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Record W4409794794 · doi:10.61091/jcmcc127b-528

Digital Twin Structure Monitoring System and Key Technologies of Distribution Network Based on Intelligent Communication Network

2025· article· en· W4409794794 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Combinatorial Mathematics and Combinatorial Computing · 2025
Typearticle
Languageen
FieldComputer Science
TopicTechnology and Security Systems
Canadian institutionsnot available
Fundersnot available
KeywordsKey (lock)Computer scienceNetwork structureComputer networkDistributed computingComputer security

Abstract

fetched live from OpenAlex

The continuous development of power market puts forward new requirements for power grid operation and power supply quality.Under this background, if electric power enterprises want to achieve sustainable development, they must strengthen management and technological innovation to improve their competitiveness.Currently, the distribution network construction is still dominated by the traditional cable transmission method, which has many drawbacks and can hardly meet the requirements of modern power production for communication capability.Digital twin technology is an advanced intelligent control method, which can effectively integrate information in complex systems.It can use data-driven to achieve real-time monitoring, fault detection and analysis functions, which can better help users improve the efficiency and security of power use.The intelligent communication network has the characteristics of good real-time, strong scalability and can quickly adapt to different environments, different devices and application scenarios.By building a complete set of distributed automatic control system, the goal of stable, reliable, efficient and energy-saving power system can be achieved.This paper presented the relevant calculation formulas of energy consumption and time delay in smart grid, and the effectiveness of the formula was verified through simulation.By combining the principle of heterogeneous sensors, a new intelligent integrated management system for remote monitoring of distribution lines was designed to realize a series of functions such as centralized meter reading, load forecasting, inspector positioning, online diagnosis, etc. of the intelligent dispatching center, which provided a theoretical basis for the optimal dispatching of the smart grid.This paper compared the traditional distribution network monitoring system with the distribution network digital twin monitoring system based on intelligent communication network.The results showed that the time delay and bit error rate of the optimized detection system had been significantly reduced, and the success rate of packet reception had increased by 10.4%; in addition, it could achieve higher accuracy and security and reduce operation

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.408
Threshold uncertainty score0.853

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.231
Teacher spread0.223 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it