Wind speed forecasting at different time scales: a non parametric approach

The prediction of wind speed is one of the most important aspects when dealing with renewable energy. In this paper we show a new nonparametric model, based on semi-Markov chains, to predict wind speed. Particularly we use an indexed semi-Markov model, that reproduces accurately the statistical behavior of wind speed, to forecast wind speed one step ahead for different time scales and for very long time horizon maintaining the goodness of prediction. In order to check the main features of the model we show, as indicator of goodness, the root mean square error between real data and predicted ones and we compare our forecasting results with those of a persistence model

Search for an infrared counterpart of IGR J16358-4756

We report here on near infrared observations of the field around IGR J16358-4756. The source belongs to the new class of highly absorbed X-ray binaries discovered by IBIS/INTEGRAL. Our primary goal was to identify the infrared counterpart of the source, previously suggested to be a LMXB and then further reclassified as a HMXB. We have made use of Chandra observations of the source in order to better constrain the number of possible counterparts. Using the differential photometry technique, in observations spanning a timescale of 1 month, we found no long term variability in our observations. This is compatible, and we suggest here, that the source is a HMXB.Comment: 5 pages, 2 figures, all styles included; to be published in: "The Transient Milky Way: a perspective for MIRAX", eds. F. D'Amico, J. Braga, and R. E. Rothschild, AIP Conference Proceeding