CN114610797A - Data distribution planning method based on fluid dynamics - Google Patents
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- CN114610797A CN114610797A CN202210305399.9A CN202210305399A CN114610797A CN 114610797 A CN114610797 A CN 114610797A CN 202210305399 A CN202210305399 A CN 202210305399A CN 114610797 A CN114610797 A CN 114610797A
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Abstract
The invention discloses a data distribution planning method based on fluid dynamics, which comprises the following steps: collecting fluid data of a special drainage basin, acquiring original data information of the fluid data, and generating a plurality of data blocks by the original data information; generating a distribution strategy according to the data information of each data block of the obtained original data and each classification information, and obtaining distributed fluid data; planning a data range of the distributed fluid data, and further collecting the fluid data of the drainage basin; sorting and screening the collected fluid data, removing useless data from the sorted and screened data, reserving useful data, and using the reserved data as original data; based on the raw data, a data model suitable for the raw data is built. The invention can divide the fluid data and collect the divided fluid data, so that the data can be comprehensively utilized, and meanwhile, the invention can facilitate the visual query of the data by the working personnel.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a data distribution planning method based on fluid dynamics.
Background
With the rapid development of computer technology and massively parallel computing technology, computational fluid dynamics has become a common fluid mechanics research method, and has very wide application in the fields of scientific research and engineering application. With the development of industrial application systems, application data of various information systems rapidly grow, and informatization construction gradually enters a big data era. The current prominent problems in the industry at the early stage of big data informatization construction are reflected in the following aspects: 1. fluid data cannot be comprehensively utilized; 2. the fluid data source is unclear, so that the data source is disordered, the versions are numerous, and the data cannot be accurately traced.
Disclosure of Invention
Based on the technical problems in the background art, the invention provides a data distribution planning method based on fluid dynamics.
The invention provides a data distribution planning method based on fluid dynamics, which comprises the following steps:
s1, collecting fluid data of a special drainage basin, acquiring original data information of the fluid data, and generating a plurality of data blocks from the original data information;
s2, generating a distribution strategy according to the data information of each data block of the obtained original data and each classification information, and obtaining distributed fluid data;
s3, planning the data range of the distributed fluid data, and further collecting the fluid data of the drainage basin;
s4, sorting and screening the collected fluid data, removing useless data from the sorted and screened data, reserving useful data, and using the reserved data as original data;
s5, establishing a data model suitable for the original data based on the original data;
s6 classifies the modeled raw data, evaluates the classified raw data, and searches the raw data for data source, data geographic location, and data collection time.
Preferably, the step S1 includes a data acquisition module, the data acquisition module is used for collecting watershed data, and the data acquisition module is provided with a data collection port.
Preferably, the data search of step S6 includes a data search engine.
Preferably, the data sorting in step S3 includes splitting the fluid data, removing useless data, and then integrating the split fluid data.
Preferably, the step S6 further plans a data standard, including establishing a data standard center and establishing a data migration center, establishing the data standard center to ensure consistency in use of each data, establishing a standard for storing source data in the data center, performing a normalization process on the source data of the same type, providing a data corresponding standard for extracting data to the data center, and establishing the data migration center to determine how to initialize data in the data standard table and how to incrementally import data in the data standard table.
Preferably, the step S6 evaluates and analyzes the raw data according to its own requirements.
Preferably, the step S4 inputs the retained original data into a distributed database for storage.
Preferably, the step S6 of classifying the raw data includes classifying according to data source, classifying according to data geographic location and classifying according to data collection time.
According to the data distribution planning method based on fluid dynamics, the fluid data can be divided, and the divided fluid data are collected, so that the data can be comprehensively utilized, and meanwhile, the data can be conveniently and visually inquired by workers.
Drawings
Fig. 1 is a flowchart of a data distribution planning method based on fluid dynamics according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments.
