{"id":"https://openalex.org/W4407937597","doi":"https://doi.org/10.1109/access.2025.3545449","title":"A Hybrid Prediction Model Integrating Artificial Intelligence and Geospatial Analysis for Disaster Management","display_name":"A Hybrid Prediction Model Integrating Artificial Intelligence and Geospatial Analysis for Disaster Management","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4407937597","doi":"https://doi.org/10.1109/access.2025.3545449"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3545449","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3545449","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3545449","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5052926022","display_name":"Muhammad Asim Saleem","orcid":"https://orcid.org/0000-0003-2709-5508"},"institutions":[{"id":"https://openalex.org/I158708052","display_name":"Chulalongkorn University","ror":"https://ror.org/028wp3y58","country_code":"TH","type":"education","lineage":["https://openalex.org/I158708052"]}],"countries":["TH"],"is_corresponding":true,"raw_author_name":"Muhammad Asim Saleem","raw_affiliation_strings":["Department of Electrical Engineering, Center of Excellence in Artificial Intelligence, Machine Learning, and Smart Grid Technology, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand","Department of Electrical Engineering, Faculty of Engineering, Center of Excellence in Artificial Intelligence, Machine Learning, and Smart Grid Technology, Chulalongkorn University, Bangkok, Thailand"],"raw_orcid":"https://orcid.org/0000-0003-2709-5508","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Center of Excellence in Artificial Intelligence, Machine Learning, and Smart Grid Technology, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand","institution_ids":["https://openalex.org/I158708052"]},{"raw_affiliation_string":"Department of Electrical Engineering, Faculty of Engineering, Center of Excellence in Artificial Intelligence, Machine Learning, and Smart Grid Technology, Chulalongkorn University, Bangkok, Thailand","institution_ids":["https://openalex.org/I158708052"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043931111","display_name":"Watit Benjapolakul","orcid":"https://orcid.org/0000-0001-6134-7268"},"institutions":[{"id":"https://openalex.org/I158708052","display_name":"Chulalongkorn University","ror":"https://ror.org/028wp3y58","country_code":"TH","type":"education","lineage":["https://openalex.org/I158708052"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Watit Benjapolakul","raw_affiliation_strings":["Department of Electrical Engineering, Center of Excellence in Artificial Intelligence, Machine Learning, and Smart Grid Technology, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand","Department of Electrical Engineering, Faculty of Engineering, Center of Excellence in Artificial Intelligence, Machine Learning, and Smart Grid Technology, Chulalongkorn University, Bangkok, Thailand"],"raw_orcid":"https://orcid.org/0000-0001-6134-7268","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Center of Excellence in Artificial Intelligence, Machine Learning, and Smart Grid Technology, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand","institution_ids":["https://openalex.org/I158708052"]},{"raw_affiliation_string":"Department of Electrical Engineering, Faculty of Engineering, Center of Excellence in Artificial Intelligence, Machine Learning, and Smart Grid Technology, Chulalongkorn University, Bangkok, Thailand","institution_ids":["https://openalex.org/I158708052"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019433340","display_name":"Wattanasak Srisiri","orcid":"https://orcid.org/0009-0006-2036-9317"},"institutions":[{"id":"https://openalex.org/I158708052","display_name":"Chulalongkorn University","ror":"https://ror.org/028wp3y58","country_code":"TH","type":"education","lineage":["https://openalex.org/I158708052"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Wattanasak Srisiri","raw_affiliation_strings":["Department of Electrical Engineering, Center of Excellence in Artificial Intelligence, Machine Learning, and Smart Grid Technology, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand","Department of Electrical Engineering, Faculty of Engineering, Center of Excellence in Artificial Intelligence, Machine Learning, and Smart Grid Technology, Chulalongkorn University, Bangkok, Thailand"],"raw_orcid":"https://orcid.org/0009-0006-2036-9317","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Center of Excellence in Artificial Intelligence, Machine Learning, and Smart Grid Technology, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand","institution_ids":["https://openalex.org/I158708052"]},{"raw_affiliation_string":"Department of Electrical Engineering, Faculty of Engineering, Center of Excellence in Artificial Intelligence, Machine Learning, and Smart Grid Technology, Chulalongkorn University, Bangkok, Thailand","institution_ids":["https://openalex.org/I158708052"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043748658","display_name":"Surachai Chaitusaney","orcid":"https://orcid.org/0000-0002-4194-3342"},"institutions":[{"id":"https://openalex.org/I158708052","display_name":"Chulalongkorn University","ror":"https://ror.org/028wp3y58","country_code":"TH","type":"education","lineage":["https://openalex.org/I158708052"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Surachai Chaitusaney","raw_affiliation_strings":["Department of Electrical Engineering, Center of Excellence in Artificial Intelligence, Machine Learning, and Smart Grid Technology, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand","Department of Electrical Engineering, Faculty of Engineering, Center of Excellence in Artificial Intelligence, Machine Learning, and Smart Grid Technology, Chulalongkorn University, Bangkok, Thailand"],"raw_orcid":"https://orcid.org/0000-0002-4194-3342","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Center