Numerical algorithms are widely used in different applications, therefore, the execution time of the functions involved in numerical algorithms is important, and, in some cases, decisive, for example, in machine learning algorithms. Given a finite set of independent functions A(x), B(x), ..., Z(x) with domains defined by disjoint, consecutive, and not necessarily adjacent intervals, the main goal is to integrate into a single function F(x) = k1×A(x) + k2×B(x) + … + kn×Z(x), where each activation coefficient k, is one if x is in the interval of the respective domain and zero otherwise. The novelty of this work is the presentation and formal demonstration of two general forms of integration of functions in a single function: The first is the mathematical version and the second is the computational version (with the AND function at the bit level), which is characterized by its efficiency. The result is applied in a case study (Peru), where two regression functions were obtained that integrate all the waves of Covid-19, that is, the epidemic curve of the variable global number of deaths/infected per day, the adjustment provided a highly statistically significant measure of correlation, a Pearson's product-moment correlation of 0.96 and 0.98 respectively. Finally, the size of the epidemic was projected for the next 30 days.
Es importante el estudio de la disponibilidad de energías renovables y en particular el eólico para su valorización. Por lo que este artículo analiza el potencial de la energía eólica de un sitio ubicado en el sur del Perú (Laraqueri), utilizando datos de viento de 2020 a una altura de 10 metros sobre el nivel del suelo. Se utilizaron dos métodos numéricos para estimar los parámetros de la función de distribución de Weibull y se calculó la densidad de potencia para cada mes. También se calculó el grado de error de la función de Weibull con los datos observados. Se concluye que, la ubicación propuesta es apropiada para la generación de energía eólica de baja potencia y la metodología propuesta se puede utilizar en otros lugares.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.