embodiment of the present invention provides an intelligent data optimization processing system for a smart station. The present invention can realize dynamic and accurate data priority judgment, realize intelligent data optimization processing, and ensure the processing setting accuracy of data priority, thereby improving the overall operation efficiency and intelligence level of the smart station.
[0005] In order to achieve the above object, the present invention provides an intelligent data optimization processing system for a smart station, comprising: A factor generation module, used to determine a plurality of data packets to be processed, determine a data reception time corresponding to each data packet to be processed, and generate an initial data priority processing factor for each data packet to be processed based on a score decay function and the data reception time; A set division module, used for collecting multiple groups of data processing influencing parameters corresponding to each data packet to be processed, and dividing each group of data processing influencing parameters into an enhanced data processing influencing parameter set or a degraded data processing influencing parameter set; a first calculation module, configured to calculate an upgraded data processing coefficient of the data packet to be processed according to the upgraded data processing influencing parameter set, and to calculate a degraded data processing coefficient of the data packet to be processed according to the degraded data processing influencing parameter set; A second calculation module is used to extract all the upgraded data processing coefficients to determine an upgraded data processing coefficient sequence, extract all the degraded data processing coefficients to determine a degraded data processing coefficient sequence, and calculate the comprehensive data processing coefficient of the data packet to be processed according to the upgraded data processing coefficient sequence and the degraded data processing coefficient sequence; A data processing module is used to adjust the initial data priority processing factor based on the comprehensive data processing coefficient of the data packet to be processed, obtain the target data priority processing factor of the data packet to be processed, and determine the data processing priority order of the data packet to be processed based on the target data priority processing factor.
[0006] Furthermore, the set partitioning module is used for: The set partitioning module is used to determine the standard data processing impact parameter corresponding to the data packet to be processed; The set division module is used for dividing the data processing influence parameters into an enhanced data processing influence parameter set or a degraded data processing influence parameter set according to the standard data processing influence parameters and the data processing influence parameters; The set division module is used for dividing the corresponding data processing influence parameter into the degraded data processing influence parameter set when the data processing influence parameter is less than the standard data processing influence parameter; The set division module is used for dividing the corresponding data processing influence parameter into the enhanced data processing influence parameter set when the data processing influence parameter is greater than or equal to the standard data processing influence parameter.
[0007] Furthermore, the first calculation module is used for: The first calculation module is used to assign a data parameter calculation weight to each data processing influencing parameter in the enhanced data processing influencing parameter set; The first calculation module is used to calculate the enhanced data processing coefficient of the data packet to be processed according to the following formula: ; ; ; ; Where a is the enhanced data processing coefficient of the data packet to be processed, e is a constant, d1 is the number of data processing influencing parameters in the enhanced data processing influencing parameter set, and f j is the jth data processing influencing parameter in the enhanced data processing influencing parameter set, g j Calculate the weight for the data parameter corresponding to the jth data processing influencing parameter, where k is the standard data processing influencing parameter.
[0008] Furthermore, the first calculation module is used for: The first calculation module is used to calculate the set mean and the set variance corresponding to the set of degraded data processing influencing parameters; The first calculation module is used to construct a set interval according to the set mean and the set variance, analyze the set of degraded data processing influencing parameters, and determine the number of parameters of the data processing influencing parameters falling into the set interval; The first calculation module is used to calculate the degraded data processing coefficient of the data packet to be processed according to the following formula: ; Where q is the degraded data processing coefficient of the data packet to be processed, w1 is the number of data processing influencing parameters in the degraded data processing influencing parameter set, and r e is the e-th data processing influencing parameter in the degraded data processing influencing parameter set, is the ensemble mean, For all The maximum value in , w2 is the number of parameters affected by the data processing that falls into the set interval.
[0009] Furthermore, the second calculation module is used for: The second calculation module is used to fit the enhanced data processing coefficient sequence to obtain an enhanced sequence fitting curve; The second calculation module is used to determine all curve slopes corresponding to the incremental sequence fitting curve, and select the maximum curve slope to determine the incremental sequence calculation coefficient e t , where t is the maximum curve slope; The second calculation module is used to respectively calculate each of the enhanced data processing coefficients in the enhanced data processing coefficient sequence and the enhanced sequence calculation coefficient e t The product value of is used as the processing coefficient of the enhanced sub-comprehensive data; The second calculation module is used to fit the degraded data processing coefficient sequence to obtain a degraded sequence fitting curve; The second calculation module is used to determine all curve slopes corresponding to the degradation sequence fitting curve, and select the maximum curve slope to determine the degradation sequence calculation coefficient e y , where y is the maximum curve slope; The second calculation module is used to respectively calculate each degraded data processing coefficient in the degraded data processing coefficient sequence and the degraded sequence calculation coefficient e y The product value of is used as the processing coefficient of the degraded sub-comprehensive data; The second calculation module is used to calculate the comprehensive data processing coefficient of the data packet to be processed according to the upgraded sub-comprehensive data processing coefficient and the downgraded sub-comprehensive data processing coefficient.
