Publication2020
Improved prediction of daily pan evaporation using Deep-LSTM model
The record
- Type
- Publication
- Date
- 1 June 2020
- Level
- National
- Journal
- Neural Computing and Applications
- Volume
- 32
- Issue
- 12
- Pages
- 7823-7838
- Published
- 1 June 2020
- DOI
- 10.1007/s00521-019-04127-7
- Scopus ID
- 85062735146
- ISSN
- 09410643
- Authors
- 4
- Open access
- No
- Citations
- 115
- International co-authorship
- No
- Co-author countries
- IN
Classification
Every label below carries the reasoning it was assigned on, the confidence band it was assigned in, and what produced it. The rubric is published.
UN Sustainable Development Goals
6.4 Substantially increase water-use efficiency and address water scarcity
Deep-LSTM neural network predicts daily pan evaporation with improved accuracy in drought-prone agro-climatic zones for optimized water resource management and irrigation.
- High confidence
- The subject matter is a strong and direct inference from the record type, the funding or organising body, or the programme context, even where the title alone is thin. Example: an ICMR-funded project against SDG 3, on the strength of the agency.
- Judged
- Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
13.1 Strengthen resilience and adaptive capacity to climate-related hazards and natural disasters
Evaporation estimation under climate variability improves climate resilience in water-stressed regions and agricultural drought adaptation.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Viksit Bharat @2047
vb-2.1 Agriculture and the rural economy
Water resource optimization and agricultural climate adaptation support rural economy resilience and agricultural sustainability.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
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- 1
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Citing this record
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KIIT Deemed to be University. “Improved prediction of daily pan evaporation using Deep-LSTM model”. Kortex.