Referring to fig. 1, a data distribution planning method based on fluid dynamics includes the following steps:
s1, collecting fluid data of a special drainage basin, acquiring original data information of the fluid data, and generating a plurality of data blocks from the original data information;
s2, generating a distribution strategy according to the data information of each data block of the obtained original data and each classification information, and obtaining distributed fluid data;
s3, planning the data range of the distributed fluid data, and further collecting the fluid data of the drainage basin;
s4, sorting and screening the collected fluid data, removing useless data from the sorted and screened data, reserving useful data, and using the reserved data as original data;
s5, establishing a data model suitable for the original data based on the original data;
s6 classifies the modeled raw data, evaluates the classified raw data, and searches the raw data for data source, data geographic location, and data collection time.
In the present invention, step S1 includes a data acquisition module, where the data acquisition module is used to collect basin data, and the data acquisition module is provided with a data collection port.
In the present invention, the data search of step S6 includes a data search engine.
In the invention, the data arrangement of the step S3 comprises the steps of splitting the fluid data, eliminating useless data in the fluid data, and integrating the split fluid data of the biang.
In the present invention, step S6 further plans the data standard, including establishing a data standard center and establishing a data migration center, establishing the data standard center to ensure consistency in use of each data, establishing a standard for storing the source data in the data center, performing a normalization process on the source data of the same type, providing a data corresponding standard for extracting the data to the data center, and establishing the data migration center to determine how to initialize the data in the data standard table and how to incrementally import the data in the data standard table.
In the invention, step S6 evaluates the original data, and evaluates and analyzes the data planning result according to the self requirement.
In the present invention, step S4 inputs the retained original data into the distributed database for storage.
In the present invention, the step S6 of classifying the raw data includes dividing according to the data source, dividing according to the data geographic location and dividing according to the data acquisition time.
The invention comprises the following steps: collecting fluid data of a special drainage basin, acquiring original data information of the fluid data, and generating a plurality of data blocks by the original data information; generating a distribution strategy according to the data information of each data block of the obtained original data and each classification information, and obtaining distributed fluid data; planning a data range of the distributed fluid data, and further collecting the fluid data of the drainage basin; sorting and screening the collected fluid data, removing useless data from the sorted and screened data, reserving useful data, and using the reserved data as original data; establishing a data model suitable for the original data based on the original data; classifying the modeled raw data, evaluating the classified raw data, and searching the data source, the data geographic position and the data acquisition time of the raw data.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.
Claims (8)
1. A data distribution planning method based on fluid dynamics is characterized by comprising the following steps:
s1, collecting fluid data of a special drainage basin, acquiring original data information of the fluid data, and generating a plurality of data blocks from the original data information;
s2, generating a distribution strategy according to the data information of each data block of the obtained original data and each classification information, and obtaining distributed fluid data;
s3, planning the data range of the distributed fluid data, and further collecting the fluid data of the drainage basin;
s4, sorting and screening the collected fluid data, removing useless data from the sorted and screened data, reserving useful data, and using the reserved data as original data;
s5, establishing a data model suitable for the original data based on the original data;
s6 classifies the modeled raw data, evaluates the classified raw data, and searches the raw data for data source, data geographic location, and data collection time.
2. The fluid dynamics-based data distribution planning method according to claim 1, wherein the step S1 includes a data collection module for collecting basin data, and the data collection module is provided with a data collection port.
3. The fluid dynamics-based data distribution planning method of claim 1, wherein the data search of step S6 includes a data search engine.
4. The fluid dynamics-based data distribution planning method according to claim 1, wherein the data sorting of step S3 includes splitting the fluid data, and after removing useless data, integrating the split fluid data.
5. The hydrodynamics-based data distribution planning method of claim 1, wherein the step S6 is further to plan a data standard, and includes establishing a data standard center and a data migration center, establishing the data standard center to ensure consistency of data usage, establishing a standard for storing source data in the data center, performing a normalization scheme on source data of the same type, providing data corresponding standards for data extraction to the data center, and establishing the data migration center to determine how to initialize data in the data standard table and how to incrementally import data in the data standard table.
6. The fluid dynamics-based data distribution planning method of claim 1, wherein the step S6 evaluates and analyzes the data planning result according to its own requirements for evaluation of the raw data.
7. The fluid dynamics-based data distribution planning method of claim 1, wherein the step S4 inputs the retained original data into a distributed database for storage.
8. The fluid dynamics-based data distribution planning method of claim 1, wherein the step S6 classifying the raw data includes classifying by data source, classifying by data geographic location and classifying by data acquisition time.
