1,721,034 research outputs found
Qualità dell'aria nella città di Bari: monitoraggio e trend di concentrazione di IPA e metalli pesanti
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A comparison between two receptor models to determine the source apportionment of atmospheric pollutants
No full textTwo frequently used factor analysis (FA) methods, Absolute Principal Components Scores (APCS) and Target Transformation Factor Analysis (TTFA), are compared by examining two cases with different complexity on sources and parameters. The effect of the noise contribution on the data is evaluated. By applying the methods to simulated data matrices, it has been found that the APCS method characterizes the source matrix better than TTFA method. APCS method also reconstructs the sample better than TTFA. In addition both methods are applied to real data collected during a monitoring campaign in Taranto city (South Italy)
‘A simple feedforward neural network for the PM10 forecasting: comparison with a radial basis function network and a multivariate linear regression model’
No full textThe problem of air pollution is a frequently recurring situation and its management has social and economic considerable effects. Given the interaction of the numerous factors involved in the raising of the atmospheric pollution rates, it should be considered that the relation between the intensity of emission produced by the polluting source and the resulting pollution is not immediate. The aim of this study was to realise and to compare two support decision system (neural networks and multivariate regression model) that, correlating the air quality data with the meteorological information, are able to predict the critical pollution events. The development of a back-propagation neural network is presented to predict the daily PM10 concentration 1, 2 and 3 days early. The measurements obtained by the territorial monitoring stations are one of the primary data sources; the forecasting of the major weather parameters available on the website and the forecasting of the Saharan dust obtained by the "Centro Nacional de Supercomputaciòn" website, satellite images and back trajectories analysis are used for the weather input data. The results obtained with the neural network were compared with those obtained by a multivariate linear regression model for 1 and 2 days forecasting. The relative root mean square error for both methods shows that the artificial neural networks (ANN) gives more accurate results than the multivariate linear regression model mostly for 1 day forecasting; moreover, the regression model used, in spite of ANN, failed when it had to fit spiked high values of PM10 concentration
Sviluppo di una rete neutrale di tipo feed forward back propagation per la previsione di PM10: confrontato con un modello di regressione multivariata
No full textAnalisi di metalli pesanti nel particolato atmosferico: cromatografia ionica e preconcentrazione
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PM10 and gaseous pollutants trends from air quality monitoring networks in Bari province: Principal component analysis and absolute principal component scores on a two years and half data set
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Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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