[0010] Furthermore, the second calculation module is used for: The second calculation module is used to extract all the downgraded sub-integrated data processing coefficients and the upgraded sub-integrated data processing coefficients and use them as sub-integrated data processing coefficients; The second calculation module is used to extract the same sub-integrated data processing coefficient from all the sub-integrated data processing coefficients and obtain multiple sub-integrated data processing coefficient arrays; The second calculation module is used to count the number of the first sub-integrated data processing coefficient array of the sub-integrated data processing coefficient array; The second calculation module is used to extract a sub-integrated data processing coefficient from all sub-integrated data processing coefficient arrays respectively, and calculate the first sub-integrated data processing coefficient and value; The second calculation module is used to calculate the variance of the sub-integrated data processing coefficients of the sub-integrated data processing coefficient group, eliminate all sub-integrated data processing coefficient arrays that are smaller than the variance of the sub-integrated data processing coefficients, and count the number of second sub-integrated data processing coefficient arrays of the remaining sub-integrated data processing coefficient arrays; The second calculation module is used to extract a sub-integrated data processing coefficient from the remaining sub-integrated data processing coefficient arrays, and calculate the second sub-integrated data processing coefficient and value; The second calculation module is used to calculate the comprehensive data processing coefficient of the data packet to be processed based on the number of the first sub-comprehensive data processing coefficient array, the number of the second sub-comprehensive data processing coefficient array, the first sub-comprehensive data processing coefficient sum and the second sub-comprehensive data processing coefficient sum.
[0011] Furthermore, the second calculation module is used for: The second calculation module is used to calculate the comprehensive data processing coefficient of the data packet to be processed according to the following formula: ; Among them, u is the comprehensive data processing coefficient of the data packet to be processed, p1 is the number of the first sub-comprehensive data processing coefficient array, p2 is the number of the second sub-comprehensive data processing coefficient array, c1 is the sum of the first sub-comprehensive data processing coefficient, and c2 is the sum of the second sub-comprehensive data processing coefficient.
[0012] Furthermore, the data processing module is used for: The data processing module is used to preset a first preset comprehensive data processing coefficient and a second preset comprehensive data processing coefficient; The data processing module is used to pre-set a first preset factor adjustment coefficient, a second preset factor adjustment coefficient and a third preset factor adjustment coefficient; The data processing module is used for calculating the product value of the first preset factor adjustment coefficient and the initial data priority processing factor as the target data priority processing factor of the data packet to be processed when the comprehensive data processing coefficient is less than the first preset comprehensive data processing coefficient; The data processing module is used for calculating the product value of the second preset factor adjustment coefficient and the initial data priority processing factor as the target data priority processing factor of the data packet to be processed when the comprehensive data processing coefficient is greater than or equal to the first preset comprehensive data processing coefficient and less than the second preset comprehensive data processing coefficient; The data processing module is used to calculate the product value of the third preset factor adjustment coefficient and the initial data priority processing factor as the target data priority processing factor of the data packet to be processed when the comprehensive data processing coefficient is greater than or equal to the second preset comprehensive data processing coefficient.
[0013] Furthermore, the data processing module is used for: The data processing module is used to determine the target data priority processing factor corresponding to each data packet to be processed; The data processing module is used to sort all target data priority processing factors from large to small, and determine the data processing priority order of each data packet to be processed.
