Decision support tool for the tanker second-hand market using data mining techniques

Abstract

This thesis proposes an innovative decision support tool intended for market leaders and those anticipating market states of "sale and purchase". This is feasible with the use of powerful data mining techniques and the construction of explanatory forecasting models. Data mining techniques seek and extract patterns from databases. These patterns can be used to reveal possible interactions between database variables and to predict values for future "sale and purchase" market states as an aid to decision-making. Possible: users of such a tool are ship brokers, ship owners, shipyards and general brokers and investors. It is crucial to mention the rising need for decisional tools especially when asset play in shipping seems to increase its proportion among other investment practices.