¿Qué necesidad se resolvió?
Addressing problems of predicting future values of a group of variables of interest, for which no explicit relationship is known, as well as detecting anomalous behaviours over a relatively large set of historical values and in dynamic environments, is a classic and recurrent problem in the field of applied mathematics/computational science. For industry, this class of problems is of special
interest, as it makes it possible to obtain predictions, identify behaviour patterns and detect critical events. In this specific case, it is a common factor in all its businesses, associated to problems related to its production assets.
¿Qué servicio(s) se proporciona(n)?
Nowadays, within the area of artificial intelligence (automatic learning and computational intelligence) and particularly in the area of deep learning, alternatives are beginning to be developed to solve the problem of prediction, forecasting and decision making in the presence of complex and large volume data, whose industrial application is promising. These techniques are in the leading
edge in the specialized academic field.
We intend to integrate improvements in prediction processes in their industrial systems for decision
making: very complex systems in an environment of uncertainty, which imply the management of
large volumes of information from heterogeneous sources and often require real-time decision
making.
Three lines of work will be established:
Relación con la digitalización
The handling of large volumes of information, the inclusion of new Deep Learning methodologies and Artificial Intelligence require R&D activity and in general the use of computational resources that can be considered non-conventional.
Cliente, detalles
REPSOL