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Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102023011A (en) * | 2009-09-21 | 2011-04-20 | 上海贝尔股份有限公司 | Method and system for managing relevant information of geographical position |
| CN105589958A (en) * | 2015-12-22 | 2016-05-18 | 浪潮软件股份有限公司 | Distributed big data planning method |
| CN106202457A (en) * | 2016-07-17 | 2016-12-07 | 合肥赑歌数据科技有限公司 | A kind of distributed big data schema method |
| US20190316309A1 (en) * | 2018-04-17 | 2019-10-17 | One Concern, Inc. | Flood monitoring and management system |
| CN110968629A (en) * | 2019-11-27 | 2020-04-07 | 开普云信息科技股份有限公司 | Cross-hierarchy heterogeneous data aggregation-based unified information resource management method and system |
| CN111444595A (en) * | 2020-03-10 | 2020-07-24 | 中国环境科学研究院 | Sewage interception engineering environmental effect evaluation method and device based on SWMM and EFDC coupling model |
| WO2020232591A1 (en) * | 2019-05-19 | 2020-11-26 | 深圳齐心集团股份有限公司 | Stationery information distributed planning system based on big data |
| CN112734306A (en) * | 2021-02-25 | 2021-04-30 | 澜途集思生态科技集团有限公司 | Watershed ecological water storage capacity assessment method |
| CN112765216A (en) * | 2021-01-19 | 2021-05-07 | 澜途集思生态科技集团有限公司 | Data batch processing method based on Internet of things |
| CN112903339A (en) * | 2021-01-19 | 2021-06-04 | 澜途集思生态科技集团有限公司 | Pollution source identification method and system |
| US20210315150A1 (en) * | 2018-08-16 | 2021-10-14 | Mahindra & Mahindra Limited | Method and systems for generating prescription plans for a region under cultivation |
| CN114218876A (en) * | 2021-12-17 | 2022-03-22 | 澜途集思生态科技集团有限公司 | Distributed fluid dynamics calculation method based on Apache Spark |
-
2022
- 2022-03-25 CN CN202210305399.9A patent/CN114610797A/en active Pending
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102023011A (en) * | 2009-09-21 | 2011-04-20 | 上海贝尔股份有限公司 | Method and system for managing relevant information of geographical position |
| CN105589958A (en) * | 2015-12-22 | 2016-05-18 | 浪潮软件股份有限公司 | Distributed big data planning method |
| CN106202457A (en) * | 2016-07-17 | 2016-12-07 | 合肥赑歌数据科技有限公司 | A kind of distributed big data schema method |
| US20190316309A1 (en) * | 2018-04-17 | 2019-10-17 | One Concern, Inc. | Flood monitoring and management system |
| US20210315150A1 (en) * | 2018-08-16 | 2021-10-14 | Mahindra & Mahindra Limited | Method and systems for generating prescription plans for a region under cultivation |
| WO2020232591A1 (en) * | 2019-05-19 | 2020-11-26 | 深圳齐心集团股份有限公司 | Stationery information distributed planning system based on big data |
| CN110968629A (en) * | 2019-11-27 | 2020-04-07 | 开普云信息科技股份有限公司 | Cross-hierarchy heterogeneous data aggregation-based unified information resource management method and system |
| CN111444595A (en) * | 2020-03-10 | 2020-07-24 | 中国环境科学研究院 | Sewage interception engineering environmental effect evaluation method and device based on SWMM and EFDC coupling model |
| CN112765216A (en) * | 2021-01-19 | 2021-05-07 | 澜途集思生态科技集团有限公司 | Data batch processing method based on Internet of things |
| CN112903339A (en) * | 2021-01-19 | 2021-06-04 | 澜途集思生态科技集团有限公司 | Pollution source identification method and system |
| CN112734306A (en) * | 2021-02-25 | 2021-04-30 | 澜途集思生态科技集团有限公司 | Watershed ecological water storage capacity assessment method |
| CN114218876A (en) * | 2021-12-17 | 2022-03-22 | 澜途集思生态科技集团有限公司 | Distributed fluid dynamics calculation method based on Apache Spark |
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