Algal Bloom Forecasting: Classical Machine Learning versus Deep-Learning

The aim of this paper is to find out which Machine Learning (ML) model predicts the concentration of Chlorophyll-a, in the Palmar lake in Uruguay best. Currently there are no such models to predict the growth in this lake. The algorithms which will be compared in this paper are a Linear Regression model and the U-Net model. We will compare the...

Global shoreline forecasting with a clustering approach

Coastal areas around the world have always been densely populated areas. However, sea-level-rise and an increase in single extreme events due to climate change, threaten the coastal areas and their inhabitants. Governmental organizations, coastal managers and various private parties thrive for better insights into long-term shoreline behavior...

The development of a two day ahead power forecasting model for an offshore windpark

The growing fleet of offshore wind farms in the North Sea imposes a lot of stress on the energy grid due to its volatile power production. Accurate forecasting models that can predict the power generation of these wind parks could help grid operators to keep the energy grid stable and reduce the re-dispatch of energy. Therefore the objective of...

An Optimisation and Forecasting Framework for ULD Packing in the Air Cargo Supply Chain

The air cargo industry is a challenging environment due to the high competition between the stakeholders involved. This demands, as example, high efficiency from cargo airlines. Efficiency can be ensured by designing loading strategies that fully exploit the available cargo volume. Unknowns in the booking dimensions and flight information make...