{"id":"https://openalex.org/W4401880344","doi":"https://doi.org/10.1109/icps59941.2024.10640026","title":"Prediction of irrigation water requirement based on parallel CNN-LSTM model and Mann-Kendall test","display_name":"Prediction of irrigation water requirement based on parallel CNN-LSTM model and Mann-Kendall test","publication_year":2024,"publication_date":"2024-05-12","ids":{"openalex":"https://openalex.org/W4401880344","doi":"https://doi.org/10.1109/icps59941.2024.10640026"},"language":"en","primary_location":{"id":"doi:10.1109/icps59941.2024.10640026","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icps59941.2024.10640026","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 7th International Conference on Industrial Cyber-Physical Systems (ICPS)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101711953","display_name":"Wen Hao","orcid":"https://orcid.org/0000-0002-0487-2784"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Wen","raw_affiliation_strings":["Shenzhen University,College of Mechatronics and Control Engineering,Shenzhen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen University,College of Mechatronics and Control Engineering,Shenzhen,China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101317858","display_name":"Haochen Ma","orcid":null},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haochen Ma","raw_affiliation_strings":["Shenzhen University,College of Mechatronics and Control Engineering,Shenzhen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen University,College of Mechatronics and Control Engineering,Shenzhen,China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102025730","display_name":"Yu Du","orcid":"https://orcid.org/0000-0002-2239-4659"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Du","raw_affiliation_strings":["Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ),Shenzhen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ),Shenzhen,China","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101924366","display_name":"Jinchao Zhang","orcid":"https://orcid.org/0000-0003-4611-9675"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jinchao Zhang","raw_affiliation_strings":["Dongshen Intelligent Water Technology Company, LTD,Shenzhen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dongshen Intelligent Water Technology Company, LTD,Shenzhen,China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108449643","display_name":"Li He","orcid":null},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li He","raw_affiliation_strings":["Shenzhen University,College of Mechatronics and Control Engineering,Shenzhen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen University,College of Mechatronics and Control Engineering,Shenzhen,China","institution_ids":["https://openalex.org/I180726961"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11490","display_name":"Hydrological Forecasting Using AI","score":0.9847000241279602,"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":0.9847000241279602,"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/T11052","display_name":"Energy Load and Power Forecasting","score":0.9186000227928162,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9121999740600586,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.639362096786499},{"id":"https://openalex.org/keywords/test","display_name":"Test (biology)","score":0.5559174418449402},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48038560152053833},{"id":"https://openalex.org/keywords/irrigation","display_name":"Irrigation","score":0.4213997721672058},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3286590576171875},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.07852673530578613}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.639362096786499},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.5559174418449402},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48038560152053833},{"id":"https://openalex.org/C88862950","wikidata":"https://www.wikidata.org/wiki/Q11453","display_name":"Irrigation","level":2,"score":0.4213997721672058},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3286590576171875},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.07852673530578613},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icps59941.2024.10640026","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icps59941.2024.10640026","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 7th International Conference on Industrial Cyber-Physical Systems (ICPS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Clean water and sanitation","score":0.7599999904632568,"id":"https://metadata.un.org/sdg/6"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W2797746338","https://openalex.org/W2908043352","https://openalex.org/W2939035037","https://openalex.org/W3002846642","https://openalex.org/W3004026468","https://openalex.org/W3008737037","https://openalex.org/W3032611411","https://openalex.org/W3122281830","https://openalex.org/W3197773005","https://openalex.org/W4205205037","https://openalex.org/W4281902005","https://openalex.org/W4293490409","https://openalex.org/W4313570471","https://openalex.org/W4321616068","https://openalex.org/W4322769135"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"Accurate":[0],"prediction":[1,19,49],"of":[2,84,97,102,122,172,190],"irrigation":[3,10,46,140,173,186,194],"water":[4,11,47,141,174,191],"requirement":[5,48,96,142,175],"is":[6,75,109,113,128],"the":[7,14,31,66,72,81,89,95,99,119,125,134,158,162,168],"basis":[8],"for":[9,37,130,183],"conservation.":[12],"However,":[13],"widely":[15],"used":[16,114,129],"machine":[17],"learning":[18],"methods":[20],"do":[21],"not":[22],"utilize":[23],"spatiotemporal":[24,100],"information":[25,101,121],"between":[26],"related":[27],"features":[28],"effectively,":[29],"and":[30,58,117,148,170,187],"abrupt":[32],"mutation":[33,82],"data":[34,74,86,151],"processing":[35],"method":[36,50],"environmental":[38],"factors":[39],"requires":[40],"improvement.":[41],"This":[42,177],"study":[43,178],"proposes":[44],"an":[45],"using":[51],"a":[52,105,181],"parallel":[53,106],"Convolutional":[54],"Neural":[55],"Network":[56],"(CNN)":[57],"Long":[59],"Short-Term":[60],"Memory":[61],"network":[62,108,127],"(LSTM)":[63],"based":[64,79],"on":[65,80],"Mann-Kendall":[67,90],"test.":[68,91],"In":[69],"this":[70],"study,":[71],"non-stationary":[73],"segmented":[76],"into":[77],"subsequences":[78],"points":[83],"meteorological":[85],"detected":[87],"by":[88],"Then,":[92],"to":[93,115,137,154],"satisfy":[94],"extracting":[98],"input":[103],"features,":[104],"CNN-LSTM":[107],"built.":[110],"The":[111],"CNN":[112],"reextract":[116],"down-sample":[118],"spatial":[120],"features.":[123],"Furthermore,":[124],"LSTM":[126],"regression":[131],"fitting":[132],"in":[133,156,193],"time":[135],"dimension":[136],"realize":[138],"farmland":[139],"prediction.":[143,176],"Compared":[144],"with":[145,150],"CNN,":[146],"LSTM,":[147],"CNNLSTM":[149],"from":[152],"2020":[153],"2023":[155],"Beijing,":[157],"results":[159],"show":[160],"that":[161],"proposed":[163],"model":[164],"can":[165,179],"effectively":[166],"improve":[167],"accuracy":[169],"stability":[171],"provide":[180],"reference":[182],"intelligent":[184],"water-saving":[185],"optimal":[188],"allocation":[189],"resources":[192],"areas.":[195]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
