{"id":"https://openalex.org/W3195077117","doi":"https://doi.org/10.1109/iccta40200.2016.9513235","title":"Forecasting Rainfall Based On Hybrid Intelligent System","display_name":"Forecasting Rainfall Based On Hybrid Intelligent System","publication_year":2016,"publication_date":"2016-10-25","ids":{"openalex":"https://openalex.org/W3195077117","doi":"https://doi.org/10.1109/iccta40200.2016.9513235","mag":"3195077117"},"language":"en","primary_location":{"id":"doi:10.1109/iccta40200.2016.9513235","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccta40200.2016.9513235","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 26th International Conference on Computer Theory and Applications (ICCTA)","raw_type":"proceedings-article"},"type":"article","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/A5007349672","display_name":"Hatem Abdelkader","orcid":"https://orcid.org/0000-0003-0606-215X"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Hatem Abdel-Kader","raw_affiliation_strings":["Information Systems, Menufia University, Shibin Al Kawm, Egypt"],"affiliations":[{"raw_affiliation_string":"Information Systems, Menufia University, Shibin Al Kawm, Egypt","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031504120","display_name":"I. M. Selim","orcid":"https://orcid.org/0000-0001-5925-6383"},"institutions":[{"id":"https://openalex.org/I160419504","display_name":"Higher Technological Institute","ror":"https://ror.org/051q8jk17","country_code":"EG","type":"education","lineage":["https://openalex.org/I160419504"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Ibrahim Selim","raw_affiliation_strings":["Computer Science, Higher Technological Institute, Tenth of Ramadan City, Egypt"],"affiliations":[{"raw_affiliation_string":"Computer Science, Higher Technological Institute, Tenth of Ramadan City, Egypt","institution_ids":["https://openalex.org/I160419504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101098383","display_name":"Amira Ahmed","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Amira Ahmed","raw_affiliation_strings":["Information Systems, Menufia University, Shibin Al Kawm, Egypt"],"affiliations":[{"raw_affiliation_string":"Information Systems, Menufia University, Shibin Al Kawm, Egypt","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069703336","display_name":"Mona A. Mohamed","orcid":"https://orcid.org/0000-0002-3331-2882"},"institutions":[{"id":"https://openalex.org/I160419504","display_name":"Higher Technological Institute","ror":"https://ror.org/051q8jk17","country_code":"EG","type":"education","lineage":["https://openalex.org/I160419504"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Mona Mohamed","raw_affiliation_strings":["Information Systems, Higher Technological Institute, Tenth of Ramadan City, Egypt"],"affiliations":[{"raw_affiliation_string":"Information Systems, Higher Technological Institute, Tenth of Ramadan City, Egypt","institution_ids":["https://openalex.org/I160419504"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5007349672"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.2153302,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2","issue":null,"first_page":"56","last_page":"61"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9962999820709229,"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"}},"topics":[{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9962999820709229,"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"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9814000129699707,"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"}},{"id":"https://openalex.org/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.9807000160217285,"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/particle-swarm-optimization","display_name":"Particle swarm optimization","score":0.6669384241104126},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6360548734664917},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.575995683670044},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.5744990110397339},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.5741788744926453},{"id":"https://openalex.org/keywords/wind-speed","display_name":"Wind speed","score":0.5338503122329712},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.5244446396827698},{"id":"https://openalex.org/keywords/hybrid-system","display_name":"Hybrid system","score":0.42714864015579224},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3330512046813965},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3178035020828247},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.2535369098186493},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.176316499710083},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.15102291107177734}],"concepts":[{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.6669384241104126},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6360548734664917},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.575995683670044},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.5744990110397339},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.5741788744926453},{"id":"https://openalex.org/C161067210","wikidata":"https://www.wikidata.org/wiki/Q1464943","display_name":"Wind speed","level":2,"score":0.5338503122329712},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.5244446396827698},{"id":"https://openalex.org/C50897621","wikidata":"https://www.wikidata.org/wiki/Q2665508","display_name":"Hybrid system","level":2,"score":0.42714864015579224},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3330512046813965},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3178035020828247},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.2535369098186493},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.176316499710083},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.15102291107177734},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccta40200.2016.9513235","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccta40200.2016.9513235","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 26th International Conference on Computer Theory and Applications (ICCTA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.41999998688697815,"display_name":"Climate action","id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320324156","display_name":"Zagazig University","ror":"https://ror.org/053g6we49"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1586335931","https://openalex.org/W1820051232","https://openalex.org/W2057440314","https://openalex.org/W2106351878","https://openalex.org/W2137699621","https://openalex.org/W2145237692","https://openalex.org/W2161715150","https://openalex.org/W2166998380","https://openalex.org/W2183189662","https://openalex.org/W2186104583","https://openalex.org/W2188355796","https://openalex.org/W2325235630","https://openalex.org/W2338837925","https://openalex.org/W2388652475","https://openalex.org/W2479631876","https://openalex.org/W2509746057","https://openalex.org/W2543580944","https://openalex.org/W2613057783","https://openalex.org/W4285719527","https://openalex.org/W6686114281","https://openalex.org/W6721574430"],"related_works":["https://openalex.org/W2076543106","https://openalex.org/W4322009192","https://openalex.org/W4320483926","https://openalex.org/W2019891950","https://openalex.org/W2085842814","https://openalex.org/W4286643620","https://openalex.org/W2523437662","https://openalex.org/W2559793074","https://openalex.org/W4387048144","https://openalex.org/W3203207972"],"abstract_inverted_index":{"Forecasting":[0],"the":[1,6,15,57,121,128],"weather":[2,84],"in":[3,11,47,64],"future":[4],"won":[5],"attention":[7],"of":[8,59,127,137],"many":[9],"researchers":[10],"different":[12],"countries":[13],"around":[14],"world.":[16],"In":[17],"this":[18],"work":[19],"a":[20],"robust":[21],"hybrid":[22,129],"technique":[23,55,130],"was":[24],"applied":[25],"to":[26,113],"forecast":[27],"rainfall":[28,115],"by":[29,79],"combining":[30],"Particle":[31],"Swarm":[32],"Optimization":[33],"based":[34,81,116],"Learning":[35],"Automata":[36],"(PSOLA)":[37,80],"and":[38,73,98],"Multi-Layer":[39],"Perceptron":[40],"(MLP)":[41],"which":[42],"is":[43,140],"popular":[44],"kind":[45],"used":[46],"Feed":[48],"Forward":[49],"Neural":[50],"Network":[51],"(FFNN).":[52],"The":[53,124],"proposed":[54],"solves":[56],"flaw":[58],"PSO":[60],"through":[61],"implementing":[62],"it":[63],"two":[65],"steps,":[66],"first":[67],"step":[68,75],"construct":[69],"ANN":[70],"-":[71],"MLP":[72,112],"second":[74,122],"generate":[76],"optimal":[77],"weights":[78,118],"on":[82,117],"four":[83],"parameters.":[85],"These":[86],"parameters":[87,103],"are":[88],"Minimum":[89],"temperature":[90,94],"(Min":[91],"temperature),":[92,96],"Maximum":[93],"(Max":[95],"Humidity,":[97],"Wind":[99],"Speed":[100],"as":[101,109],"input":[102],"whereas":[104],"rain":[105],"rate":[106],"parameter":[107],"considered":[108],"output.":[110],"Trained":[111],"predict":[114],"driven":[119],"from":[120],"phase.":[123],"simulation":[125],"result":[126],"represents":[131],"that":[132],"Mean":[133],"Square":[134],"Error":[135],"(MSE)":[136],"testing":[138],"dataset":[139],"0.9.":[141]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}