On July, 22 of 2020, an article authored by Maria João Sousa, Alexandra Moutinho and Miguel Almeida [1], was presented at the World Congress on Computational Intelligence (WCCI), a flagship biennial international conference that joins conferences of the three branches of computational intelligence, namely: fuzzy systems (FUZZ-IEEE), neural networks (IJCNN) and evolutionary computation (CEC).
The article proposes a data-driven optimization solution for the dimensioning and design of configurations of fleets of unmanned aerial vehicles, based on an estimated demand for the need to perform aerial missions in a given region. The case study analyzed focuses on the application of this method for situations of monitoring of forest fires.
The article is available online (https://ieeexplore.ieee.org/document/9177642), and also available on this page.
Link to the file on ResearchGate:
https://www.researchgate.net/publication/343894818_Decentralized_Distribution_of_UAV_Fleets_Based_on_Fuzzy_Clustering_for_Demand-driven_Aerial_Services
Reference:
[1] M. J. Sousa, A. Moutinho and M. Almeida. (2020). “Decentralized Distribution of UAV Fleets Based on Fuzzy Clustering for Demand-driven Aerial Services” in IEEE International Conference on Fuzzy Systems (FUZZ–IEEE), Glasgow, United Kingdom, 2020, pp.1–8, doi: 10.1109/FUZZ48607.2020.9177642.
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