AI-based enterprise project data flexible resource scheduling method and server

Abstract

The invention relates to the technical field of intelligent scheduling of internet data, and discloses an AI-based flexible resource scheduling method and server for enterprise project data, and the method comprises the following steps: 1, importing various project data into a server system of an enterprise by enterprise personnel through information import; 2, an AI system learning module learns and intelligently analyzes project data in information import and project data imported into a server system to form an intelligent server system; step 3, enterprise personnel inquire required project data through information search; and step 4, the server system carries out intelligent disassembly, analysis and understanding on the data from the information search to form a set of project data meeting the requirements of the information search, and the project data are displayed in front of enterprise personnel through information output. According to the method, enterprise project data, search data and personal terminal information are integrated, and an AI system learning module is combined, so that the system can autonomously learn and analyze the data.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent scheduling of Internet data, and in particular to an AI-based elastic resource scheduling method and server for enterprise project data. Background Art

[0002] With the development of the Internet, data storage has become increasingly convenient in all walks of life. From the initial paper storage to the current Internet storage, the production / service efficiency of all industries has been greatly improved. In addition, with the rapid development of AI technology, relying on the Internet big data platform, the processing of various data has become more and more intelligent, and its application areas have become increasingly extensive.

[0003] As the main production carrier of social development, the efficiency of enterprise production development will directly affect the speed of social development. Now many enterprises are adapting to and using Internet technology and AI technology, especially in data storage and scheduling. At present, most enterprises are more conducive to the storage of project data using Internet technology. When it is necessary to call, various information needs to be entered on the designated software platform to retrieve the required information. Moreover, due to the non-standardization of information input by employees, it is easy to cause the project data retrieved by the system to deviate from the expected data, which in turn affects work efficiency and increases the processing burden of the system. Summary of the Invention

[0004] To solve the above-mentioned problems in the prior art, the present invention provides an AI-based enterprise project data elastic resource scheduling method and server, which are characterized by comprising: information import, server system, AI system learning module, information search, information output, and server hardware. The project data elastic resource scheduling method generally has the following process: Step 1, enterprise personnel import various project data into the enterprise's server system through the information import; Step 2, the AI ​​system learning module learns and intelligently analyzes the project data in the information import and the project data already imported into the server system to form an intelligent server system; Step 3, enterprise personnel query the required project data through the information search; Step 4, the server system intelligently disassembles, analyzes, and understands the data from the information search to form a set of project data that meets the requirements of the information search, and presents it to the enterprise personnel through the information output;

[0005] The information import includes an information input module and an input information processing module. Enterprise personnel organize and upload project data through the information input module, and then analyze and process the project data through the input information processing module.

[0006] The information search includes a search engine and a search module. The search module is embedded in the search engine. Enterprise personnel can open the search engine and use the search module therein to enter keywords for the project data they want to query.

[0007] The server system includes a data storage module, personal terminal data information, a search information processing module, and an AI system data integration module. The data storage module is used to store project data analyzed and processed by the input information processing module. The search information processing module is used to analyze and process keywords from the search module. The AI ​​system data integration module performs intelligent processing on the three data modules: the data storage module, the personal terminal data information, and the search information processing module, and integrates a version of project data that meets the requirements.

[0008] The information output includes an output module and user confirmation, and the output module can output the project data integrated by the AI ​​system data integration module to the enterprise personnel;

[0009] The server hardware includes a cabinet and a plurality of hosts, and the plurality of hosts are arranged in the cabinet.

[0010] A further preferred solution is that the input module is provided with a fixed input template, the search module is provided with a fixed search template, and the output module is provided with a fixed output template, and the form of each template is arranged according to the type of different project data.

[0011] A further preferred solution is that the personal-side data information is directly linked to the human resources information and computer-side data information of each enterprise employee, that is, the personal-side data information can call out the information of any enterprise employee and their computer-side data, which can be used as a reference for data calling in the server system.

