Implementation of Deep Learning Technique for Streamflow Prediction

Name: Implementation of Deep Learning Technique for Streamflow Prediction
Brand: LAP LAMBERT Academic Publishing
SKU: 9786206844822
Price: 22282 HUF
Availability: InStock

Szerző: Sarmad Latif

Nyelv:

Kötés: Puha kötésű

Kiadó: LAP LAMBERT Academic Publishing

Elérhetőség: Beszállítói készleten

Küldés 8-11 napon belül

22 282 Ft

The control and management of water resources is greatly aided by dams and reservoirs, which have be...

Információk a könyvről

Szerző

Sarmad Latif

Nyelv

Angol

Kötés

Könyv - Puha kötésű

Kiadva

2023

oldal

188

EAN

9786206844822

ISBN

620684482X

Enbook ID

44620871

Kiadó

LAP LAMBERT Academic Publishing

Súly

298

Méretek

150 x 220 x 12

Teljes leírás

The control and management of water resources is greatly aided by dams and reservoirs, which have benefited human societies in many ways. These benefits include enhanced human health, increased food production, access to clean water for domestic and industrial use, economic growth, irrigation, the production of hydropower, and flood control. An important non-engineering step to verify flood-control measures and improve water supply efficiency is accurate inflow forecasting. Furthermore, as inflow is the primary input into reservoirs, precise inflow prediction can provide recommendations for reservoir development and management. The purpose of this study is to compare how deep learning algorithms and traditional machine learning algorithms are used to reservoir inflow prediction. LSTM, as an effective deep learning model, outperformed other conventional machine learning models in forecasting reservoir inflow. The findings of the current study could be in direct interest for global water organizations, public and private water sectors around the world.

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Implementation of Deep Learning Technique for Streamflow Prediction

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