Predictive modeling of ships’ power consumption with Bayesian hierarchical methods
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URL
Journal Title
Journal ISSN
Volume Title
Perustieteiden korkeakoulu |
Master's thesis
Authors
Date
2019-10-22
Department
Major/Subject
Applied Mathematics
Mcode
SCI3053
Degree programme
Master’s Programme in Mathematics and Operations Research
Language
en
Pages
78+16
Series
Description
Supervisor
Hyvönen, NuuttiThesis advisor
Solonen, AnttiStaboulis, Stratos
Keywords
Bayesian probability, Hamiltonian Monte Carlo methods, hierarchical models, ships’ total power models, service power