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Research on Deep Learning Based Dispatching Fault Disposal Robot Technology
- Source :
- 2018 2nd IEEE Conference on Energy Internet and Energy System Integration (EI2).
- Publication Year :
- 2018
- Publisher :
- IEEE, 2018.
-
Abstract
- The current rapid development of artificial intelligence technology represented by deep learning has attracted much attention in all walks of life. The real-time regulation and operation of large-scale power grids is a typical combination of knowledge experience-based and online analysis. In particular, the fault disposal of power grids mainly depends on the pre-compiled texts of failure scenarios, which is actually the induction of prior knowledge and summary of dispatchers. Based on the above scenarios, this paper proposes a deep learning based dispatching fault disposal robot technology. Firstly, the natural language processing technology is used to learn, understand and extract the key information of the fault preplan text, and then a fault disposal knowledge map is built on this basis. Through the reasoning and analysis of knowledge, automatic/semi-automatic disposal of faults can be achieved.
- Subjects :
- Computer science
business.industry
Deep learning
02 engineering and technology
Fault (power engineering)
Industrial engineering
Online analysis
030507 speech-language pathology & audiology
03 medical and health sciences
0202 electrical engineering, electronic engineering, information engineering
Key (cryptography)
Robot
020201 artificial intelligence & image processing
Artificial intelligence
0305 other medical science
business
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2018 2nd IEEE Conference on Energy Internet and Energy System Integration (EI2)
- Accession number :
- edsair.doi...........3898269c82d61a383cdde2e6b37477b0