[0014] Compared with the prior art, the present invention has the following beneficial effects: The present invention discloses an intelligent data optimization processing system for a smart station. A factor generation module determines the data reception time and generates an initial data priority processing factor; a set division module collects data processing influencing parameters and divides them into an enhanced data processing influencing parameter set or a downgraded data processing influencing parameter set; a first calculation module calculates an enhanced data processing coefficient and a downgraded data processing coefficient; a second calculation module determines an enhanced data processing coefficient sequence and a downgraded data processing coefficient sequence, and calculates a comprehensive data processing coefficient; a data processing module adjusts the initial data priority processing factor based on the comprehensive data processing coefficient, obtains a target data priority processing factor, determines a data processing priority sequence, realizes dynamic and accurate data priority judgment, realizes intelligent data optimization processing, ensures the setting accuracy of data priority, and improves the overall operation efficiency and intelligence level of the smart station. BRIEF DESCRIPTION OF THE DRAWINGS
[0015] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings: Figure 1 A structural schematic diagram of an intelligent data optimization processing system for a smart station in an embodiment of the present invention is shown. DETAILED DESCRIPTION
[0016] The specific implementation of the present invention is further described in detail below in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.
[0017] In the description of the present application, it should be understood that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.
[0018] The terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, unless otherwise specified, "plurality" means two or more.
[0019] In the description of this application, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.
[0020] The following is a description of preferred embodiments of the present invention with reference to the accompanying drawings.
[0021] like Figure 1 As shown, an embodiment of the present invention discloses an intelligent data optimization processing system for a smart station, comprising: A factor generation module, used to determine a plurality of data packets to be processed, determine a data reception time corresponding to each data packet to be processed, and generate an initial data priority processing factor for each data packet to be processed based on a score decay function and the data reception time; A set division module, used for collecting multiple groups of data processing influencing parameters corresponding to each data packet to be processed, and dividing each group of data processing influencing parameters into an enhanced data processing influencing parameter set or a degraded data processing influencing parameter set; a first calculation module, configured to calculate an upgraded data processing coefficient of the data packet to be processed according to the upgraded data processing influencing parameter set, and to calculate a degraded data processing coefficient of the data packet to be processed according to the degraded data processing influencing parameter set; A second calculation module is used to extract all the upgraded data processing coefficients to determine an upgraded data processing coefficient sequence, extract all the degraded data processing coefficients to determine a degraded data processing coefficient sequence, and calculate the comprehensive data processing coefficient of the data packet to be processed according to the upgraded data processing coefficient sequence and the degraded data processing coefficient sequence; A data processing module is used to adjust the initial data priority processing factor based on the comprehensive data processing coefficient of the data packet to be processed, obtain the target data priority processing factor of the data packet to be processed, and determine the data processing priority order of the data packet to be processed based on the target data priority processing factor.
[0022] In this embodiment, the score decay function is used to describe the phenomenon that certain quantities gradually decrease over time or due to other factors, and the initial priority processing factor of each data packet to be processed can be obtained.
[0023] The beneficial effects of the above technical solution are: the present invention determines the data processing priority order, realizes dynamic and accurate data priority judgment, realizes intelligent data optimization processing, ensures the setting accuracy of data priority, and improves the overall operation efficiency and intelligence level of smart stations.
[0024] In some embodiments of the present application, the set partitioning module is used to: The set partitioning module is used to determine the standard data processing impact parameter corresponding to the data packet to be processed; The set division module is used for dividing the data processing influence parameters into an enhanced data processing influence parameter set or a degraded data processing influence parameter set according to the standard data processing influence parameters and the data processing influence parameters; The set division module is used for dividing the corresponding data processing influence parameter into the degraded data processing influence parameter set when the data processing influence parameter is less than the standard data processing influence parameter; The set division module is used for dividing the corresponding data processing influence parameter into the enhanced data processing influence parameter set when the data processing influence parameter is greater than or equal to the standard data processing influence parameter.
[0025] In this embodiment, the data processing influencing parameters include data value, data historical processing security, data historical processing times, data popularity, etc.
[0026] In this embodiment, the standard data processing influencing parameter corresponds to the data processing influencing parameter one by one and is set in advance. For example, the standard data processing influencing parameter corresponding to the data value is 0.8, which can be adjusted according to actual needs, and the rest are not shown one by one.
[0027] The beneficial effect of the above technical solution is: the present invention divides the data processing influence parameters into an enhanced data processing influence parameter set or a downgraded data processing influence parameter set according to the standard data processing influence parameters and the data processing influence parameters, thereby realizing the refined division of the data processing influence parameters and ensuring the accuracy of the set division.
