CN115905205A - Predictive database convenient for computer processing - Google Patents
Predictive database convenient for computer processing Download PDFInfo
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- CN115905205A CN115905205A CN202310015800.XA CN202310015800A CN115905205A CN 115905205 A CN115905205 A CN 115905205A CN 202310015800 A CN202310015800 A CN 202310015800A CN 115905205 A CN115905205 A CN 115905205A
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- 238000012545 processing Methods 0.000 title claims abstract description 83
- 238000001914 filtration Methods 0.000 claims abstract description 29
- 230000005540 biological transmission Effects 0.000 claims abstract description 22
- 238000005457 optimization Methods 0.000 claims abstract description 15
- 238000000605 extraction Methods 0.000 claims abstract description 14
- 238000012937 correction Methods 0.000 claims abstract description 13
- 238000004364 calculation method Methods 0.000 claims description 12
- 238000012216 screening Methods 0.000 claims description 10
- 239000013589 supplement Substances 0.000 claims description 8
- 238000011282 treatment Methods 0.000 claims description 7
- 238000011221 initial treatment Methods 0.000 claims description 2
- 238000000034 method Methods 0.000 abstract description 7
- 230000000694 effects Effects 0.000 abstract description 3
- 230000001502 supplementing effect Effects 0.000 abstract description 2
- 238000010586 diagram Methods 0.000 description 3
- 230000003670 easy-to-clean Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000000717 retained effect Effects 0.000 description 2
- 238000004891 communication Methods 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
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Abstract
The application discloses a predictive database convenient for computer processing, which comprises an input processing module, a filtering module and a computer client, wherein the input processing module is respectively connected with an input module and a historical input module, the input processing module is connected with a second transmission module, the second transmission module is connected with the filtering module, the filtering module is connected with an extraction module, and the extraction module is connected with an optimization module; the optimization module is connected with the storage module. The method has the advantages that the database is used for predicting and supplementing the input information of the user completely, so that the information loss is reduced, the integrity of the information is ensured, and the subsequent computer identification is facilitated; the workload of the computer is reduced, and the success rate of computer processing is improved; the system is provided with an error correction structure, so that the content in the database can be periodically checked, error information and data can be eliminated, the validity of the data is ensured, and the management effect on the information in the database is improved.
Description
Technical Field
The present application relates to the field of computer data processing, and more particularly to a predictive database that facilitates computer processing.
Background
A database is a "warehouse that organizes, stores, and manages data according to a data structure. The data processing method is a large data set which is stored in a computer for a long time, organized, sharable and uniformly managed, and can be assisted by a database in the process of processing data and information by the computer, so that the processing efficiency of the computer is improved.
The existing database is not easy to predict and supplement information input by a user, the input information has a missing phenomenon and is incomplete, the identification of a subsequent computer is not facilitated, the workload of the computer is increased, the success rate of computer processing is influenced, the internal part of the database does not have an error correction function, the error information and data are not easy to be cleaned, and the management of the database is not facilitated. Therefore, a predictive database that facilitates computer processing is proposed to address the above-mentioned problems.
Disclosure of Invention
The embodiment provides a predictive database convenient for computer processing, which is used for solving the problems that the existing database in the prior art is not easy to predict and supplement the information input by the user, the input information has a missing phenomenon and is not complete enough, the identification of a subsequent computer is not facilitated, the workload of the computer is increased, the success rate of computer processing is influenced, the inside of the database does not have an error correction function, the wrong information and data are not easy to clean, and the management of the database is not facilitated.
According to one aspect of the present application, there is provided a predictive database for facilitating computer processing, comprising an input processing module, a filtering module, and a computer client, the input processing module being connected to the input module and the history input module, respectively, the input processing module being connected to a second transmission module, the second transmission module being connected to the filtering module, the filtering module being connected to an extraction module, the extraction module being connected to an optimization module; the optimization module is connected with the storage module, the storage module is connected with the filtering module, the filtering module is connected with the additional input module, the additional input module is connected with the first transmission module, and the first transmission module is connected with the computer client.
Furthermore, the second transmission module is connected with a multi-stage processing module, the multi-stage processing module is connected with the filtering module, and the multi-stage processing module internally comprises a first-stage processing module, a second-stage processing module and a third-stage processing module.
Furthermore, the primary processing module is connected with the secondary processing module, and the secondary processing module is connected with the tertiary processing module.
Furthermore, a screening module and a database module are arranged in the filtering module, and the screening module is connected with the database module.
Further, the database module is connected with an output module, the output module is arranged inside the auxiliary module, and the output module is connected with the supplementary module.
Further, the supplementary module is respectively connected with the error correction module and the information module.
Furthermore, the error correction module, the output module, the supplement module and the information module form an auxiliary module.
Further, the storage module is connected with an additional input module, and the additional input module is connected with an input device.
Further, the optimization module comprises a calculation module and a threshold processing module, and the calculation module is connected with the threshold processing module.
Further, the calculation module is connected with the extraction module, and the threshold processing module is connected with the storage module.
