Continuous-Time Stationary Processes And Wind Power:Infinitely divisible distributions, stochastic delay differentialequations, and applcations to wind power production
Notice bibliographique
Résumé
half of my PhD studies and are therefore included to a varying extent in my progress report written as part of the qualifying examination after which I obtained a master's degree in Mathematics-Economics.The first chapter is an introduction to the studied topics.A small introduction to each paper is also included.The introduction is meant to tie the papers together under three main themes: infinitely divisible distributions, stochastic delay differential equations, and wind power production.While these themes cover a variety of very different topics, it is an aim of the introduction to unveil some common ground among them.The papers appear ordered in the continuum introduced by the three main themes, ranging from infinitely divisible distributions over stochastic delay differential equations to wind power production.In this way, Paper A is the paper most concerned with infinitely divisible distributions and Paper I deals most exclusively with wind power production.This progression of the papers through the main themes is not chronological.Together with the conclusion of my PhD studies belongs a sincere thanks to a lot of people.I wish to express my gratitude to my supervisor Andreas Basse-O'Connor for many insightful comments, considerate attitude, and cheerful mood.My other supervisor Jan Pedersen also deserve a big praise for always having an open door, asking the good question, and having an abundance of helpful comments both in and outside the academic setup.I am truly grateful to both my supervisors for showing patience with me, for the guidance through the years, and the many meetings with advise and laughter.I would like to thank Fred Espen Benth for being the central figure in a very pleasant visit to the University of Oslo.I enjoyed my time there immensely, and the conversations in Oslo and the following correspondence via email have always been insightful and enjoyable.Our collaborations have inspired me to pursue different areas of mathematics, and have therefore sparked a lot of passion in me.I would also like to express my gratitude to Mikkel Slot Nielsen for the many interesting collaborations and discussions.Furthermore, a warm thank you goes out to Troels Sønderby Christensen for a very pleasant collaboration and visits, both the visit to Aarhus and when I went to Aalborg, and for the good times in the office and on the skis in Oslo.James Nichols and Vestas Wind Systems also deserve a big thank you for a great collaboration and interesting meetings.Many fellow PhD student at Aarhus University also deserve a big praise for the many joyful experiences over the years, in particular, Julie, Thorbjørn, Mikkel, Jeanett, Patrick, Mads, Claudio, and Mathias.Finally, my most heartfelt thanks goes to my family.I am deeply grateful to my significant other, Line, who is
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,002 |
| Communication savante | 0,002 | 0,003 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».