Please use this identifier to cite or link to this item:
http://www.idr.iitkgp.ac.in/xmlui/handle/123456789/15243
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Sushanth, Kallem | - |
dc.date.accessioned | 2024-09-25T05:17:32Z | - |
dc.date.available | 2024-09-25T05:17:32Z | - |
dc.date.issued | 2024-01 | - |
dc.identifier.govdoc | NB18277 | - |
dc.identifier.uri | http://www.idr.iitkgp.ac.in/xmlui/handle/123456789/15243 | - |
dc.language.iso | en | en_US |
dc.publisher | IIT Kharagpur | en_US |
dc.subject | Bias Correction | en_US |
dc.subject | GFS Forecasts | en_US |
dc.subject | Irrigation Demand | en_US |
dc.subject | LSTM Model | en_US |
dc.subject | Reservoir Module | en_US |
dc.title | Effective Water Resources Management in a Reservoir-Regulated River Basin – A Novel Approach Using Distributed Hydrological Modelling and Machine Learning | en_US |
dc.type | Thesis | en_US |
Appears in Collections: | Effective Water Resources Management in a Reservoir-Regulated River Basin – A Novel Approach Using Distributed Hydrological Modelling and Machine Learning |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
NB18277_Abstract.pdf | 84.04 kB | Adobe PDF | View/Open | |
NB18277_Thesis.pdf Restricted Access | 8.7 MB | Adobe PDF | View/Open Request a copy |
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