Artificial neural network model of the relationshi

Authors: Małgorzata Puc

Publish Date: 2011/05/15

Volume: 56, Issue: 2, Pages: 395-401

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Abstract

Birch pollen is one of the main causes of allergy during spring and early summer in northern and central Europe The aim of this study was to create a forecast model that can accurately predict daily average concentrations of Betula sp pollen grains in the atmosphere of Szczecin Poland In order to achieve this a novel data analysis technique—artificial neural networks ANN—was used Sampling was carried out using a volumetric spore trap of the Hirst design in Szczecin during 2003–2009 Spearman’s rank correlation analysis revealed that humidity had a strong negative correlation with Betula pollen concentrations Significant positive correlations were observed for maximum temperature average temperature minimum temperature and precipitation The ANN resulted in multilayer perceptrons 366 8 2928711 time series prediction was of quite high accuracy SD Ratio between 03 and 05 R 085 Direct comparison of the observed and calculated values confirmed good performance of the model and its ability to recreate most of the variationBirch trees Betula sp are common throughout Poland The genus Betula belongs to the Fagales order and the Betulaceae family which also includes Alnus Corylus and Carpinus Five species of birch present in Poland grow in their natural habitat and a few have been introduced Betula pendula and Betula pubescens are the most common and occur most frequently Betula pendula is also often planted in parks streets and gardens as an ornamental tree The second species in terms of numbers is the common white birch B pubescens which grows in moist habitats like swamp birch forests The other three species Betula humilis Betula nana 1991 Betula × oycoviensis are rare Seneta 1991 APG II System 2003Birch pollen is abundant in the air during April and May and is a well known major treeallergen in central and northern Europe D’Amato and Spieksma 1992 with a significant impact on human health Estimates suggest that between 10 and 20 of the population of northern and central Europe are allergic to birch pollen Spieksma 1990 In Poland according to Rapiejko et al 2004 patients sensitive to birch pollen first develop symptoms of hay fever when exposed to more than 20 birch pollen grains/m3 air In Poland such concentrations of birch pollen occur almost throughout the whole birch pollen season 77–98 of the season However atmospheric birch pollen concentrations higher than 155 grains/m3 have been shown to evoke dyspnea disordered or inadequate breathing and the number of days with such high birch pollen concentrations make up 20–62 of the total birch pollen season Although the relationships between atmospheric concentrations of birch pollen and meteorological factors is well documented in literature CastellanoMéndez et al 2005 Clot 2001 Corden et al 2000 2002 Emberlin et al 2002 Latałowa et al 2002 Puc and Wolski 2002 Stach et al 2008 there are only a few statistical models describing the most important parameters affecting the presence of birch pollen in the air and their values determining high or low concentrations of birch grains CastellanoMéndez et al 2005 Latałowa et al 2002 However the majority of previously proposed models have been aimed more frequently at predicting airborne birch pollen concentrations One of the reasons for such a situation is the nonnormality and nonlinearity of variables involved in modelling when the statistical methods typically used linear or multiple regression reveal insufficient performance Therefore the use of other modelling techniques should be investigated One of the methods recently introduced into ecological modelling is the artificial neural network technique ANN Neural networks function as a universal approximating system with an ability to learn This method is especially applicable to multivariate data sets with nonlinear dependencies and does not require variables to fit any theoretical distribution The main difference between ANN and the programs for algorithmic processing of information eg presented in aerobiological literature is the ability to generalize knowledge over new previously unknown data not presented in the process of learning Carling 1992 Fausett 1994 Tadeusiewicz 1993 2001 Osowski 1996 Lek and Guegan 1999 The phenological phase of pollination and the subsequent dispersal of pollen in the air depends on local climatic factors modified by geographical location Kornaś and MedweckaKornaś 2002 These specific relationships are well analyzed and modeled by neural networks In Poland ANN techniques have been used hitherto only for fungal spores GrinnGofroń and Strzelczak 2008 2009 but because of the differences in the biology of pollen grains and fungal spores meteorological conditions have different effects on sporulation processes and pollination and on the means of dispersal of spores and pollen Shivanna and Rangaswamy 1992Szczecin is the capital of Western Pomerania situated in the Northwest of Poland The city is surrounded by three woods and hills and water reservoirs constituting almost onequarter of the city’s territory The climate of the region is modified by the influence of Atlantic air masses and the proximity of the Baltic Sea It has a mild climate with January the coldest month −11°C and July the hottest 177°C The average annual temperature is 84°C annual mean relative humidity ranges between 70 and 77 and rainfall is concentrated mainly in summer Mean annual precipitation is 528 mm The most unfavourable characteristics of the climate of Szczecin include strong and very strong winds which are frequent especially from November until March Koźmiński and Czarnecka 1996 Within the city area there are synanthropic plants and trees introduced by man and also primeval forest The growing season defined as the period of the year during which growing conditions for native vegetation and cultivated crops are the most favourable is about 210–220 days This is the period with a mean 24 h air temperature above 5°C and in the moderate climate zone in Poland it lasts from the last spring ground frost to the first autumn ground frost Kożuchowski and Degrimendžić 2005Aerobiological monitoring was conducted continuously during 2003–2009 using volumetric spore traps of the Hirst design Hirst 1952 Lanzoni VPPS2000 Italy The trap was set on a rooftop in the Śródmieście district of Szczecin 53°26′26″ N 14°32′50′ E at an elevation of 21 m above ground level The measuring site was 05 km northwest from the Jan Kasprowicz Park the largest green complex in the part of Szczecin on the left bank of the Odra River A microscope slide was prepared for each day of measurements Pollen grains were counted along four longitudinal transects which were divided into 2 mm 1 hourly intervals the daily average pollen concentration was expressed as grains/m3Meteorological data covering the 7 years of study were provided by an Automatic Weather Station Vaisala MAWS101 Helsinki Finland situated in the vicinity of the pollen monitoring site The meteorological factors considered for assessing the effect of weather conditions on airborne pollen were mean and maximum wind speed daily precipitation relative humidity mean minimum and maximum air temperature and the dew point temperatureDue to nonlinearity and nonnormality of the analyzed variables particularly visible in matrix histograms and scatter plots Spearman’s rank correlation analysis was used to examine the relationships between airborne Betula pollen concentrations and meteorological variables

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