[0028] In some embodiments of the present application, the first computing module is used to: The first calculation module is used to assign a data parameter calculation weight to each data processing influencing parameter in the enhanced data processing influencing parameter set; The first calculation module is used to calculate the enhanced data processing coefficient of the data packet to be processed according to the following formula: ; ; ; ; Where a is the enhanced data processing coefficient of the data packet to be processed, e is a constant, d1 is the number of data processing influencing parameters in the enhanced data processing influencing parameter set, and f j is the jth data processing influencing parameter in the enhanced data processing influencing parameter set, g j Calculate the weight for the data parameter corresponding to the jth data processing influencing parameter, where k is the standard data processing influencing parameter.
[0029] In this embodiment, a corresponding data parameter calculation weight is assigned to each data processing influencing parameter based on a weight allocation table.
[0030] The beneficial effect of the above technical solution is that the present invention calculates the enhanced data processing coefficient of the data packet to be processed based on the enhanced data processing influencing parameter set. On the one hand, it ensures the calculation accuracy of the enhanced data processing coefficient, and on the other hand, it lays the foundation for the calculation of the comprehensive data processing coefficient.
[0031] In some embodiments of the present application, the first computing module is used to: The first calculation module is used to calculate the set mean and the set variance corresponding to the set of degraded data processing influencing parameters; The first calculation module is used to construct a set interval according to the set mean and the set variance, analyze the set of degraded data processing influencing parameters, and determine the number of parameters of the data processing influencing parameters falling into the set interval; The first calculation module is used to calculate the degraded data processing coefficient of the data packet to be processed according to the following formula: ; Where q is the degraded data processing coefficient of the data packet to be processed, w1 is the number of data processing influencing parameters in the degraded data processing influencing parameter set, and r e is the e-th data processing influencing parameter in the degraded data processing influencing parameter set, is the ensemble mean, For all The maximum value in , w2 is the number of parameters affected by the data processing that falls into the set interval.
[0032] In this embodiment, the set interval includes a set mean and a set variance.
[0033] The beneficial effect of the above technical solution is: the present invention calculates the degraded data processing coefficient of the data packet to be processed according to the degraded data processing influencing parameter set, on the one hand, ensures the calculation accuracy of the degraded data processing coefficient, and on the other hand, lays the foundation for the calculation of the comprehensive data processing coefficient.
[0034] In some embodiments of the present application, the second computing module is used to: The second calculation module is used to fit the enhanced data processing coefficient sequence to obtain an enhanced sequence fitting curve; The second calculation module is used to determine all curve slopes corresponding to the incremental sequence fitting curve, and select the maximum curve slope to determine the incremental sequence calculation coefficient e t , where t is the maximum curve slope; The second calculation module is used to respectively calculate each of the enhanced data processing coefficients in the enhanced data processing coefficient sequence and the enhanced sequence calculation coefficient e t The product value of is used as the processing coefficient of the enhanced sub-comprehensive data; The second calculation module is used to fit the degraded data processing coefficient sequence to obtain a degraded sequence fitting curve; The second calculation module is used to determine all curve slopes corresponding to the degradation sequence fitting curve, and select the maximum curve slope to determine the degradation sequence calculation coefficient e y , where y is the maximum curve slope; The second calculation module is used to respectively calculate each degraded data processing coefficient in the degraded data processing coefficient sequence and the degraded sequence calculation coefficient e y The product value of is used as the processing coefficient of the degraded sub-comprehensive data; The second calculation module is used to calculate the comprehensive data processing coefficient of the data packet to be processed according to the upgraded sub-comprehensive data processing coefficient and the downgraded sub-comprehensive data processing coefficient.
[0035] In this embodiment, the curve fitting method will not be introduced in detail here.
[0036] In this embodiment, e is a constant.
[0037] In some embodiments of the present application, the second calculation module is used to extract all the degraded sub-integrated data processing coefficients and the enhanced sub-integrated data processing coefficients and use them as sub-integrated data processing coefficients; The second calculation module is used to extract the same sub-integrated data processing coefficient from all the sub-integrated data processing coefficients and obtain multiple sub-integrated data processing coefficient arrays; The second calculation module is used to count the number of the first sub-integrated data processing coefficient array of the sub-integrated data processing coefficient array; The second calculation module is used to extract a sub-integrated data processing coefficient from all sub-integrated data processing coefficient arrays respectively, and calculate the first sub-integrated data processing coefficient and value; The second calculation module is used to calculate the variance of the sub-integrated data processing coefficients of the sub-integrated data processing coefficient group, eliminate all sub-integrated data processing coefficient arrays that are smaller than the variance of the sub-integrated data processing coefficients, and count the number of second sub-integrated data processing coefficient arrays of the remaining sub-integrated data processing coefficient arrays; The second calculation module is used to extract a sub-integrated data processing coefficient from the remaining sub-integrated data processing coefficient arrays, and calculate the second sub-integrated data processing coefficient and value; The second calculation module is used to calculate the comprehensive data processing coefficient of the data packet to be processed based on the number of the first sub-comprehensive data processing coefficient array, the number of the second sub-comprehensive data processing coefficient array, the first sub-comprehensive data processing coefficient sum and the second sub-comprehensive data processing coefficient sum.
