Conditional Reliability Modeling of Short-Term River Basin Management

River Basin Management with Spin

This paper presents de use of the Spin model checker as the core engine to build Decision Support Systems (DSSs) to control complex river basins during flood situations. Current DSSs in this domain are mostly based on simulators to predict the rainfall and the water flow along the river basin. In this paper, we propose a scheme that integrates simulators in the water domain with additional logi...

Modeling Short-Term Energy Load with Continuous Conditional Random Fields

Short-term energy load forecasting, such as hourly predictions for the next n (n ≥ 2) hours, will benefit from exploiting the relationships among the n estimated outputs. This paper treats such multisteps ahead regression task as a sequence labeling (regression) problem, and adopts a Continuous Conditional Random Fields (CCRF) strategy. This discriminative approach intuitively integrates two la...

Digital Spatial Data as Support for River Basin Management: the Case of Sotla River Basin

Many real-world spatially related problems, including river-basin planning and management, give rise to geographical information system based decision making, since the performance of spatial policy alternatives were traditionally and are still often represented by thematic maps. Advanced technologies and approaches, such as geographical information systems (GIS), offer a unique opportunity to ...

Social Learning in River Basin Management

Flood Risk and River Basin Management

Recent scenario studies on water management focus on one or two projection years and the effects on the water system and functions. The future is however more complex and dynamic. Therefore, we analyse transient scenarios in order to evaluate the performance of water management strategies. Current available simulation tools are not suitable for this purpose. Therefore, we have developed and use...