Automatic forecasts of univariate time series are largely demanded in business and science. In this paper, we investigate the forecasting task for geo-referenced time series. We take into account the temporal and spatial dimension of time series to get accurate forecasting of future data. We describe two algorithms for forecasting which ARIMA models. The first is designed for seasonal data and ...

Radio Frequency Identification (RFID) is a highly beneficial technological advancement which could eventually change the way of doing business. However, the difficulty in assessing the potential benefits of RFID has been delayed RFID related investment decisions within organizations. Especially, time lag, or payback time from RFID investment, has been one of key barriers in RFID investment. Thi...

This paper introduces Lags COevolving with Rbfns (L-Co-R), a coevolutionary method developed to face time-series forecasting problems. L-Co-R simultaneously evolves the model that provides the forecasted values and the set of time lags the model must use in the prediction process. Coevolution takes place by means of two populations that evolve at the same time, cooperating between them; the fir...

This paper analyses robotic signals in the perspective of fractional dynamics and the pseudo phase plane (PPP). It is shown that the spectra of several experimental signals can be approximated by trend lines whose slope characterizes their fractional behavior. For the PPP reconstruction of each signal, the time lags are calculated through the fractal dimension. Moreover, to obtain a smooth PPP,...

A general methodology that involves geometric configuration of the network structure for studying multistability and multiperiodicity is developed. We consider a general class of nonautonomous neural networks with delays and various activation functions. A geometrical formulation that leads to a decomposition of the phase space into invariant regions is employed. We further derive criteria unde...

To contribute to a deeper understanding of M-phase control in eukaryotic cells, we have constructed a model based on the biochemistry of M-phase promoting factor (MPF) in Xenopus oocyte extracts, where there is evidence for two positive feedback loops (MPF stimulates its own production by activating Cdc25 and inhibiting Wee1) and a negative feedback loop (MPF stimulates its own destruction by i...

We study the properties of type-C quasi-periodic oscillation (type-C QPO) MAXI J1348-630 during its 2019 outburst and reflare with NICER. This is first time that evolution QPOs studied an reflare. found QPO are similar to those observed in other black-hole systems outburst. suggests physical processes responsible for same a also FWHM high-frequency broadband component changes significantly ener...

We study the response of populations of digital organisms that adapt to a time-varying (periodic) fitness landscape of two oscillating peaks. We corroborate in general predictions from quasi-species theory in dynamic landscapes, such as adaptation to the average fitness landscape at small periods (high frequency) and quasistatic adaptation at large periods (low frequency). We also observe adapt...

We examine multistability of several coexisting bursting patterns in a central pattern generator network composed of three Hodgkin-Huxley type cells coupled reciprocally by inhibitory synapses. We establish that the control of switching between bursting polyrhythms and their bifurcations are determined by the temporal characteristics, such as the duty cycle, of networked interneurons and the co...