[0038] The beneficial effect of the above technical solution is: the present invention calculates the comprehensive data processing coefficient of the data packet to be processed based on the number of the first sub-comprehensive data processing coefficient array, the number of the second sub-comprehensive data processing coefficient array, the sum of the first sub-comprehensive data processing coefficient and the sum of the second sub-comprehensive data processing coefficient. The present invention ensures the calculation accuracy of the comprehensive data processing coefficient, provides a basis for data priority sorting, does not require manual participation in setting, and eliminates errors caused by subjectivity.
[0039] In some embodiments of the present application, the second computing module is used to: The second calculation module is used to calculate the comprehensive data processing coefficient of the data packet to be processed according to the following formula: ; Among them, u is the comprehensive data processing coefficient of the data packet to be processed, p1 is the number of the first sub-comprehensive data processing coefficient array, p2 is the number of the second sub-comprehensive data processing coefficient array, c1 is the sum of the first sub-comprehensive data processing coefficient, and c2 is the sum of the second sub-comprehensive data processing coefficient.
[0040] In some embodiments of the present application, the data processing module is used to: The data processing module is used to preset a first preset comprehensive data processing coefficient and a second preset comprehensive data processing coefficient; The data processing module is used to pre-set a first preset factor adjustment coefficient, a second preset factor adjustment coefficient and a third preset factor adjustment coefficient; The data processing module is used for calculating the product value of the first preset factor adjustment coefficient and the initial data priority processing factor as the target data priority processing factor of the data packet to be processed when the comprehensive data processing coefficient is less than the first preset comprehensive data processing coefficient; The data processing module is used for calculating the product value of the second preset factor adjustment coefficient and the initial data priority processing factor as the target data priority processing factor of the data packet to be processed when the comprehensive data processing coefficient is greater than or equal to the first preset comprehensive data processing coefficient and less than the second preset comprehensive data processing coefficient; The data processing module is used to calculate the product value of the third preset factor adjustment coefficient and the initial data priority processing factor as the target data priority processing factor of the data packet to be processed when the comprehensive data processing coefficient is greater than or equal to the second preset comprehensive data processing coefficient.
[0041] In this embodiment, the first preset comprehensive data processing coefficient is preferably 4, and the second preset comprehensive data processing coefficient is preferably 8, which can be adjusted according to actual needs.
[0042] In this embodiment, the first preset factor adjustment coefficient is preferably 0.85, the second preset factor adjustment coefficient is preferably 1.15, and the third preset factor adjustment coefficient is preferably 1.25, which can be adjusted according to actual conditions.
[0043] The beneficial effect of the above technical solution is: the present invention realizes dynamic adjustment of the initial data priority processing factor according to the comprehensive data processing coefficient, the first preset comprehensive data processing coefficient and the second preset comprehensive data processing coefficient, and accurately obtains the target data priority processing factor of the data packet to be processed.
[0044] In some embodiments of the present application, the data processing module is used to: The data processing module is used to determine the target data priority processing factor corresponding to each data packet to be processed; The data processing module is used to sort all target data priority processing factors from large to small, and determine the data processing priority order of each data packet to be processed.
[0045] The beneficial effects of the above technical solution are: sorting all target data priority processing factors from large to small, determining the data processing priority order of each data packet to be processed, realizing dynamic and accurate data priority judgment, realizing intelligent data optimization processing, ensuring the setting accuracy of data priority, and improving the overall operation efficiency and intelligence level of smart stations.
[0046] In the description of the above embodiments, specific features, structures, materials or characteristics may be combined in a suitable manner in any one or more embodiments or examples.
