The central trajectory of a linear program consists of the set of optimal solutions x(Mu) and (y(t), s(j)) to the logarithmic barrier problems:

In this paper we introduce a timed extension of the extended finite state machines model. On the one hand, we consider that output actions take time to be performed. This time may depend on several factors such as the value of variables. On the other hand, our formalism allows to specify timeouts. In addition to present our formalism, we develop a testing theory. First, we define ten timed conformance relations and relate them. Second, we introduce a notion of timed test and define how to apply tests to IUTs.

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Abstract

Air pollution is a risk factor for many diseases that can lead to death. Therefore, it is important to develop forecasting mechanisms that can be used by the authorities, so that they can anticipate measures when high concentrations of certain pollutants are expected in the near future. Machine Learning models, in particular, Deep Learning models, have been widely used to forecast air quality. In this paper we present a comprehensive review of the main contributions in the field during the period 2011–2021. We have searched the main scientific publications databases and, after a careful selection, we have considered a total of 155 papers. The papers are classified in terms of geographical distribution, predicted values, predictor variables, evaluation metrics and Machine Learning model.