T/CES 102-2022 Active Group standards

T/CES 102-2022 Power AI knowledge graph component function and interface specification

T/CES 102-2022 Power AI knowledge graph component function and interface specification

Publish Date: 2022-06-22 Implement Date: 2022-06-24 For services related to genuine standard inquiry, procurement, translation, and other related services in China, please Contact Us
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Basic Information

Standard Code: T/CES 102-2022
Standard Type: Group standards
Standard Status: Active
is_force_gb: no
CCS Name: -
ICS Name: The application of information technology in industry
Publish Date: 2022-06-22
Implement Date: 2022-06-24

Scope

Scope: This document specifies the system architecture, functional modules, service interfaces, and performance indicator specifications of power artificial intelligence knowledge graph components. This document is applicable to the application development of power artificial intelligence knowledge graph components in professional fields such as power generation and supply, and enterprise management. All units that develop their own knowledge graph tools should refer to and implement this document. Main technical content: The China Electrotechnical Society group standard T/CES 102-2022, "Function and Interface Specifications of Power Artificial Intelligence Knowledge Graph Components", is coordinated by the Smartization Working Group of the Standard Working Committee of the China Electrotechnical Society and led by State Grid Information and Communication Industry Group Co., Ltd. in its preparation. The standard specifies the system architecture, functional modules, service interfaces, and performance indicator specifications of power artificial intelligence knowledge graph components. It is applicable to the planning, design, development, construction, and operation and maintenance of power artificial intelligence knowledge graph components, and is of great significance for improving construction efficiency and ensuring the reuse of data across various power professional fields, as well as leveraging the analytical and technical value of knowledge graphs.

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