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Short-term prediction of Betula airborne pollen concentration in Vigo (NW Spain) using logistic additive models and partially linear models

机译:使用逻辑加性模型和部分线性模型对维哥(西班牙西北部)的桦树气传播的花粉浓度进行短期预测

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Betula pollen is a common cause of pollinosis in localities in NW Spain and between 13% and 60% of individuals who are immunosensitive to pollen grains respond positively to its allergens. It is important in the case of all such people to be able to predict pollen concentrations in advance. We therefore undertook an aerobiological study in the city of Vigo (Pontevedra, Spain) from 1995 to 2001, using a Hirst active-impact pollen trap (VPPS 2000) situated in the city centre. Vigo presents a temperate maritime climate with a mean annual temperature of 14.9 °C and 1,412 mm annual total precipitation. This paper analyses two ways of quantifying the prediction of pollen concentration: first by means of a generalized additive regression model with the object of predicting whether the series of interest exceeds a certain threshold; second using a partially linear model to obtain specific prediction values for pollen grains. Both models use a self-explicative part and another formed by exogenous meteorological factors. The models were tested with data from 2001 (year in which the total precipitation registered was almost twice the climatological average overall during the flowering period), which were not used in formulating the models. A highly satisfactory classification and good forecasting results were achieved with the first and second approaches respectively. The estimated line taking into account temperature and a calm S–SW wind, corresponds to the real line recorded during 2001, which gives us an idea of the proposed model's validity.
机译:桦树花粉是西班牙西北部地区花粉症的常见原因,对花粉粒免疫敏感的人群中有13%至60%的人对其花粉过敏产生积极反应。对于所有这些人而言,重要的是能够预先预测花粉浓度。因此,我们使用位于市中心的Hirst主动撞击式花粉收集器(VPPS 2000),于1995年至2001年在比戈市(西班牙庞特维德拉)进行了一项航空生物学研究。维戈(Vigo)属海洋性温带气候,年平均气温为14.9°C,年平均降水量为1,412 mm。本文分析了两种量化花粉浓度预测的方法:首先,通过广义加性回归模型,以预测目标系列是否超过某个阈值为目标;第二种方法是使用部分线性模型来获取花粉粒的特定预测值。两种模式都使用自我说明部分,另一部分则由外因气象因素形成。使用2001年的数据(年份记录的总降水量几乎是开花期总体气候平均水平的两倍)对模型进行了测试,这些数据并未用于模型的建立。第一种和第二种方法分别获得了非常令人满意的分类和良好的预测结果。考虑到温度和西南风平稳的估算线与2001年记录的实际线相对应,这使我们对所提出的模型的有效性有了一个认识。

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