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The Baltic Dry Index (BDI) is a robust indicator in the shipping sector in terms of global economic activities, future world trade, transport capacity, freight rates, ship demand, ship orders, etc. It is hard to forecast the BDI because of its high volatility and complexity. This paper proposes an artificial neural network (ANN) approach for BDI forecasting. Data from January 2010 to December 2016 are used to forecast the BDI. Three different ANN models are developed: (i) the past weekly observation of the BDI, (ii) the past two weekly observations of the BDI, and (iii) the past weekly observation of the BDI with crude oil price. While the performance parameters of these three models are close to each other, the most consistent model is found to be the second one. Results show that the ANN approach is a significant method for modeling and forecasting the BDI and proving its applicability. [ABSTRACT FROM AUTHOR]

• Maintenance risks in a two-stroke marine diesel engine were investigated. • FAHP method was used to rank maintenance risks. • Critical maintenances and physical dimensions resulted in higher risk rankings. Maintenance activities in ship machineries are of vital importance due to economical and operational requirements. Most of ships in commercial activities have two-stroke marine diesel engines (MDEs) in the propulsion systems. Durability of the commercial activities depends on the stable operation of the main engine in the ship propulsion system. This phenomenon shows the importance of maintenance activities in the two-stroke MDEs. In this study, 46 identified maintenance activities in the two-stroke MDEs were investigated via fuzzy analytical hierarchy process (FAHP) method considering risk magnitudes. The results revealed that critical maintenance activities and physical dimensions of the parts have higher risk rankings. It was also achieved from the research that top and lowest risky maintenances are the overhaul of the turbocharger (T1) and dismantling and mounting of safety valve (C5), respectively. [ABSTRACT FROM AUTHOR]