Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 2 de 2
Filtrar
Mais filtros

Base de dados
País/Região como assunto
Ano de publicação
Tipo de documento
Intervalo de ano de publicação
1.
Environ Monit Assess ; 193(2): 84, 2021 Jan 26.
Artigo em Inglês | MEDLINE | ID: mdl-33495931

RESUMO

In this paper, we described generation and performances of feedforward neural network models that could be used for a day ahead predictions of the daily maximum 1-h ozone concentration (1hO3) and 8-h average ozone concentration (8hO3) at one traffic and one background station in the urban area of Novi Sad, Serbia. The six meteorological variables for the day preceding the forecast and forecast day, ozone concentrations in the day preceding the forecast, the number of the day of the year, and the number of the weekday for which ozone prediction was performed were utilized as inputs. The three-layer perceptron neural network models with the best performance were chosen by testing with different numbers of neurons in the hidden layer and different activation functions. The mean bias error, mean absolute error, root mean squared error, correlation coefficient, and index of agreement or Willmott's Index for the validation data for 1hO3 forecasting were 0.005 µg m-3, 12.149 µg m-3, 15.926 µg m-3, 0.988, and 0.950, respectively, for the traffic station (Dnevnik), and - 0.565 µg m-3, 10.101 µg m-3, 12.962 µg m-3, 0.911, and 0.953, respectively, for the background station (Liman). For 8hO3 forecasting, statistical indicators were - 1.126 µg m-3, 10.614 µg m-3, 12.962 µg m-3, 0.910, and 0.948 respectively for the station Dnevnik and - 0.001 µg m-3, 8.574 µg m-3, 10.741 µg m-3, 0.936, and 0.966, respectively, for the station Liman. According to the Kolmogorov-Smirnov test, there is no significant difference between measured and predicted data. Models showed a good performance in forecasting days with the high values over a certain threshold.


Assuntos
Poluentes Atmosféricos , Ozônio , Poluentes Atmosféricos/análise , Monitoramento Ambiental , Previsões , Meteorologia , Redes Neurais de Computação , Ozônio/análise , Sérvia
2.
Microsc Res Tech ; 75(7): 968-76, 2012 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-22392855

RESUMO

Apatura ilia (Denis and Schiffermüller, 1775) and A. iris (Linnaeus, 1758) are fascinating butterflies found in the Palaearctic ecozone (excepting the north of Africa). The wings of these insects are covered with a great number of two types of scales positioned like roof tiles. Type I scales are on the surface, while type II scales are situated below them. The structural color of the type I scales is recognized only on the dorsal side of both the fore and hind wings of the males of the aforementioned species. Both types of scales are responsible for pigment color of the wings, but iridescence is observed only in the type I scales. The brilliant structural color is due to a multilayer structure. The features of the scales, their dimensions and fine structure were obtained using scanning electron microscopy. Cross sections of the scales were then analyzed by transmission electron microscopy. The scales of the "normal" and clytie forms of A. ilia have a different nanostructure, but are of the same type. A similar type of structure, but with a different morphology, was also noticed in A. iris. The scales of the analyzed species resemble the scales of tropical Morpho butterflies.


Assuntos
Borboletas/ultraestrutura , Asas de Animais/ultraestrutura , África , Animais , Feminino , Masculino , Microscopia Eletrônica de Varredura , Microscopia Eletrônica de Transmissão , Nanoestruturas/ultraestrutura
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA