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The limited availability of local climatological stations and the limitations to predict the wind speed (WS) accurately are significant barriers to the expansion of wind energy (WE) projects worldwide. A methodology to forecast accurately the WS at the local scale can be used to overcome these barriers. This study proposes a methodology to forecast the WS with high-resolution and long-term horizons, which combines a Fourier model and a nonlinear autoregressive network (NAR). Given the nonlinearities of the WS variations, a NAR model is used to forecast the WS based on the variability identified with the Fourier analysis. The NAR modelled successfully 1.7 years of wind-speed with 3 hours of the time interval, what may be considered the longest forecasting horizon with high resolution at the moment. [ABSTRACT FROM AUTHOR]

A mechanism for the modeling of how the sugar cane mill gears functions, formed by five elements: three bars, a sliding and a support, whose degree of mobility is 2, taking into account the presence of two motor sources: the torque applied to the superior gears and the hydraulic pressure that guarantees the positioning of the superior mass. [ABSTRACT FROM AUTHOR]