Decision making on sea: an expert system for risk assessment in maritime using data mining Online publication date: Thu, 02-Dec-2021
by Dimitrios Kokotos; Alkiviadis Kyriakakis
International Journal of Information and Decision Sciences (IJIDS), Vol. 13, No. 4, 2021
Abstract: This work proposes the prototyping implementation of a dynamic expert system. The essence is the proposal is prediction of ship accidents. The validation process is based on data collected from coast guard official investigation reports. A classifier based on C5 algorithm is able to work even in presence of limitations for real-world data (noisy, many missing attribute values, etc). C5 algorithm is used for building decision trees and the models are used in the knowledge acquisition and its representation. The optimal decision rules estimated the dependency of the most important predictor upon the target variable 'source of accidents'. The comparison between two time periods shows that accidents due to human error were reduced, a result in line with the IMO report. The resulting patterns can be used to gain insight into aspects of shipping safety and to predict outcomes for future situations as an aid to decision making.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Information and Decision Sciences (IJIDS):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook