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All Outputs (7)

Integrating wind variability to modelling wind-ramp events using a non-binary ramp function and deep learning models (2022)
Presentation / Conference
Sharp, R., Ihshaish, H., & Deza, J. I. (2022, August). Integrating wind variability to modelling wind-ramp events using a non-binary ramp function and deep learning models. Paper presented at International Conference for Sustainable Ecological Engineering Design for Society, SEEDS 22, UWE Bristol and online

The forecasting of large ramps in wind power output known as ramp events is crucial for the incorporation of large volumes of wind energy into national electricity grids. Large variations in wind power supply must be compensated by ancillary energy s... Read More about Integrating wind variability to modelling wind-ramp events using a non-binary ramp function and deep learning models.

Parallel software package for the construction and analysis of complex networks (2013)
Presentation / Conference
Ihshaish, H., & Dijkzeul, J. (2013, November). Parallel software package for the construction and analysis of complex networks. Poster presented at LINC Mid-Term Review, Potsdam, Germany

In climate research, big and complex networks could be generated by the big climate data produced by high resolution climate models, and also observations. To analyze such complex networks, there are two main computational challenges concerning both... Read More about Parallel software package for the construction and analysis of complex networks.

Genetic ensemble (G-Ensemble) for meteorological prediction enhancement (2011)
Presentation / Conference
Ihshaish, H., Cortes, A., & Senar, M. (2011, July). Genetic ensemble (G-Ensemble) for meteorological prediction enhancement. Paper presented at The 2011 International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA2011), Las Vegas, Nevada, USA

The need for reliable predictions in environmental modelling is long known. Particularly, the predicted weather and meteorological information about the future atmospheric state is crucial and necessary for almost all other areas of environmental mod... Read More about Genetic ensemble (G-Ensemble) for meteorological prediction enhancement.