[0047] Although the present invention has been described above with reference to the embodiments, various modifications may be made thereto and parts thereof may be replaced with equivalents without departing from the scope of the present invention. In particular, as long as there is no structural conflict, the various features in the embodiments disclosed by the present invention may be used in combination with each other in any manner, and the fact that these combinations are not fully described in this specification is only for the sake of omitting space and saving resources.
[0048] Those skilled in the art can understand that the above are only preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions recorded in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.
Claims
1. An intelligent data optimization processing system for a smart station, characterized in that: include: A factor generation module, used to determine a plurality of data packets to be processed, determine a data reception time corresponding to each data packet to be processed, and generate an initial data priority processing factor for each data packet to be processed based on a score decay function and the data reception time; A set division module, used for collecting multiple groups of data processing influencing parameters corresponding to each data packet to be processed, and dividing each group of data processing influencing parameters into an enhanced data processing influencing parameter set or a degraded data processing influencing parameter set; a first calculation module, configured to calculate an upgraded data processing coefficient of the data packet to be processed according to the upgraded data processing influencing parameter set, and to calculate a degraded data processing coefficient of the data packet to be processed according to the degraded data processing influencing parameter set; A second calculation module is used to extract all the upgraded data processing coefficients to determine an upgraded data processing coefficient sequence, extract all the degraded data processing coefficients to determine a degraded data processing coefficient sequence, and calculate the comprehensive data processing coefficient of the data packet to be processed according to the upgraded data processing coefficient sequence and the degraded data processing coefficient sequence; A data processing module is used to adjust the initial data priority processing factor based on the comprehensive data processing coefficient of the data packet to be processed, obtain the target data priority processing factor of the data packet to be processed, and determine the data processing priority order of the data packet to be processed based on the target data priority processing factor.
2. The intelligent data optimization processing system for smart stations according to claim 1 is characterized in that: The set partitioning module is used for: The set partitioning module is used to determine the standard data processing influencing parameters corresponding to the data packets to be processed; The set division module is used for dividing the data processing influence parameters into an enhanced data processing influence parameter set or a degraded data processing influence parameter set according to the standard data processing influence parameters and the data processing influence parameters; The set division module is used for dividing the corresponding data processing influence parameter into the degraded data processing influence parameter set when the data processing influence parameter is less than the standard data processing influence parameter; The set division module is used for dividing the corresponding data processing influence parameter into the enhanced data processing influence parameter set when the data processing influence parameter is greater than or equal to the standard data processing influence parameter.
3. The intelligent data optimization processing system for smart stations according to claim 1 is characterized in that: The first calculation module is used for: The first calculation module is used to assign a data parameter calculation weight to each data processing influencing parameter in the enhanced data processing influencing parameter set; The first calculation module is used to calculate the enhanced data processing coefficient of the data packet to be processed according to the following formula: ； ； ； ； Where a is the enhanced data processing coefficient of the data packet to be processed, e is a constant, d1 is the number of data processing influencing parameters in the enhanced data processing influencing parameter set, and f j is the jth data processing influencing parameter in the enhanced data processing influencing parameter set, g j Calculate the weight for the data parameter corresponding to the jth data processing influencing parameter, where k is the standard data processing influencing parameter.
4. The intelligent data optimization processing system for smart stations according to claim 1 is characterized in that: The first calculation module is used for: The first calculation module is used to calculate the set mean and the set variance corresponding to the set of degraded data processing influencing parameters; The first calculation module is used to construct a set interval according to the set mean and the set variance, analyze the set of degraded data processing influencing parameters, and determine the number of parameters of the data processing influencing parameters falling into the set interval; The first calculation module is used to calculate the degraded data processing coefficient of the data packet to be processed according to the following formula: ； Where q is the degraded data processing coefficient of the data packet to be processed, w1 is the number of data processing influencing parameters in the degraded data processing influencing parameter set, and r e is the e-th data processing influencing parameter in the degraded data processing influencing parameter set, is the ensemble mean, For all , w2 is the maximum value in , and w2 is the number of parameters affected by the data processing that falls into the set interval.
