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2018 | OriginalPaper | Buchkapitel

Prediction of Container Damage Insurance Claims for Optimized Maritime Port Operations

verfasst von : Ashwin Panchapakesan, Rami Abielmona, Rafael Falcon, Emil Petriu

Erschienen in: Advances in Artificial Intelligence

Verlag: Springer International Publishing

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Abstract

A company operating in a commercial maritime port often experiences clients filing insurance claims on damaged shipping containers. In this work, multiple classifiers have been trained on synthesized data, to predict such insurance claims. The results show that Random Forests outperform other classifiers on typical machine learning metrics. Further, insights into the importance of various features in this prediction are discussed, and their deviation from expert opinions. This information facilitates selective information collation to predict container claims, and to rank data sources by relevance. To our knowledge, this is the first publication to investigate the factors associated with container damage and claims, as opposed to ship damage or other related problems.

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Titel: Prediction of Container Damage Insurance Claims for Optimized Maritime Port Operations
verfasst von: Ashwin Panchapakesan
Rami Abielmona
Rafael Falcon
Emil Petriu
Verlag: Springer International Publishing
Buch: Advances in Artificial Intelligence
Print ISBN: 978-3-319-89655-7

Electronic ISBN: 978-3-319-89656-4

Copyright-Jahr: 2018
DOI: https://doi.org/10.1007/978-3-319-89656-4_25

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