By the embodiment of the application, the problems that the existing database is not easy to predict and supplement information input by a user, the input information has a missing phenomenon and is not complete enough, the identification of a subsequent computer is not facilitated, the workload of the computer is increased, the success rate of computer processing is influenced, the inside of the database does not have an error correction function, the error information and data are not easy to clean, and the management of the database is not facilitated are solved, the input information of the user is predicted and supplemented completely by the database, the missing of the information is reduced, the integrity of the information is ensured, and the identification of the subsequent computer is facilitated; the workload of the computer is reduced, and the success rate of computer processing is improved; the system is provided with an error correction structure, so that the content in the database can be periodically checked, error information and data can be eliminated, the validity of the data is ensured, and the effect of managing the information in the database is improved.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without inventive exercise.
FIG. 1 is a schematic overall structure of an embodiment of the present application;
FIG. 2 is a schematic diagram of an internal structure of a multi-stage processing module according to an embodiment of the present application;
FIG. 3 is a schematic diagram of an internal structure of a filtration module according to an embodiment of the present application;
fig. 4 is a schematic diagram of an internal structure of an auxiliary module according to an embodiment of the present application.
In the figure: 1. an input module; 2. an input processing module; 3. a history input module; 4. a multi-stage processing module; 5. a filtration module; 6. an additional input module; 7. a first transmission module; 8. a storage module; 9. an optimization module; 901. a calculation module; 902. a threshold processing module; 10. an extraction module; 11. a second transmission module; 12. a screening module; 13. a database module; 14. an auxiliary module; 15. an error correction module; 16. an output module; 17. a supplement module; 18. an information module; 19. a computer client; 20. a primary processing module; 21. a secondary processing module; 22. and a three-stage treatment module.
Detailed Description
In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only partial embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and claims of this application and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It should be understood that the data so used may be interchanged under appropriate circumstances such that embodiments of the application described herein may be used. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
In the present application, the terms "upper", "lower", "left", "right", "front", "rear", "top", "bottom", "inner", "outer", "middle", "vertical", "horizontal", "lateral", "longitudinal", and the like indicate an orientation or positional relationship based on the orientation or positional relationship shown in the drawings. These terms are used primarily to better describe the present application and its embodiments, and are not used to limit the indicated devices, elements or components to a particular orientation or to be constructed and operated in a particular orientation.
Moreover, some of the above terms may be used in other meanings besides orientation or positional relationship, for example, the term "upper" may also be used in some cases to indicate a certain attaching or connecting relationship. The specific meaning of these terms in this application will be understood by those of ordinary skill in the art as appropriate.
Furthermore, the terms "mounted," "disposed," "provided," "connected," and "sleeved" are to be construed broadly. For example, it may be a fixed connection, a removable connection, or a unitary construction; can be a mechanical connection, or an electrical connection; may be directly connected, or indirectly connected through intervening media, or may be in internal communication between two devices, elements or components. The specific meaning of the above terms in the present application can be understood by those of ordinary skill in the art as the case may be.
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
Referring to fig. 1-4, a predictive database for facilitating computer processing includes an input processing module 2, a filtering module 5, and a computer client 19, wherein the input processing module 2 is connected to the input module 1 and the history input module 3, respectively, the input processing module 2 is connected to a second transmission module 11, the second transmission module 11 is connected to the filtering module 5, the filtering module 5 is connected to an extraction module 10, and the extraction module 10 is connected to an optimization module 9; the optimization module 9 is connected with a storage module 8, the storage module 8 is connected with a filtering module 5, the filtering module 5 is connected with an additional input module 6, the additional input module 6 is connected with a first transmission module 7, and the first transmission module 7 is connected with a computer client 19.
The second transmission module 11 is connected with the multi-stage processing module 4, the multi-stage processing module 4 is connected with the filtering module 5, and the multi-stage processing module 4 internally comprises a first-stage processing module 20 and second-stage processing modules 21 and 23.
The primary treatment module 20 is connected with the secondary treatment module 21, and the secondary treatment module 21 is connected with the tertiary treatment module 22.
A screening module 12 and a database module 13 are arranged in the filtering module 5, and the screening module 12 is connected with the database module 13.
The database module 13 is connected to an output module 16, the output module 16 is arranged inside the auxiliary module 14, and the output module 16 is connected to a supplementary module 17.
The supplementary module 17 is connected to the error correction module 15 and the information module 18, respectively.
The error correction module 15, the output module 16, the supplement module 17 and the information module 18 constitute an auxiliary module 14.
The storage module 8 is connected to an additional input module 6, and the additional input module 6 is connected to an input device.
The optimization module 9 includes a calculation module 901 and a threshold processing module 902, and the calculation module 901 and the threshold processing module 902 are connected.
The calculating module 901 is connected to the extracting module 10, and the threshold processing module 902 is connected to the storing module 8.
