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Data · dataset · 2025

Optimal Siting of Electric Vehicle Charging Station in Emerging City Using Adaptive Genetic Algorithm: The Addis Ababa Case Study

Listed in Teesside University Research Data Repository

This study includes a complete case setting and Python codes that implement both the Bass diffusion model for forecasting electric vehicle adoption and a genetic algorithm for optimizing charging station placement.

Description

The code performs data-driven predictions of future EV growth and then utilizes this information to strategically determine the best locations for charging stations. These files collectively enable a more cost-effective, efficient, and tailored rollout of charging infrastructure to meet future demand.

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Where it is published

Catalogue records · 1

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Provenance · 1 source records, 11 field assertions
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Teesside University Research Data Repositoryoai:data.mendeley.com/2xvvmjr7d4.19 d agoJSON v1
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