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首页> 外文会议>Autonomous air and ground sensing systems for agricultural optimization and phenotyping II >Automated information-analytical system for thunderstorm monitoring and early warning alarms using modern physical sensors and information technologies with elements of artificial intelligence
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Automated information-analytical system for thunderstorm monitoring and early warning alarms using modern physical sensors and information technologies with elements of artificial intelligence

机译：使用现代物理传感器和具有人工智能元素的信息技术，用于雷暴监视和预警警报的自动化信息分析系统

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摘要

Methods of artificial intelligence are a good solution for weather phenomena forecasting. They allow to process a large amount of diverse data. Recirculation Neural Networks is implemented in the paper for the system of thunderstorm events prediction. Large amounts of experimental data from lightning sensors and electric field mills networks are received and analyzed. The average recognition accuracy of sensor signals is calculated. It is shown that Recirculation Neural Networks is a promising solution in the forecasting of thunderstorms and weather phenomena, characterized by the high efficiency of the recognition elements of the sensor signals, allows to compress images and highlight their characteristic features for subsequent recognition.
机译：人工智能方法是天气预报的好方法。它们允许处理大量不同的数据。本文针对雷暴事件预测系统实现了循环神经网络。接收并分析了来自雷电传感器和电场研磨机网络的大量实验数据。计算传感器信号的平均识别精度。结果表明，循环神经网络在雷暴和天气现象的预测中是一个有前途的解决方案，其特征在于传感器信号的识别元件的高效性，可以压缩图像并突出其特征以进行后续识别。

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