Development of Levenberg-Marquardt theoretical approach for electric networks

2020/04/01 by Alexey Mikhaylov, S. I. Tarakanov · 1 voice
Engineering · #Industrial Engineering and Technologies #Engineering Diagnostics and Reliability #Electric Power Systems and Control

paper · doi:10.1088/1742-6596/1515/5/052006

openalex publication_date 2020/04/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29

Abstract

Abstract The algorithm for artificial neural networks is presented for the optimal distribution of tasks in electric networks in an automatic mode without operator participation. The article presents the artificial neural networks algorithm based on Levenberg-Marquardt approach that implements the specified task, as well as substantiation of its characteristics. It is proposed to use the technology of artificial neural networks (ANN), which on the basis of the developed multi-criteria evaluation electricity system of ARES allows ranking. The ANN architecture with Levenberg-Marquardt algorithm of weights optimization and their efficiency is estimated. As indicators of efficiency, the F-measure and the percentage of correctly made decisions (accuracy) were chosen for optimal network parameters. The obtained ANN was successfully tested.

Citations

• BLOCKCHAIN INFRASTRUCTURE AND GROWTH OF GLOBAL POWER CONSUMPTION
• OIL PRICE PREDICTORS: MACHINE LEARNING APPROACH
• Machine learning in economic planning: ensembles of algorithms

Discussions

• Mikhaylov, A., Tarakanov, S. (2020). Development of Levenberg-Marquardt theoretical approach for electric network. Journal of Physics: Conference Series, 1515, 052006, doi.org/10.1088/1742... [bsky, 2 points, 0 comments]

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