Abstract

Load forecasts of short lead times ranging from an hour to a day ahead are essential for improving the economic efficiency and reliability of power systems. This paper proposes a hybrid model based on the wavelet transform (WT) and the weighted nearest neighbor (WNN) techniques to [...]

Abstract

Die Integration erneuerbarer Energiequellen und die Sektorenkopplung erhöhen den Bedarf an Flexibilität im Elektrizitätssystem. Elektrofahrzeuge koordiniert zu Laden bietet die Chance solche Flexibilität bereitzustellen. Allerdings hängt das Flexibilitätspotential von Elektrofahrzeugen [...]

Abstract

Thermostatic load control systems are widespread in many countries. Since they provide heat for domestic hot water and space heating on a massive scale in the residential sector, the assessment of their energy performance and the effect of different control strategies requires [...]

Abstract

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies Forecasting bike availability is of great importance when turning the shared bike into a reliable, pleasant and uncomplicated mode of transport. Several [...]

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In view of the success of machine learning based prediction algorithms in the recent years, in this study, we have employed a selection of these algorithms on some time series prediction problems in the context of smart grid. We have used real world data from the UCLA campus solar [...]

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In this paper a new parking guiding and information system is described. The system assists the user to find the most suitable parking space based on his/her preferences and learned behavior. The system takes into account parameters such as driver's parking duration, arrival time, [...]

Abstract

Date of Conference: 29 May-1 June 2017 Conference name: 18th IEEE International Conference on Mobile Data Management (MDM), 2017 Among different components of urban mobility, urban freight transport is usually considered as the least sustainable. Limited traffic infrastructures and [...]

Abstract

urate and reliable forecasting of traffic variables is one of the primary functions of Intelligent Transportation Systems. Reliable systems that are able to forecast traffic conditions accurately, multiple time steps into the future, are required for advanced traveller information [...]

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The correlated exploitation of heterogeneous data sources offering very large historical as well as streaming data is important to increasing the accuracy of computations when analysing and predicting future states of moving entities. This is particularly critical in the maritime [...]

Abstract

From a European, regional and local perspective, as well as from the point of view of port authorities, it is important that waterborne transport should be sustainable. In this context, liquefied natural gas (LNG) is often put forward as a viable alternative fuel for deep-sea, [...]