An extreme learning machine approach for modeling evapotranspiration using extrinsic inputs

Computers and Electronics in Agriculture

Volumn 121, Issue , 2016, Pages 385-392

  Patil, Amit Prakash ^a   Deka, Paresh Chandra ^a  

^a NATIONAL INSTITUTE OF TECHNOLOGY KARNATAKA   (India)

Author keywords

Arid region; Evapotranspiration; Extreme learning machine; Least square support vector machine; Limited data

Indexed keywords

ALGORITHMS; ARID REGIONS; ARTIFICIAL INTELLIGENCE; CROPS; EFFICIENCY; ERROR STATISTICS; EVAPOTRANSPIRATION; KNOWLEDGE ACQUISITION; LEARNING ALGORITHMS; MEAN SQUARE ERROR; NEURAL NETWORKS; SUPPORT VECTOR MACHINES;

EXTREME LEARNING MACHINE; HARGREAVES EQUATIONS; LEAST SQUARE SUPPORT VECTOR MACHINES; LIMITED DATA; REFERENCE CROP EVAPOTRANSPIRATIONS; ROOT MEAN SQUARED ERRORS; TEMPERATURE DATA; WEATHER STATIONS;

LEARNING SYSTEMS;

AIR TEMPERATURE; ALGORITHM; ARID REGION; DATA SET; EFFICIENCY MEASUREMENT; EVAPOTRANSPIRATION; LEAST SQUARES METHOD; MACHINE LEARNING; PERFORMANCE ASSESSMENT; SUPPORT VECTOR MACHINE; WATER USE; WEATHER STATION;

INDIA; JODHPUR; PALI; RAJASTHAN; THAR DESERT;

EID: 84954489395     PISSN: 01681699     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compag.2016.01.016     Document Type: Article

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