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Analytics-Driven Solutions for Power Systems: Integrating Neural Networks and Data Science

EasyChair Preprint no. 12281

13 pagesDate: February 24, 2024


In the realm of power systems, the integration of advanced analytics, particularly neural networks and data science, has emerged as a transformative force. This paper explores the multifaceted application of analytics-driven solutions in optimizing power systems. By leveraging neural networks, sophisticated algorithms, and vast datasets, significant advancements are achievable in various aspects of power system management, including forecasting, fault detection, optimization, and decision-making processes. This integration not only enhances the efficiency and reliability of power systems but also contributes to their sustainability and resilience in the face of dynamic operational challenges and evolving energy landscapes.

Keyphrases: Analytics, Data Science, fault detection, Forecasting, neural networks, Optimization, power systems, Resilience, Sustainability

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Usman Hider},
  title = {Analytics-Driven Solutions for Power Systems: Integrating Neural Networks and Data Science},
  howpublished = {EasyChair Preprint no. 12281},

  year = {EasyChair, 2024}}
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