Zobrazeno 1 - 10
of 46
pro vyhledávání: '"Igor G. Olaizola"'
Publikováno v:
Applied Sciences, Vol 13, Iss 19, p 10987 (2023)
Similarly efficient feature groups occur in prediction procedures such as Olive phenology forecasting. This study proposes a procedure that can be used to extract the most representative feature grouping from Market Basket Analysis-derived methodolog
Externí odkaz:
https://doaj.org/article/f43c62d8a8ee49ad97aa05cc41a18cbd
Publikováno v:
IEEE Access, Vol 9, Pp 44390-44401 (2021)
Transmitting and storing large volumes of dynamic / time series data collected by modern sensors can represent a significant technological challenge. A possibility to mitigate this challenge is to effectively select a subset of significant data point
Externí odkaz:
https://doaj.org/article/9bee9e2bc2b5463d877bad5dd557a73d
Publikováno v:
Sensors, Vol 22, Iss 23, p 9164 (2022)
Industry 4.0 concept has become a worldwide revolution that has been mainly led by the manufacturing sector. Continuous Process Industry is part of this global trend where there are aspects of the “fourth industrial revolution” that must be adapt
Externí odkaz:
https://doaj.org/article/d0d900ecf6084a81896d26359d0d3ad9
Autor:
Marco Quartulli, Amaia Gil, Ane Miren Florez-Tapia, Pablo Cereijo, Elixabete Ayerbe, Igor G. Olaizola
Publikováno v:
Energies, Vol 14, Iss 14, p 4115 (2021)
Battery Cell design and control have been widely explored through modeling and simulation. On the one hand, Doyle’s pseudo-two-dimensional (P2D) model and Single Particle Models are among the most popular electrochemical models capable of predictin
Externí odkaz:
https://doaj.org/article/1e6fd58b801c4eacacb64ee7b27be8b1
Autor:
Maria Teresa Linaza, Jorge Posada, Jürgen Bund, Peter Eisert, Marco Quartulli, Jürgen Döllner, Alain Pagani, Igor G. Olaizola, Andre Barriguinha, Theocharis Moysiadis, Laurent Lucat
Publikováno v:
Agronomy, Vol 11, Iss 6, p 1227 (2021)
One of the main challenges for the implementation of artificial intelligence (AI) in agriculture includes the low replicability and the corresponding difficulty in systematic data gathering, as no two fields are exactly alike. Therefore, the comparis
Externí odkaz:
https://doaj.org/article/eac071940c964e14890490ad219cfb3f
Publikováno v:
Sensors, Vol 20, Iss 21, p 6381 (2020)
Knowledge of phenological events and their variability can help to determine final yield, plan management approach, tackle climate change, and model crop development. THe timing of phenological stages and phases is known to be highly correlated with
Externí odkaz:
https://doaj.org/article/d863707c4f1949c5972296ac90fdc00f
Publikováno v:
Applied Sciences, Vol 10, Iss 18, p 6346 (2020)
In industrial applications of data science and machine learning, most of the steps of a typical pipeline focus on optimizing measures of model fitness to the available data. Data preprocessing, instead, is often ad-hoc, and not based on the optimizat
Externí odkaz:
https://doaj.org/article/dfdb7b1c762e4de691cd94807baf7476
Autor:
Iker Landa Del Barrio, Julen Cestero, Marco Quartulli, Igor G. Olaizola, Naiara Aginako, Juan José Ugartemendia
Publikováno v:
Linköping Electronic Conference Proceedings.
This work discusses the development of a multi-physics simulated model, in the frame of the decarbonization and energy efficiency objectives of the European Commission. Its central feature is the interconnection, through a microgrid, of a distributed
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1626fa59b784dfb951faa1669b66b203
https://doi.org/10.3384/ecp2118675
https://doi.org/10.3384/ecp2118675
The correct functioning of photovoltaic (PV) cells is critical to ensuring the optimal performance of a solar plant. Anomaly detection techniques for PV cells can result in significant cost savings in operation and maintenance (O&M). Recent research
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::43afa89a838db9184213d149ef358077
http://arxiv.org/abs/2212.07768
http://arxiv.org/abs/2212.07768
Autor:
Edurne Loyarte, Igor G. Olaizola
Publikováno v:
Applied Artificial Intelligence. 36
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c92dac7ee2b00e66c58e31e5ec9df782
https://doi.org/10.1080/08839514.2022.2151160
https://doi.org/10.1080/08839514.2022.2151160