The Stowage and Segregation of Dangerous Goods on a Container Ship through Use of Artificial Neural Network Approach

Container ships carry most seagoing non-bulk cargo through major seaports today. Due to the increased demand in a variety of industrial fields, the movement of dangerous goods has increased through seaborne trade. One of the greatest challenges of container shipping is the transportation of dangerous cargo onboard. The preservation methods for dangerous goods during transport can have serious consequences onboard a ship. The loading or stowage for a container ship is one of the serious problems that has to be solved by each company that manage a container terminal. The stowage of dangerous goods requires more attention due to the hazardous consequences, which are monitored using strict regulations by IMDG Code. This study aims to create a Decision Support System (DSS) by using Multi-Layer Perceptron (MLP) as an Artificial Neural Network Model which may help in determination of the proper locations for these dangerous goods on a ship. In this way, the operator (maritime terminal or agency) will have more awareness of the situation and it would be possible to prevent maritime accidents due to improper stowage and segregation of dangerous goods.

Language

  • English

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Filing Info

  • Accession Number: 01564956
  • Record Type: Publication
  • Files: TRIS
  • Created Date: May 8 2015 10:38AM