[0012] Further preferred solution: The AI ​​system learning module includes a supervised learning module, an unsupervised learning module, and a deep learning module. The supervised learning module is used to learn the mapping relationship between input and output from the data of the input information processing module and the search module. The unsupervised learning module is used to learn the distribution and structure of data from the data of the personal end data information. The deep learning module is used to learn the generation rules and patterns of the AI ​​system data integration module.

[0013] Further preferred solution: the user confirmation includes two situations: pass and fail. When the user confirms pass, the enterprise personnel can directly export the project data of the output module. When the user confirms fail, it is necessary to return to the AI ​​system data integration module to re-integrate the data until the user confirms pass.

[0014] A further preferred solution is that a plurality of supporting plates are arranged from top to bottom in the cabinet, a cavity is formed between two adjacent supporting plates, and a plurality of hosts are placed on the supporting plates.

[0015] A further preferred solution is that the supporting plates are in the shape of mesh plates, and the supporting plates are all tilted downward toward the cabinet, and the host is placed in the cavity in a state of being tilted downward toward the cabinet.

[0016] A further preferred solution is that a heat dissipation screen is provided on each of the chambers on the movable side of the main unit.

[0017] The beneficial effects of the present invention are embodied in:

[0018] First, by integrating enterprise project data, search data, and personal information, and combining it with the AI ​​system learning module, the system can autonomously learn and analyze the data in the server system. Then, relying on this server system, an intelligent enterprise project data elastic resource scheduling system is formed, so that the mapping relationship between input and output is as consistent as possible, making the generation rules and patterns of project data increasingly intelligent.

[0019] Second, by creating an inclined host placement state and combining it with the physical property that heat is dissipated upward, the efficiency of heat dissipation can be greatly improved through the physical structure of the cabinet, thereby improving the use effect of the server hardware. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 Schematic diagram of the method flow of the present invention;

[0021] Figure 2 Schematic diagram of the input module system of the present invention;

[0022] Figure 3 This is a schematic diagram of the search module system of the present invention;

[0023] Figure 4 Schematic diagram of the output module system of the present invention;

[0024] Figure 5 This is a schematic diagram of the overall external structure of the server hardware of the present invention;

[0025] Figure 6 This is a schematic diagram of the longitudinal cross-section structure of the server hardware of the present invention;

[0026] Figure 7 It is a schematic diagram of the longitudinal cross-section structure of the cabinet of the present invention.

[0027] Figure numerals: 1. Information import; 101. Input module; 102. Input information processing module; 2. Server system; 201. Data storage module; 202. Personal end data information; 203. Search information processing module; 204. AI system data integration module; 3. Information search; 301. Search engine; 302. Search module; 4. Information output; 401. Output module; 402. User confirmation; 5. AI system learning module; 6. Server hardware; 7. Cabinet; 8. Host; 9. Heat dissipation grid; 10. Chamber; 11. Loading plate. DETAILED DESCRIPTION

[0028] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0029] Example 1:

[0030] Reference Figure 1 , information import 1 includes information input module 101 and input information processing module 102. Enterprise personnel organize project data and upload it through information input module 101, and then analyze and process the project data through input information processing module 102; information search 3 includes search engine 301 and search module 302. Search module 302 is nested in search engine 301. Enterprise personnel can enter keywords of project data to be queried by opening search engine 301 and using search module 302 therein; server system 2 includes data storage module 201, personal terminal data information 202, search information processing module 203, AI system data According to the integration module 204, the data storage module 201 is used to store the project data analyzed and processed by the input information processing module 102, and the search information processing module 203 is used to analyze and process the keywords from the search module 302. The AI ​​system data integration module 204 performs intelligent processing through the three data modules of the data storage module 201, the personal end data information 202, and the search information processing module 203, and integrates a version of project data that meets the requirements; the information output 4 includes the output module 401 and the user confirmation 402. The output module 401 can output the project data integrated by the AI ​​system data integration module 204 to the eyes of enterprise personnel.

[0031] The general process of the project data elastic resource scheduling method is as follows: Step 1, enterprise personnel import various project data into the enterprise's server system 2 through information import 1; Step 2, the AI ​​system learning module 5 forms an intelligent server system 2 by learning and intelligently analyzing the project data in the information import 1 and the project data that has been imported into the server system 2; Step 3, enterprise personnel query the required project data through the information search 3; Step 4, the server system 2 intelligently disassembles, analyzes and understands the data from the information search 3 to form a set of project data that meets the requirements of the information search 3, and presents it to the enterprise personnel through the information output 4.