5. The intelligent data optimization processing system for smart stations according to claim 1 is characterized in that: The second calculation module is used for: The second calculation module is used to fit the enhanced data processing coefficient sequence to obtain an enhanced sequence fitting curve; The second calculation module is used to determine all curve slopes corresponding to the incremental sequence fitting curve, and select the maximum curve slope to determine the incremental sequence calculation coefficient e t , where t is the maximum curve slope; The second calculation module is used to respectively calculate each of the enhanced data processing coefficients in the enhanced data processing coefficient sequence and the enhanced sequence calculation coefficient e t The product value of is used as the processing coefficient of the enhanced sub-comprehensive data; The second calculation module is used to fit the degraded data processing coefficient sequence to obtain a degraded sequence fitting curve; The second calculation module is used to determine all curve slopes corresponding to the degradation sequence fitting curve, and select the maximum curve slope to determine the degradation sequence calculation coefficient e y , where y is the maximum curve slope; The second calculation module is used to respectively calculate each degraded data processing coefficient in the degraded data processing coefficient sequence and the degraded sequence calculation coefficient e y The product value of is used as the processing coefficient of the degraded sub-comprehensive data; The second calculation module is used to calculate the comprehensive data processing coefficient of the data packet to be processed according to the upgraded sub-comprehensive data processing coefficient and the downgraded sub-comprehensive data processing coefficient.
6. The intelligent data optimization processing system for smart stations according to claim 5 is characterized in that: The second calculation module is used for: The second calculation module is used to extract all the downgraded sub-integrated data processing coefficients and the upgraded sub-integrated data processing coefficients and use them as sub-integrated data processing coefficients; The second calculation module is used to extract the same sub-integrated data processing coefficient from all the sub-integrated data processing coefficients and obtain multiple sub-integrated data processing coefficient arrays; The second calculation module is used to count the number of the first sub-integrated data processing coefficient array of the sub-integrated data processing coefficient array; The second calculation module is used to extract a sub-integrated data processing coefficient from all sub-integrated data processing coefficient arrays respectively, and calculate the first sub-integrated data processing coefficient and value; The second calculation module is used to calculate the variance of the sub-integrated data processing coefficients of the sub-integrated data processing coefficient group, eliminate all sub-integrated data processing coefficient arrays that are smaller than the variance of the sub-integrated data processing coefficients, and count the number of second sub-integrated data processing coefficient arrays of the remaining sub-integrated data processing coefficient arrays; The second calculation module is used to extract a sub-integrated data processing coefficient from the remaining sub-integrated data processing coefficient arrays, and calculate the second sub-integrated data processing coefficient and value; The second calculation module is used to calculate the comprehensive data processing coefficient of the data packet to be processed based on the number of the first sub-comprehensive data processing coefficient array, the number of the second sub-comprehensive data processing coefficient array, the first sub-comprehensive data processing coefficient sum and the second sub-comprehensive data processing coefficient sum.
7. The intelligent data optimization processing system for smart stations according to claim 6 is characterized in that: The second calculation module is used for: The second calculation module is used to calculate the comprehensive data processing coefficient of the data packet to be processed according to the following formula: ； Among them, u is the comprehensive data processing coefficient of the data packet to be processed, p1 is the number of the first sub-comprehensive data processing coefficient array, p2 is the number of the second sub-comprehensive data processing coefficient array, c1 is the sum of the first sub-comprehensive data processing coefficient, and c2 is the sum of the second sub-comprehensive data processing coefficient.
8. The intelligent data optimization processing system for smart stations according to claim 1 is characterized in that: The data processing module is used for: The data processing module is used to preset a first preset comprehensive data processing coefficient and a second preset comprehensive data processing coefficient; The data processing module is used to pre-set a first preset factor adjustment coefficient, a second preset factor adjustment coefficient and a third preset factor adjustment coefficient; The data processing module is used for calculating the product value of the first preset factor adjustment coefficient and the initial data priority processing factor as the target data priority processing factor of the data packet to be processed when the comprehensive data processing coefficient is less than the first preset comprehensive data processing coefficient; The data processing module is used for calculating the product value of the second preset factor adjustment coefficient and the initial data priority processing factor as the target data priority processing factor of the data packet to be processed when the comprehensive data processing coefficient is greater than or equal to the first preset comprehensive data processing coefficient and less than the second preset comprehensive data processing coefficient; The data processing module is used to calculate the product value of the third preset factor adjustment coefficient and the initial data priority processing factor as the target data priority processing factor of the data packet to be processed when the comprehensive data processing coefficient is greater than or equal to the second preset comprehensive data processing coefficient.
9. The intelligent data optimization processing system for smart stations according to claim 1 is characterized in that: The data processing module is used for: The data processing module is used to determine the target data priority processing factor corresponding to each data packet to be processed; The data processing module is used to sort all target data priority processing factors from large to small, and determine the data processing priority order of each data packet to be processed.