Optimization of the Electrical Infrastructure in Paracho de Verduzco using Graph Simulation Algorithms and Artificial Intelligence
DOI:
https://doi.org/10.32870/recibe.v15i2.500Keywords:
Graph theory, graph mining, machine learning development code, software development and technology.Abstract
Given the scalability of graph AI, it's possible to establish algorithms that simulate and optimize the graph database to obtain the optimal solution to a given problem. In this sense, AI contains machine learning (ML) codes capable of learning under certain conditions and making predictions through simulations. The simulation of a "Stress Scenario" (failure at the North node) demonstrates that the use of AI allows for efficient load redistribution in less than a second, drastically reducing economic losses. Centrality analysis identifies the exact nodes requiring priority investment, optimizing the public infrastructure budget. The implementation of this analysis not only modernizes the lighting network of Paracho, but also positions the municipality as a benchmark for technological innovation in the P´urépecha Plateau, linking artisanal tradition with cutting-edge energy efficiency.References
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