A method for the reduction of the computational cost associated with the implementation of particle-filter-based failure prognostic algorithms

Autor: Rozas, Heraldo, Jaramillo, Francisco, Perez, Aramis, Jimenez, Diego, Orchard, Marcos E., Medjaher, Kamal

Publikováno v: In Mechanical Systems and Signal Processing 1 January 2020 135

Spatio-temporal probabilistic modeling based on Gaussian mixture models and neural gas theory for prediction of criminal activity

Autor: Jaramillo, Francisco, L. Quintero, Vanessa, Perez, Aramis, Orchard, Marcos

Publikováno v: Repositorio Institucional de documento digitales de acceso abierto de la UTP
Universidad Tecnológica de Panamá
instacron:U Tecnológica de Panamá

Criminal risk models are used to assist security forces both in the identification of zones with high of criminal activity for better resource allocation and prediction of future criminal events for the prevention of new crimes. In this sense, spatio

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http://ridda2.utp.ac.pa/handle/123456789/6153

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Particle-Filtering-Based State-of-Health Estimation and End-of-Life Prognosis for Lithium-Ion Batteries at Operation Temperature

Autor: Pola, Daniel, Guajardo, Felipe, Jofré, Esteban, L. Quintero, Vanessa, Perez, Aramis, Acuña, David, Orchard, Marcos

Publikováno v: Scopus-Elsevier
Repositorio Institucional de documento digitales de acceso abierto de la UTP
Universidad Tecnológica de Panamá
instacron:U Tecnológica de Panamá

We present the implementation of a particle-filtering-based framework that estimates the State-of-Health (SOH) and predicts the End-of-Life (EOL) of Lithium-Ion batteries, efficiently incorporating variations of ambient temperature in the analysis. T

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::a59f250cfea0eb66c739d02fede5b9f5
http://ridda2.utp.ac.pa/handle/123456789/6155

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