{"id":"https://openalex.org/W1978128908","doi":"https://doi.org/10.1061/(asce)0733-9437(2002)128:4(224)","title":"Estimating Evapotranspiration using Artificial Neural Network","display_name":"Estimating Evapotranspiration using Artificial Neural Network","publication_year":2002,"publication_date":"2002-07-28","ids":{"openalex":"https://openalex.org/W1978128908","doi":"https://doi.org/10.1061/(asce)0733-9437(2002)128:4(224)","mag":"1978128908"},"language":"en","primary_location":{"id":"doi:10.1061/(asce)0733-9437(2002)128:4(224)","doi":"https://doi.org/10.1061/(asce)0733-9437(2002)128:4(224)","is_oa":false,"landing_page_url":"https://doi.org/10.1061/(asce)0733-9437(2002)128:4(224)","pdf_url":null,"source":{"id":"https://openalex.org/S196009193","display_name":"Journal of Irrigation and Drainage Engineering","issn_l":"0733-9437","issn":["0733-9437","1943-4774"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-b","jufo-1","norway-1","poland-70","russia-white-list-2"],"host_organization":"https://openalex.org/P4310315747","host_organization_name":"American Society of Civil Engineers","host_organization_lineage":["https://openalex.org/P4310315747"],"host_organization_lineage_names":["American Society of Civil Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Irrigation and Drainage Engineering","raw_type":"journal-article"},"parent_works":[],"lineage":["https://openalex.org/W1978128908"],"child_works_count":0,"type":"article","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5005151894","display_name":"Manoranjan Kumar","orcid":"https://orcid.org/0000-0002-7096-3289","observed_orcids":["https://orcid.org/0000-0002-7096-3289"]},"institutions":[{"id":"https://openalex.org/I145894827","display_name":"Indian Institute of Technology Kharagpur","ror":"https://ror.org/03w5sq511","country_code":"IN","type":"education","lineage":["https://openalex.org/I145894827"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"M. Kumar","raw_affiliation_strings":["Research Scholar, Dept. of Agricultural and Food Engineering,  Indian Institute of Technology, Kharagpur WB\u2009721\u2009302, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research Scholar, Dept. of Agricultural and Food Engineering,  Indian Institute of Technology, Kharagpur WB\u2009721\u2009302, India","institution_ids":["https://openalex.org/I145894827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112618468","display_name":"N. S. Raghuwanshi","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I145894827","display_name":"Indian Institute of Technology Kharagpur","ror":"https://ror.org/03w5sq511","country_code":"IN","type":"education","lineage":["https://openalex.org/I145894827"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"N. S. Raghuwanshi","raw_affiliation_strings":["Associate Professor, Dept. of Agricultural and Food Engineering,  Indian Institute of Technology, Kharagpur WB\u2009721\u2009302, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Associate Professor, Dept. of Agricultural and Food Engineering,  Indian Institute of Technology, Kharagpur WB\u2009721\u2009302, India","institution_ids":["https://openalex.org/I145894827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048861401","display_name":"Rajendra Prasad Singh","orcid":"https://orcid.org/0000-0002-6597-9737","observed_orcids":["https://orcid.org/0000-0002-6597-9737"]},"institutions":[{"id":"https://openalex.org/I145894827","display_name":"Indian Institute of Technology Kharagpur","ror":"https://ror.org/03w5sq511","country_code":"IN","type":"education","lineage":["https://openalex.org/I145894827"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"R. Singh","raw_affiliation_strings":["Associate Professor, Dept. of Agricultural and Food Engineering,  Indian Institute of Technology, Kharagpur WB\u2009721\u2009302, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Associate Professor, Dept. of Agricultural and Food Engineering,  Indian Institute of Technology, Kharagpur WB\u2009721\u2009302, India","institution_ids":["https://openalex.org/I145894827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112078345","display_name":"W. W. Wallender","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I84218800","display_name":"University of California, Davis","ror":"https://ror.org/05rrcem69","country_code":"US","type":"education","lineage":["https://openalex.org/I84218800"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"W. W. Wallender","raw_affiliation_strings":["Professor, Dept. of Biological and Agricultural Engineering and Dept. of Hydrologic Science, Univ. of California, Davis, CA\u200995616"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Professor, Dept. of Biological and Agricultural Engineering and Dept. of Hydrologic Science, Univ. of