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The Decision Support System for the Classification of Allergenic Pollen Types Based on Fuzzy Expert Data of Pollen Features on the Microscope Images

机译:基于显微镜图像上花粉特征的模糊专家数据对过敏性花粉类型分类的决策支持系统

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The article is devoted to the development of the decision support system for the classification of allergic pollen types based on fuzzy expert data of their features on the microscope images and the improvement of the identification method of this system. The genetic algorithm of the classifier training has been improved taking into account the spatial-temporal features of the distribution of pollen in the air, namely: adaptive fitness function for evaluating solutions, tournament selection with elitism and initialization of the initial population, allowing to improve the accuracy of classification. The example of the proposed system and method application based on real expert data of Vinnytsia monitoring station which is the part of European Aeroallergen Network is shown.
机译:本文基于其特征的模糊专家数据对显微镜图像特征的模糊专家数据以及改进该系统的识别方法的模糊专家数据,本文致力于发展过敏花粉类型的决策支持系统。已经提高了分类器培训的遗传算法,考虑到空气中花粉分布的空间时间特征,即:用于评估解决方案的自适应性能,锦标赛选择与初始人口的初始化,允许改进分类的准确性。基于欧洲航空预报网络的一部分Vinnytsia监测站的真实专家数据的建议系统和方法应用程序的示例。

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