19 resultados para autocorrelation
Resumo:
The Bartlett-Lewis Rectangular Pulse Modified (BLPRM) model simulates the precipitous slide in the hourly and sub-hourly and has six parameters for each of the twelve months of the year. This study aimed to evaluate the behavior of precipitation series in the duration of 15 min, obtained by simulation using the model BLPRM in situations: (a) where the parameters are estimated from a combination of statistics, creating five different sets; (b) suitability of the model to generate rain. To adjust the parameters were used rain gauge records of Pelotas/RS/Brazil, which statistics were estimated - mean, variance, covariance, autocorrelation coefficient of lag 1, the proportion of dry days in the period considered. The results showed that the parameters related to the time of onset of precipitation (λ) and intensities (μx) were the most stable and the most unstable were ν parameter, related to rain duration. The BLPRM model adequately represented the mean, variance, and proportion of the dry period of the series of precipitation lasting 15 min and, the time dependence of the heights of rain, represented autocorrelation coefficient of the first retardation was statistically less simulated series suitability for the duration of 15 min.
Resumo:
ABSTRACT Precision agriculture (PA) allows farmers to identify and address variations in an agriculture field. Management zones (MZs) make PA more feasible and economical. The most important method for defining MZs is a fuzzy C-means algorithm, but selecting the variable for use as the input layer in the fuzzy process is problematic. BAZZI et al. (2013) used Moran’s bivariate spatial autocorrelation statistic to identify variables that are spatially correlated with yield while employing spatial autocorrelation. BAZZI et al. (2013) proposed that all redundant variables be eliminated and that the remaining variables would be considered appropriate on the MZ generation process. Thus, the objective of this work, a study case, was to test the hypothesis that redundant variables can harm the MZ delineation process. BAZZI This work was conducted in a 19.6-ha commercial field, and 15 MZ designs were generated by a fuzzy C-means algorithm and divided into two to five classes. Each design used a different composition of variables, including copper, silt, clay, and altitude. Some combinations of these variables produced superior MZs. None of the variable combinations produced statistically better performance that the MZ generated with no redundant variables. Thus, the other redundant variables can be discredited. The design with all variables did not provide a greater separation and organization of data among MZ classes and was not recommended.
Resumo:
A spatial autocorrelation study of enzyme loci detected by starch gel electrophoresis was performed to verify the occurrence of spatial genetic structure within two natural populations of Machaerium villosum Vog. The sampled populations were termed "Antropic Model (MA)" and "Natural Model (MN)" and they are situated in Campininha Farm areas, at Moji-Guaçu municipality, 22°10'43''-22°18'19'' S and 47°8'5"-47°11'34" W, in the state of São Paulo. Ten polymorphic loci in the MA population and nine polymorphic loci in the MN population were assessed by Moran's I autocorrelation statistic. No spatial autocorrelation was detected among individuals within sampled populations. Results are in line with other studies in woody species from tropical rain forest.
Resumo:
Dentre as diversas árvores frutíferas nativas dos cerrados, a cagaiteira (Eugenia dysenterica DC.) merece destaque pelo seu amplo potencial econômico. A fim de fornecer algumas informações relativas ao padrão espacial da variabilidade genética desta espécie, foram realizadas análises de autocorrelação espacial das freqüências alélicas em dez subpopulações locais da região sudeste do Estado de Goiás. Foram utilizados marcadores isoenzimáticos, em um total de seis sistemas enzimáticos (SKDH, 6-PGD, alfa-EST, MDH, PGI e PGM), com oito locos polimórficos. Foi realizada uma análise de autocorrelação espacial, utilizando índices I de Moran estimados em quatro classes de distância geográfica. Os correlogramas mostraram que, de fato, a divergência genética está estruturada no espaço em um padrão clinal de variação. Simulações de evolução neutra da variação nas freqüências alélicas entre as subpopulações, geradas a partir de um processo Ornstein-Uhlenbeck (O-U), foram utilizadas para avaliar os padrões espaciais sob essa hipótese e compará-los com os correlogramas obtidos com as freqüências alélicas. As análises indicaram que um processo estocástico (evolução neutra) deve ser o responsável pela diferenciação genética dessas populações, havendo assim um balanço entre fluxo gênico em pequenas distâncias geográficas e deriva genética dentro das populações locais, como o esperado para modelos de isolamento-por-distância ou "stepping-stone".