[0032] Example 2:

[0033] Reference Figure 1 、 Figure 2 、 Figure 3 、 Figure 4 The input module 101 is provided with a fixed input template, the search module 302 is provided with a fixed search template, and the output module 401 is provided with a fixed output template. The form of each template is arranged according to the type of different project data. The personal-side data information 202 is directly linked to the human resources information of each enterprise employee and the data information on the computer side, that is, the information of any enterprise employee and their computer-side data can be called out in the personal-side data information 202, which is used as a reference for data calling for the server system 2. The AI ​​system learning module 5 includes a supervised learning module, an unsupervised learning module, and a deep learning module. The supervised learning module is used to learn the mapping relationship between input and output from the data of the input information processing module 102 and the search module 302. The unsupervised learning module is used to learn the distribution and structure of data from the data of the personal-side data information 202. The deep learning module is used to learn the generation rules and patterns of the AI ​​system data integration module 204.

[0034] Example 3:

[0035] Reference Figure 5 、 Figure 6 、 Figure 7 The server hardware 6 includes a cabinet 7 and several hosts 8. The several hosts 8 are arranged in the cabinet 7. Several supporting plates 11 are arranged from top to bottom in the cabinet 7. A cavity 10 is formed between two adjacent supporting plates 11. Several hosts 8 are placed on the supporting plates 11. The supporting plates 11 are in the shape of mesh plates. The supporting plates 11 are all tilted downward toward the cabinet 7. The hosts 8 are placed in the cavity 10 in a state of being tilted downward toward the cabinet 7. A heat dissipation mesh plate 9 is provided on the movable side of the host 8 on several cavities 10.

[0036] Existing enterprise data servers basically consist of several hosts inserted flatly into a cabinet, and the distance between adjacent hosts is small, which makes it difficult to dissipate heat. The present invention creates an inclined placement state for the host 8, combined with the physical property that heat is dissipated upward, and can greatly improve the heat dissipation efficiency from the physical structure of the cabinet 7, thereby improving the use effect of the server hardware 6.

[0037] In the description of the embodiments of the present invention, it should be understood that the terms "upper", "lower", "front", "back", "left", "right", "vertical", "horizontal", "center", "top", "bottom", "top", "bottom", "inside", "outside", "inner side", "outer side" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. Among them, "inside" refers to an internal or enclosed area or space. "Periphery" refers to the area surrounding a specific component or specific area.

[0038] In the description of the embodiments of the present invention, the terms "first," "second," "third," and "fourth" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly specifying the number of the technical features indicated. Therefore, a feature specified as "first," "second," "third," or "fourth" may explicitly or implicitly include one or more of the features. In the description of the present invention, unless otherwise specified, "plurality" means two or more.

[0039] In the description of the embodiments of the present invention, it should be noted that, unless otherwise expressly specified or limited, the terms "installed," "connected," "connected," and "assembled" should be understood in a broad sense. For example, they may refer to fixed connections, detachable connections, or integral connections; they may refer to direct connections, indirect connections through an intermediate medium, or internal connections between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention in specific circumstances.

[0040] In the description of the embodiments of the present invention, specific features, structures, materials or characteristics may be combined in an appropriate manner in any one or more embodiments or examples.

[0041] In describing the embodiments of the present invention, it should be understood that "-" and "~" represent a range between two values, and the range includes the endpoints. For example, "AB" represents a range greater than or equal to A and less than or equal to B. "A~B" represents a range greater than or equal to A and less than or equal to B.

[0042] In describing the embodiments of the present invention, the term "and / or" is used herein to describe a relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone. Furthermore, the character " / " is generally used herein to indicate that the associated objects are in an "or" relationship.