California, Davis, CA\u200995616","institution_ids":["https://openalex.org/I84218800"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111495427","display_name":"William O. Pruitt","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I84218800","display_name":"University of California, Davis","ror":"https://ror.org/05rrcem69","country_code":"US","type":"education","lineage":["https://openalex.org/I84218800"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"W. O. Pruitt","raw_affiliation_strings":["Emeritus Irrigation Engineer, Dept. of Hydrologic Science, Univ. of California, Davis, CA\u200995616"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Emeritus Irrigation Engineer, Dept. of Hydrologic Science, Univ. of California, Davis, CA\u200995616","institution_ids":["https://openalex.org/I84218800"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":6.5667,"has_fulltext":false,"cited_by_count":533,"citation_normalized_percentile":{"value":0.95844841,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"128","issue":"4","first_page":"224","last_page":"233"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11490","display_name":"Hydrological Forecasting Using AI","score":0.9926999807357788,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11490","display_name":"Hydrological Forecasting Using AI","score":0.9926999807357788,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11186","display_name":"Hydrology and Drought Analysis","score":0.004900000058114529,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.000699999975040555,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/evapotranspiration-estimation","display_name":"evapotranspiration estimation","score":0.9049999713897705},{"id":"https://openalex.org/keywords/reference-evapotranspiration","display_name":"reference evapotranspiration","score":0.9139999747276306},{"id":"https://openalex.org/keywords/neural-network","display_name":"artificial neural networks","score":0.9760000109672546},{"id":"https://openalex.org/keywords/penman-monteith-equation","display_name":"Penman-Monteith equation","score":0.8669999837875366},{"id":"https://openalex.org/keywords/backpropagation","display_name":"backpropagation","score":0.656000018119812},{"id":"https://openalex.org/keywords/hidden-layer-architecture","display_name":"hidden layer architecture","score":0.6480000019073486},{"id":"https://openalex.org/keywords/lysimeter-measurements","display_name":"lysimeter measurements","score":0.722000002861023},{"id":"https://openalex.org/keywords/davis-california","display_name":"Davis, California","score":0.7210000157356262}],"concepts":[{"id":"https://openalex.org/C85871539","wikidata":"https://www.wikidata.org/wiki/Q734533","display_name":"Lysimeter","level":3,"score":0.7983808517456055},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.7519418001174927},{"id":"https://openalex.org/C176783924","wikidata":"https://www.wikidata.org/wiki/Q828158","display_name":"Evapotranspiration","level":2,"score":0.7064210772514343},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.6860336661338806},{"id":"https://openalex.org/C161067210","wikidata":"https://www.wikidata.org/wiki/Q1464943","display_name":"Wind speed","level":2,"score":0.5843297839164734},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5065721273422241},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.43809887766838074},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.41141176223754883},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38145920634269714},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.37962856888771057},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.36215195059776306},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.20611798763275146},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.19390931725502014},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.11118367314338684},{"id":"https://openalex.org/C159390177","wikidata":"https://www.wikidata.org/wiki/Q9161265","display_name":"Soil science","level":1,"score":0.06859374046325684},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C159750122","wikidata":"https://www.wikidata.org/wiki/Q96621023","display_name":"Soil water","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1061/(asce)0733-9437(2002)128:4(224)","doi":"https://doi.org/10.1061/(asce)0733-9437(2002)128:4(224)","is_oa":false,"landing_page_url":"https://doi.org/10.1061/(asce)0733-9437(2002)128:4(224)","pdf_url":null,"source":{"id":"https://openalex.org/S196009193","display_name":"Journal of Irrigation and Drainage Engineering","issn_l":"0733-9437","issn":["0733-9437","1943-4774"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-b","jufo-1","norway-1","poland-70","russia-white-list-2"],"host_organization":"https://openalex.org/P4310315747","host_organization_name":"American Society of Civil