Applications of Machine Learning and Data Analytics Models in Maritime Transportation - Rilegato

Yan, Ran; Wang, Shuaian

 
9781839535598: Applications of Machine Learning and Data Analytics Models in Maritime Transportation
Rilegato
ISBN 10: 1839535598 ISBN 13: 9781839535598
Casa editrice: Inst of Engineering & Technology, 2023

Sinossi

Machine learning and data analytics can be used to inform technical, commercial and financial decisions in the maritime industry. Applications of Machine Learning and Data Analytics Models in Maritime Transportation explores the fundamental principles of analysing maritime transportation related practical problems using data-driven models, with a particular focus on machine learning and operations research models.

Data-enabled methodologies, technologies, and applications in maritime transportation are clearly and concisely explained, and case studies of typical maritime challenges and solutions are also included. The authors begin with an introduction to maritime transportation, followed by chapters providing an overview of ship inspection by port state control, and the principles of data driven models. Further chapters cover linear regression models, Bayesian networks, support vector machines, artificial neural networks, tree-based models, association rule learning, cluster analysis, classic and emerging approaches to solving practical problems in maritime transport, incorporating shipping domain knowledge into data-driven models, explanation of black-box machine learning models in maritime transport, linear optimization, advanced linear optimization, and integer optimization. A concluding chapter provides an overview of coverage and explores future possibilities in the field.

The book will be especially useful to researchers and professionals with expertise in maritime research who wish to learn how to apply data analytics and machine learning to their fields.

Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.

Editore
Inst of Engineering & Technology
Data di pubblicazione
2023
Lingua
Inglese
ISBN 10 
1839535598
ISBN 13 
9781839535598
Rilegatura
Copertina rigida
Numero di pagine
305
Contatto del produttore
non disponibile
Persona responsabile
non disponibile