Author: HECTOR RODRIGUEZ RANGEL
This article presents a comparison of wind speed forecasting techniques, starting with the Auto-regressive Integrated Moving Average, followed by Artificial Intelligence-based techniques. The objective of this article is to compare these methods and provide readers with an idea of what method(s) to apply to solve their forecasting needs. The Artificial Intelligence-based techniques included in the comparison are Nearest Neighbors (the original method, and a version tuned by Differential Evolution), Fuzzy Forecasting, Artificial Neural Networks (designed and tuned by Genetic Algorithms), and Genetic Programming. These techniques were tested against twenty wind speed time series, obtained from Russian and Mexican weather stations, predicting the wind speed for 10 days, one day at a time. The results show that Nearest Neighbors using Differential Evolution outperforms the other methods. An idea this article delivers to the reader is: what part of the history of the time series to use as input to a forecaster? This question is answered by the reconstruction of phase space. Reconstruction methods approximate the phase space from the available data, yielding m (the system’s dimension) and τ (the sub-sampling constant), which can be used to determine the input for the different forecasting methods.
Carlos Torres Torres jhovani bornacelli Bonifacio Alejandro Can Uc Héctor Gabriel Silva Pereyra Luis Rodríguez Fernández MIGUEL AVALOS BORJA GLADIS JUDITH LABRADA DELGADO JUAN CARLOS CHEANG WONG Raúl Rangel Rojo ALICIA MARIA OLIVER Y GUTIERREZ (2018)
"Platinum nanoparticles were nucleated in a high-purity silica matrix by an ion-implantation method. The third-order nonlinear optical response of the samples was studied using femtosecond pulses at 800 nm with the z-scan technique; picosecond pulses at 532 nm using a self-diffraction approach; and nanosecond pulses at 532 nm employing a vectorial two-wave mixing experiment. Nanosecond and picosecond explorations indicated an important thermal process participating in the optical Kerr effect evaluated. However, femtosecond results allowed us to distinguish a purely electronic response, related exclusively to ultrafast refractive and absorptive nonlinearities. Femtosecond experiments pointed out the possibility to switch the dominant physical mechanism responsible for the nonlinear optical absorption in the sample. This opens the potential for controlling quantum mechanisms of optical nonlinearity by femtosecond interactions."
Nonlinear-optical response 3rd-order nonlinearities Enhancement Excitation Nanosheets CIENCIAS FÍSICO MATEMÁTICAS Y CIENCIAS DE LA TIERRA ASTRONOMÍA Y ASTROFÍSICA ASTRONOMÍA ÓPTICA OPTICA FÍSICA OPTICA FÍSICA