Description: Applications of Machine Learning and Data Analytics Models in Maritime Transportation, Hardcover by Yan, Ran; Wang, Shuaian, ISBN 1839535598, ISBN-13 9781839535598, Brand New, Free shipping in the US 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. 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 ML 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. Th will be especially useful to researchers and professionals with existing expertise in maritime research who wish to learn how to apply data analytics and machine learning to their field.
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Book Title: Applications of Machine Learning and Data Analytics Models in Mar
Item Length: 9.2in
Item Width: 6.1in
Author: Shuaian Wang, Ran Yan
Publication Name: Applications of Machine Learning and Data Analytics Models in Maritime Transportation
Format: Hardcover
Language: English
Publisher: Institution of Engineering & Technology
Series: Transportation Ser.
Publication Year: 2023
Type: Textbook
Number of Pages: 319 Pages