Flood Prediction Using Flow and Depth Measurement with Artificial Neural Network in Canals

机译：利用流通神经网络的流量和深度测量洪水预测

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Flood acts as a major cause of destruction, loss of property and life. This results in sociological as well as economic loss. Prediction plays a major role to avoid such calamities. In this paper, a method of two level hierarchical predictions for flood detection using Artificial Neural Networks has been proposed, which is one of the efficient computational tools. It is implemented in a model created based on Malampuzha Dam, Palakkad, Kerala. The dam opening is the first level of prediction. The water from the dam is released to canals and flow rate and level of water in one portion of canals is used to predict the possibility of a flood in the next portion of the canal. This constitutes the succeeding level of flood prediction.

机译：洪水作为破坏的主要原因，失去财产和生活。这导致社会学和经济损失。预测发挥着重要作用以避免这种灾难。在本文中，提出了一种使用人工神经网络的洪水检测的两个级别分层预测的方法，这是一种有效的计算工具之一。它在基于Malampuzha Dam，Palakkad，Kerala的模型中实现。坝开口是第一级预测。来自大坝的水被释放到运河和流速和一部分水位，用于预测运河的下一部分中洪水的可能性。这构成了洪水预测的后续水平。

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来源
《International Conference on Computing Methodologies and Communication》|2019年|627 p. :|共4页
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作者
C Nikhil Binoy; N Arjun; C Keerthi; S Sreerag; Ashwin H Nair;
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中图分类计算技术、计算机技术;
关键词
canals; dams; floods; neural nets; structural engineering computing; water resources;

机译：运河;水坝;洪水;神经网;结构工程计算;水资源;

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2. Using artificial neural networks for prediction of alternate depth shaped on rectangular channel in open channel flow [J] . Senayi Donmez Energy education science and technology . 2011,第1期

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Flood Prediction Using Flow and Depth Measurement with Artificial Neural Network in Canals

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