Evaluation of soft-computing techniques for pan evaporation estimation
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Title |
Evaluation of soft-computing techniques for pan evaporation estimation
Not Available |
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Creator |
AMIT KUMAR
A. SARANGI D.K. SINGH I. MANI K. K. BANDHYOPADHYAY S. DASH M. KHANNA |
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Subject |
Evaporation
Prediction Neural network Irrigation scheduling LSTM network |
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Description |
Not Available
Estimation of pan evaporation (Epan) can be useful in judicious irrigation scheduling for enhancing agricultural water productivity. The aim of present study was to assess the efficacy of state-of-the-art LSTM and ANN for daily Epan estimation using meteorological data. Besides this, the effect of static time-series (Julian date) as additional input variable was investigated on performance of soft-computing techniques. For this purpose, the models were trained, tested and validated with eight meteorological variables of 37 years by using preceding 1-, 3- and 5- days’ information. Data were partitioned into three groups as training (60%), testing (20%), and validation (20%) components. It was observed that the models performed well (best) with preceding 5-days meteorological information followed by 3-days and 1-day. However, all LSTMs simulated peak value of Epan was more accurate as compared to lower values. Meteorological data with julian date improved the performance of LSTMs (0.75 Not Available |
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Date |
2024-03-26T12:30:50Z
2024-03-26T12:30:50Z 2024-03-01 |
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Type |
Research Paper
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Identifier |
Kumar, A., Sarangi, A., Singh, D.K., Mani, I., Bandyopadhyay, K. K., Dash, S. and Khanna, M. (2024). Evaluation of soft-computing techniques for pan evaporation estimation. Journal of Agrometeorology, 26(1), 56-62 (NAAS rating: 6.70)
Not Available http://krishi.icar.gov.in/jspui/handle/123456789/81690 |
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Language |
English
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Relation |
Not Available;
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