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Local Rainfall Forecast System based on Time Series Analysis and Neural Networks

机译:基于时间序列分析和神经网络的局部降雨预报系统

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摘要

Rainfall is one of the most important events in daily life of human beings. During several decades, scientists have been trying to characterize the weather, current forecasts are based on high complex dynamic models. In this paper is presented a local rainfall forecast system based on Time Series analysis and Neural Networks. This model tries to complement the currently state of the art ensembles, from a locally historical perspective, where the model definition is not so dependent from the exact values of the initial conditions. After several year taking data, expert meteorologists proposed this approximation to characterize the local weather behavior, that is being automated by this system in different stages. However the whole system is introduced, it is focused on the different rainfall events situation classification as well as the time series analysis and forecast
机译:降雨是人类日常生活中最重要的事件之一。在过去的几十年中,科学家一直试图描述天气的特征,目前的预测是基于高度复杂的动态模型。本文提出了一种基于时间序列分析和神经网络的局部降雨预报系统。从局部历史的角度来看,该模型试图补充当前最先进的集成体,其中模型定义并不完全依赖于初始条件的确切值。经过数年的数据采集后,专业的气象学家提出了这种近似值,以表征当地的天气状况,并由该系统在不同阶段将其自动化。但是介绍了整个系统,它着重于不同的降雨事件情况分类以及时间序列分析和预报

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