Browsing NTNU Open by Author "Martinelli, Gabriele"
Now showing items 1-8 of 8
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A Deep Learning-Based Method for Regional Wind Power Production Volume Prediction
Liodden, Erik (Master thesis, 2020)Målet med denne studien var å estimere produksjonsvolumet av vindkraft i en stor geografisk region gitt de numeriske vær-datane (NWP) over regionen og metoder basert på dyp læring. Et presist estimat for fremtidig ... -
Dynamic exploration designs for graphical models using clustering with applications to petroleum exploration
Martinelli, Gabriele; Eidsvik, Jo (Journal article, 2014)The paper considers the problem of optimal sequential design for graphical models. Oil and gas exploration is the main application. Here, the outcomes at prospects or reservoir units are highly dependent on each other. The ... -
Investigating the Impact of Economic Curtailment Predictive Features on Deep Learning-Based Wind Power Production Forecasting
Gundersen, Henrik (Master thesis, 2023)Målet med denne studien er å utforske hvordan man kan integrere prediktive faktorer knyttet til økonomiske begrensninger i vindkraftproduksjon, i dyp læring-baserte tilnærminger for prognoser av vindkraftproduksjon. Ved å ... -
Petroleum exploration with Bayesian Networks: From prospect risk assessment to optimal exploration
Martinelli, Gabriele (Doktoravhandlinger ved NTNU, 1503-8181; 2012:273, Doctoral thesis, 2012) -
Predicting Final Intraday Electricity Prices in the Very Short Term Utilizing Artificial Neural Networks
Ullern, Simen; Fjeldberg, Vebjørn Przytula (Master thesis, 2020)Med økende bruk av fornybare energikilder har utviklingen av prismodeller for intradag handel blitt en viktig oppgave for mange markedsaktører for å optimalisere beslutningsprosessen. Dog har ikke den tilgjengelige ... -
Predicting Final Intraday Electricity Prices in the Very Short Term Utilizing Artificial Neural Networks
Ullern, Simen; Fjeldberg, Vebjørn Przytula (Master thesis, 2020)Med økende bruk av fornybare energikilder har utviklingen av prismodeller for intradag handel blitt en viktig oppgave for mange markedsaktører for å optimalisere beslutningsprosessen. Dog har ikke den tilgjengelige ... -
Sequential information gathering schemes for spatial risk and decision analysis applications
Eidsvik, Jo; Martinelli, Gabriele; Bhattacharjya, Debarun (Journal article, 2018)Several risk and decision analysis applications are characterized by spatial elements: there are spatially dependent uncertain variables of interest, decisions are made at spatial locations, and there are opportunities for ... -
Strategies for Petroleum Exploration on the Basis of Bayesian Networks: A Case Study
Martinelli, Gabriele; Eidsvik, Jo; Hokstad, Ketil; Hauge, Ragnar (Journal article; Peer reviewed, 2014)The paper presents a new approach for modeling important geologicalelements, such as reservoir, trap, and source, in a unified statistical model.This joint modeling of these geological variables is useful for reliableprospect ...