Engineers","host_organization_lineage":["https://openalex.org/P4310315747"],"host_organization_lineage_names":["American Society of Civil Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Irrigation and Drainage Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W568718827","https://openalex.org/W1554203287","https://openalex.org/W1943333985","https://openalex.org/W1969226924","https://openalex.org/W1969974566","https://openalex.org/W1981466446","https://openalex.org/W1987414283","https://openalex.org/W1996150433","https://openalex.org/W2011412119","https://openalex.org/W2013829694","https://openalex.org/W2018790612","https://openalex.org/W2019451733","https://openalex.org/W2033083046","https://openalex.org/W2048509079","https://openalex.org/W2052650612","https://openalex.org/W2055120878","https://openalex.org/W2057427964","https://openalex.org/W2065773237","https://openalex.org/W2089145279","https://openalex.org/W2090084153","https://openalex.org/W2094447130","https://openalex.org/W2164017619","https://openalex.org/W2553436524"],"related_works":["https://openalex.org/W3035813928","https://openalex.org/W7099749997","https://openalex.org/W2605872664","https://openalex.org/W1969763679","https://openalex.org/W2560398905","https://openalex.org/W3095526344","https://openalex.org/W2928632365","https://openalex.org/W2042681234","https://openalex.org/W2886600250","https://openalex.org/W4377087044"],"abstract_inverted_index":{"This":[0,192],"study":[1],"investigates":[2],"the":[3,21,26,38,53,57,66,110,135,149,173,181,197,202,225,249,263,270],"utility":[4],"of":[5,12,23,40,49,59,72,88,107,151,155,165],"artificial":[6],"neural":[7],"networks":[8,111],"(ANNs)":[9],"for":[10,86,93,102,188,274],"estimation":[11,87],"daily":[13,89,115],"grass":[14],"reference":[15],"crop":[16],"evapotranspiration":[17],"(ETo)":[18],"and":[19,56,74,76,100,121,125,129,134,158,169,176,205,222,229],"compares":[20],"performance":[22],"ANNs":[24,41,218],"with":[25,37,69,78,114],"conventional":[27,271],"method":[28,204,251,272],"(Penman\u2013Monteith)":[29],"used":[30],"to":[31,248],"estimate":[32,156],"ETo.":[33],"Several":[34],"issues":[35],"associated":[36],"use":[39],"are":[42],"examined,":[43],"including":[44],"different":[45,95],"learning":[46,63,70,190,237],"methods,":[47,64],"number":[48,58],"processing":[50],"elements":[51],"in":[52,172,215],"hidden":[54,60],"layer(s),":[55],"layers.":[61],"Three":[62],"namely,":[65],"standard":[67,153],"back-propagation":[68],"rates":[71],"0.2":[73],"0.8,":[75],"backpropagation":[77],"momentum":[79],"were":[80,112,219],"considered.":[81],"The":[82,142,162],"best":[83,143],"ANN":[84,144,160,163,264],"architecture":[85,145,164],"ETo":[90,139,208,228,267],"was":[91,146,194],"obtained":[92],"two":[94],"data":[96,106,117,232],"sets":[97],"(Sets":[98],"1":[99],"2)":[101],"Davis,":[103],"Calif.":[104],"Using":[105],"Set":[108],"1,":[109],"trained":[113],"climatic":[116,231],"(solar":[118],"radiation,":[119],"maximum":[120,124],"minimum":[122,126,182],"temperature,":[123],"relative":[127],"humidity,":[128],"wind":[130],"speed)":[131],"as":[132,140,209,246],"input":[133],"Penman\u2013Monteith":[136],"(PM)":[137,273],"estimated":[138],"output.":[141],"selected":[147],"on":[148,255],"basis":[150],"weighted":[152],"error":[154],"(WSEE)":[157],"minimal":[159],"architecture.":[161],"6-7-1,":[166],"(six,":[167],"seven,":[168],"one":[170],"neuron(s)":[171],"input,":[174],"hidden,":[175],"output":[177],"layers,":[178],"respectively)":[179],"gave":[180,239],"WSEE":[183,198,241],"(less":[184,242],"than":[185,196,243,269],"0.3":[186],"mm/day)":[187,200,245],"all":[189,236],"methods.":[191],"value":[193],"lower":[195],"(0.74":[199],"between":[201],"PM":[203,250],"lysimeter":[206,226],"measured":[207,227],"reported":[210],"by":[211],"Jensen":[212],"et":[213],"al.":[214],"1990.":[216],"Similarly,":[217],"trained,":[220],"validated,":[221],"tested":[223],"using":[224],"corresponding":[230],"(Set":[233],"2).":[234],"Again,":[235],"methods":[238],"less":[240],"0.60":[244],"compared":[247],"(0.97":[252],"mm/day).":[253],"Based":[254],"these":[256],"results,":[257],"it":[258],"can":[259,265],"be":[260],"concluded":[261],"that":[262],"predict":[266],"better":[268],"Davis.":[275]},"counts_by_year":[{"year":2026,"cited_by_count":11},{"year":2025,"cited_by_count":17},{"year":2024,"cited_by_count":27},{"year":2023,"cited_by_count":35},{"year":2022,"cited_by_count":35},{"year":2021,"cited_by_count":36},{"year":2020,"cited_by_count":38},{"year":2019,"cited_by_count":23},{"year":2018,"cited_by_count":25},{"year":2017,"cited_by_count":32},{"year":2016,"cited_by_count":31},{"year":2015,"cited_by_count":25},{"year":2014,"cited_by_count":20},{"year":2013,"cited_by_count":23},{"year":2012,"cited_by_count":29}],"updated_date":"2026-11-12T12:28:57.059296","created_date":"2016-06-24T00:00:00"}