The using method comprises the following steps: firstly, partial data are input into an input module 1 by using external equipment, historical data are stored in a historical input module 3, the data in the input module 1 and the historical input module 3 are sent into an input processing module 2 to be processed, the processed data are transmitted into the Internet network through an I/O interface of a second transmission module 11, partial input data are transmitted into a database module 13 of a filtering module 5, the historical input data are transmitted into a multistage processing module 4, multistage processing is carried out through a first-stage processing module 20, a second-stage processing module 21 and the second transmission module 11, the filtering module 5 filters the historical input data which are not successfully processed, screening is carried out by a screening module 12, after screening is finished, algorithm extraction is carried out on the historical input data which are successfully processed by an extraction module 10, the extracted input data are input into an optimization module 9, the probability is calculated by a calculation module 901, the algorithm is filtered by optimizing a threshold value through a threshold value processing module 902, the retained algorithm is input into a storage module 8, then the additional data are stored in a data module 13, additional data are input by an additional input module 6, the additional user data are transmitted into a client side computer 19 through a first transmission module 7, and are transmitted into a client side computer processing side 19.
The algorithms extracted by the extraction module 10 are too many, each algorithm corresponds to a different prediction result, if the prediction is performed based on each algorithm, too much useless work is performed, so the extracted algorithms need to be filtered, and because some algorithms repeatedly appear, correspondingly, when the algorithms are used for prediction, the accuracy of the prediction result is higher, and the higher the probability of the algorithm is, the more accurate the result predicted based on the algorithm is, therefore, the probability statistics is performed by using the algorithms extracted by the calculation module 901, the optimization filtering is performed on the low probability algorithm lower than the threshold value based on the optimization threshold value, and the high probability algorithm is retained, so the accuracy of the prediction result is improved, the workload during the computer calculation is reduced, and the success rate of the computer processing is improved.
The application has the advantages that: the database is used for predicting and supplementing the input information of the user completely, so that the loss of the information is reduced, the integrity of the information is ensured, and the subsequent computer identification is facilitated; the workload of the computer is reduced, and the success rate of computer processing is improved; the system is provided with an error correction structure, so that the content in the database can be periodically checked, error information and data can be eliminated, the validity of the data is ensured, and the management effect of the information in the database is improved.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made to the present application by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (10)
1. A predictive database that facilitates computer processing, characterized by: the system comprises an input processing module (2), a filtering module (5) and a computer client (19), wherein the input processing module (2) is respectively connected with an input module (1) and a history input module (3), the input processing module (2) is connected with a second transmission module (11), the second transmission module (11) is connected with the filtering module (5), the filtering module (5) is connected with an extraction module (10), and the extraction module (10) is connected with an optimization module (9); the optimization module (9) is connected with the storage module (8), the storage module (8) is connected with the filtering module (5), the filtering module (5) is connected with the additional input module (6), the additional input module (6) is connected with the first transmission module (7), and the first transmission module (7) is connected with the computer client (19).
2. A predictive database for facilitating computer processing of claim 1, wherein: the second transmission module (11) is connected with the multilevel processing module (4), the multilevel processing module (4) is connected with the filtering module (5), and the multilevel processing module (4) internally comprises a first-level processing module (20), a second-level processing module (21) and a second-level processing module (23).
3. A predictive database for facilitating computer processing according to claim 2, wherein: the primary treatment module (20) is connected with the secondary treatment module (21), and the secondary treatment module (21) is connected with the tertiary treatment module (22).
4. A predictive database for facilitating computer processing of claim 1, wherein: the filtering module (5) is internally provided with a screening module (12) and a database module (13), and the screening module (12) is connected with the database module (13).
5. A predictive database for facilitating computer processing according to claim 4, wherein: the database module (13) is connected with the output module (16), the output module (16) is arranged inside the auxiliary module (14), and the output module (16) is connected with the supplement module (17).
6. A predictive database for facilitating computer processing according to claim 5, wherein: the supplementary module (17) is respectively connected with the error correction module (15) and the information module (18).
7. A predictive database for facilitating computer processing according to claim 6, wherein: the error correction module (15), the output module (16), the supplement module (17) and the information module (18) form an auxiliary module (14).
8. A predictive database for facilitating computer processing of claim 1, wherein: the storage module (8) is connected with an additional input module (6), and the additional input module (6) is connected with an input device.
9. A predictive database for facilitating computer processing of claim 1, wherein: the optimization module (9) comprises a calculation module (901) and a threshold processing module (902), wherein the calculation module (901) is connected with the threshold processing module (902).
10. A predictive database for facilitating computer processing according to claim 9, wherein: the calculation module (901) is connected with the extraction module (10), and the threshold processing module (902) is connected with the storage module (8).
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN202310015800.XA CN115905205A (en) | 2023-01-06 | 2023-01-06 | Predictive database convenient for computer processing |
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| Application Number | Priority Date | Filing Date | Title |
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| CN202310015800.XA CN115905205A (en) | 2023-01-06 | 2023-01-06 | Predictive database convenient for computer processing |
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Application publication date: 20230404 |