This research applies machine learning methods to build predictive models of Net Load Imbalance for the Resource Sufficiency Flexible Ramping Requirement in the Western Energy Imbalance Market. Several methods are used in this research, including Reconstructability Analysis, developed in the systems community, and more well-known methods such as Ba...
Due to technological breakthrough in recent decades and the rapid increase in the availability of multidimensional data, data science has become one of the most important areas of research. Within this field, modeling dependence of random variables is gaining great interest. To cope with this task, the use of graphical models is often advocated. In...
OpenMarkov is an open-source software tool for probabilistic graphical models. It has been developed especially for medicine, but has also been used to build applications in other fields and for tuition, in more than 30 countries. In this paper we explain how to use it as a pedagogical tool to teach the main concepts of Bayesian networks and influe...
Published in Frontiers in Neural Circuits
Epilepsy is one of the most common neurological disorders worldwide. Recent findings suggest that the brain is a complex system composed of a network of neurons, and seizure is considered an emergent property resulting from its interactions. Based on this perspective, network physiology has emerged as a promising approach to explore how brain areas...
Ordered Multi-valued Decision Diagrams (MDDs) have been shown to be useful to represent finite domain functions/relations. For example, various constraints can be modelled with MDD constraints. Recently, a new representation called Binary Constraint Tree (BCT), which is a (special) tree structure binary Constraint Satisfaction Problem, has been pro...
The response to the COVID-19 pandemic has been highly variable. Governments have applied different mitigation policies with varying effect on social and economic measures, over time. This article presents a methodology for examining the effect of mobility restriction measures and the association between health and population activity data. As case ...
Published in Strojnícky časopis - Journal of Mechanical Engineering
The centrifugal compressor is an important machine in the oil and gas industry, so the fault prediction of these machines is widely discussed in the literature. Several techniques can and should be used in fault prediction of centrifugal compressors: vibration analysis, non-destructive testing techniques, operating parameters, and other techniques....
Machine learning (ML) modelling techniques are promising approaches in technology acceptance modelling research. Among other capabilities, ML can be used to advance and validate theories and evaluate their underlying methodologies and predictive power. This research applies linear and non-linear ML supervised regression techniques to formulate a pr...
Context: Forensic geotechnical engineering aims to determine the most likely causes leading to geotechnical failures. Standard practice tests a set of credible hypotheses against the collected evidence using backward analysis and complex but deterministic geotechnical models. Geotechnical models involving uncertainty are not usually employed to ana...
Le besoin de traiter l’imperfection des données temporelles dans le Web sémantique augmente et, par conséquent, appelle à une manière standard de représenter et de raisonner sur telles données. Cette thèse présente une nouvelle vision visant à fournir des solutions pour différents types d’imperfections affectant les données temporelles. Notre thèse...