[0043] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. An AI-based enterprise project data elastic resource scheduling method and server, characterized in that: include: Information import (1), server system (2), AI system learning module (5), information search (3), information output (4), server hardware (6), the project data elastic resource scheduling method generally has the following process: Step 1, enterprise personnel import various project data into the enterprise's server system (2) through the information import (1); Step 2, the AI ​​system learning module (5) forms an intelligent server system (2) by learning and intelligently analyzing the project data in the information import (1) and the project data that has been imported into the server system (2); Step 3, enterprise personnel query the required project data through the information search (3); Step 4, the server system (2) intelligently disassembles, analyzes and understands the data from the information search (3) to form a set of project data that meets the requirements of the information search (3), and presents it to the enterprise personnel through the information output (4); The information import (1) includes an information input module (101) and an input information processing module (102). Enterprise personnel organize and upload project data through the information input module (101), and then analyze and process the project data through the input information processing module (102); The information search (3) includes a search engine (301) and a search module (302). The search module (302) is embedded in the search engine (301). Enterprise personnel can open the search engine (301) and use the search module (302) therein to input keywords of the project data to be queried. The server system (2) comprises a data storage module (201), personal terminal data information (202), a search information processing module (203), and an AI system data integration module (204); the data storage module (201) is used to store project data analyzed and processed by the input information processing module (102); the search information processing module (203) is used to analyze and process keywords from the search module (302); and the AI ​​system data integration module (204) performs intelligent processing through the three data modules of the data storage module (201), the personal terminal data information (202), and the search information processing module (203), and integrates a version of project data that meets the requirements; The information output (4) includes an output module (401) and a user confirmation (402), wherein the output module (401) can output the project data integrated by the AI ​​system data integration module (204) to the eyes of enterprise personnel; The server hardware (6) includes a cabinet (7) and a plurality of hosts (8), and the plurality of hosts (8) are arranged in the cabinet (7).

2. The AI-based enterprise project data elastic resource scheduling method and server according to claim 1, characterized in that: The input module (101) is provided with a fixed input template, the search module (302) is provided with a fixed search template, and the output module (401) is provided with a fixed output template. The forms of the various templates are arranged according to the types of different project data.

3. The AI-based enterprise project data elastic resource scheduling method and server according to claim 1, characterized in that: The personal-side data information (202) is directly linked to the human resources information and computer-side data information of each enterprise employee, that is, the personal-side data information (202) can call out the information of any enterprise employee and their computer-side data, which can be used as a reference for data calling by the server system (2).

4. The AI-based enterprise project data elastic resource scheduling method and server according to claim 1, characterized in that: The AI ​​system learning module (5) includes a supervised learning module, an unsupervised learning module, and a deep learning module. The supervised learning module is used to learn the mapping relationship between input and output from the data of the input information processing module (102) and the search module (302). The unsupervised learning module is used to learn the distribution and structure of data from the data of the personal end data information (202). The deep learning module is used to learn the generation rules and patterns of the AI ​​system data integration module (204).

5. The AI-based enterprise project data elastic resource scheduling method and server according to claim 1, characterized in that: The user confirmation (402) includes two situations: pass and fail. When the user confirmation (402) is passed, the enterprise personnel can directly export the project data of the output module (401). When the user confirmation (402) is not passed, it is necessary to return to the AI ​​system data integration module (204) to re-integrate the data until the user confirmation (402) is passed.

6. The AI-based enterprise project data elastic resource scheduling method and server according to claim 1, characterized in that: A plurality of supporting plates (11) are arranged from top to bottom in the cabinet (7), a chamber (10) is formed between two adjacent supporting plates (11), and a plurality of hosts (8) are supported on the supporting plates (11).

7. The AI-based enterprise project data elastic resource scheduling method and server according to claim 6, characterized in that: The supporting plate (11) is in the shape of a mesh plate, and the supporting plate (11) is tilted downward toward the inside of the cabinet (7). The host (8) is placed in the chamber (10) in a state of tilting downward toward the inside of the cabinet (7).

8. The AI-based enterprise project data elastic resource scheduling method and server according to claim 1, characterized in that: A heat dissipation screen (9) is provided on each of the chambers (10) and located on the movable side of the main machine (8).

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