One potential strength of recurrent neural networks (RNNs) is their – theoretical – ability to find a connection between cause and consequence in time series in an constraint-...
We consider the problem of one-step ahead prediction for time series generated by an underlying stationary stochastic process obeying the condition of absolute regularity, describi...
Process modelling systems are complex and difficult to compare. A key attribute of any process modelling formalism or tool is time which involves how it handles and represents tem...
The synthesis of stochastic processes using genetic programming is investigated. Stochastic process behaviours take the form of time series data, in which quantities of interest v...
Temporal logic can be used to describe processes: their behaviour is characterized by a set of temporal models axiomatized by a temporal theory. Two types of models are most often ...