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Intelligent data classification and aggregation in wireless sensors for flood forecasting system

机译:洪水预报系统无线传感器中的智能数据分类和聚合

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Flood is a major natural hazard in the world. For the period 1996-2005, about 80% of global natural disasters were meteorological or hydro. The floods have affected an average of 66 million people per year between 1973 and 1997. By these statistics, floods are considered the disasters that produce the most damage. Thats why we must handling floods data with great caution since human life is at stake. In this paper, we present an intelligent model that gathers data received from the wireless sensors and reach them in an intelligent way on one hand, on the other hand, it detects erroneous or redundant data to classify them to just have reliable and adequate data to be stored in the database in order to be processed in the decision support system for real time flood forecasting by using of the multi-agent system (MAS) to process data, eliminate redundancy, non-useful and erroneous data and establish collaboration between mobile agents to send the results to the base station.
机译:洪水是世界上的主要自然灾害。在1996年至2005年期间,全球约80%的自然灾害是气象或水灾。 1973年至1997年,洪水平均每年影响6600万人。根据这些统计数据,洪水被认为是造成最大破坏的灾害。这就是为什么我们必须非常谨慎地处理洪水数据,因为生命受到威胁。在本文中,我们提出了一个智能模型,该模型可以收集从无线传感器接收的数据,并以一种智能的方式到达它们,另一方面,它会检测错误或冗余的数据以将其分类为仅具有可靠且足够的数据,通过使用多代理系统(MAS)处理数据,消除冗余,无用和错误数据并在移动代理之间建立协作,将其存储在数据库中,以便在决策支持系统中进行处理以进行实时洪水预报将结果发送到基站。

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