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All Outputs (12)

Estimating defection in subscription-type markets with down-sampled representation: Analysis from the scholarly publishing industry (2023)
Preprint / Working Paper

We explore the subscription-type market within the context of customer churn, and provide analysis on the business model of such markets, and how these characterise the academic publishing business. The proposed method attempts to provide inference o... Read More about Estimating defection in subscription-type markets with down-sampled representation: Analysis from the scholarly publishing industry.

Maintenance automation using deep learning methods: A case study from the aerospace industry (2023)
Presentation / Conference Contribution

In this study, state-of-the-art AI models are employed to classify aerospace maintenance records into categories based on the fault descriptions of avionic components. The classification is performed using short natural language text descriptions pro... Read More about Maintenance automation using deep learning methods: A case study from the aerospace industry.

Integrating wind variability to modelling wind-ramp events using a non-binary ramp function and deep learning models (2022)
Presentation / Conference Contribution

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.

Large-scale atmospheric phenomena under the lens of ordinal time-series analysis and information theory measures (2017)
Book Chapter

This review presents a synthesis of our work done in the framework of the European project Learning about Interacting Networks in Climate (LINC, climatelinc.eu). We have applied tools of information theory and ordinal time series analysis to investig... Read More about Large-scale atmospheric phenomena under the lens of ordinal time-series analysis and information theory measures.

Assessing the direction of climate interactions by means of complex networks and information theoretic tools (2015)
Journal Article

© 2015 AIP Publishing LLC. An estimate of the net direction of climate interactions in different geographical regions is made by constructing a directed climate network from a regular latitude-longitude grid of nodes, using a directionality index (DI... Read More about Assessing the direction of climate interactions by means of complex networks and information theoretic tools.

Inferring interdependencies in climate networks constructed at inter-annual, intra-season and longer time scales (2013)
Journal Article

We study global climate networks constructed by means of ordinal time series analysis. Climate interdependencies among the nodes are quantified by the mutual information, computed from time series of monthly-averaged surface air temperature anomalies... Read More about Inferring interdependencies in climate networks constructed at inter-annual, intra-season and longer time scales.