of Excellence in Artificial Intelligence, Machine Learning, and Smart Grid Technology, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand","institution_ids":["https://openalex.org/I158708052"]},{"raw_affiliation_string":"Department of Electrical Engineering, Faculty of Engineering, Center of Excellence in Artificial Intelligence, Machine Learning, and Smart Grid Technology, Chulalongkorn University, Bangkok, Thailand","institution_ids":["https://openalex.org/I158708052"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008465270","display_name":"Pasu Kaewplung","orcid":"https://orcid.org/0000-0002-5760-6543"},"institutions":[{"id":"https://openalex.org/I158708052","display_name":"Chulalongkorn University","ror":"https://ror.org/028wp3y58","country_code":"TH","type":"education","lineage":["https://openalex.org/I158708052"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Pasu Kaewplung","raw_affiliation_strings":["Department of Electrical Engineering, Center of Excellence in Artificial Intelligence, Machine Learning, and Smart Grid Technology, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand","Department of Electrical Engineering, Faculty of Engineering, Center of Excellence in Artificial Intelligence, Machine Learning, and Smart Grid Technology, Chulalongkorn University, Bangkok, Thailand"],"raw_orcid":"https://orcid.org/0000-0002-5760-6543","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Center of Excellence in Artificial Intelligence, Machine Learning, and Smart Grid Technology, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand","institution_ids":["https://openalex.org/I158708052"]},{"raw_affiliation_string":"Department of Electrical Engineering, Faculty of Engineering, Center of Excellence in Artificial Intelligence, Machine Learning, and Smart Grid Technology, Chulalongkorn University, Bangkok, Thailand","institution_ids":["https://openalex.org/I158708052"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5052926022"],"corresponding_institution_ids":["https://openalex.org/I158708052"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":14.5431,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.98559105,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"13","issue":null,"first_page":"43716","last_page":"43727"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13018","display_name":"Seismology and Earthquake Studies","score":0.7121999859809875,"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/T13018","display_name":"Seismology and Earthquake Studies","score":0.7121999859809875,"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/geospatial-analysis","display_name":"Geospatial analysis","score":0.8079538941383362},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7152433395385742},{"id":"https://openalex.org/keywords/emergency-management","display_name":"Emergency management","score":0.5044037103652954},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3629220128059387},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3515123724937439},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.13991820812225342},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.08443009853363037}],"concepts":[{"id":"https://openalex.org/C9770341","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Geospatial analysis","level":2,"score":0.8079538941383362},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7152433395385742},{"id":"https://openalex.org/C62555980","wikidata":"https://www.wikidata.org/wiki/Q1460420","display_name":"Emergency management","level":2,"score":0.5044037103652954},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3629220128059387},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3515123724937439},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.13991820812225342},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.08443009853363037},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3545449","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3545449","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:5bd2fbf827b148d8980a7f3ccbad3dfe","is_oa":true,"landing_page_url":"https://doaj.org/article/5bd2fbf827b148d8980a7f3ccbad3dfe","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 13, Pp 43716-43727 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3545449","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3545449","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Climate action","score":0.8799999952316284,"id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W116302019","https://openalex.org/W2093457913","https://openalex.org/W2107331026","https://openalex.org/W2567854072","https://openalex.org/W2616101974","https://openalex.org/W2770617885","https://openalex.org/W2957630544","https://openalex.org/W2965881028","https://openalex.org/W2986218094","https://openalex.org/W3005359275","https://openalex.org/W3013263853","https://openalex.org/W3039888984","https://openalex.org/W3128965711","https://openalex.org/W3165227408","https://openalex.org/W3175605680","https://openalex.org/W3212132479","https://openalex.org/W4229369233","https://openalex.org/W4230451521","https://openalex.org/W4285392166","https://openalex.org/W4309288251","https://openalex.org/W4386764545","https://openalex.org/W4387187512","https://openalex.org/W4388224278","https://openalex.org/W4403123867","https://openalex.org/W4404294156"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W4367313141","https://openalex.org/W4280507437","https://openalex.org/W3118689035","https://openalex.org/W2553922746","https://openalex.org/W3048452028","https://openalex.org/W2786734537","https://openalex.org/W4379390828"],"abstract_inverted_index":{"A":[0],"natural":[1,22],"or":[2],"man-made":[3],"disaster":[4],"must":[5],"be":[6],"predicted":[7],"accurately":[8],"and":[9,20,27,41,52,76,96,101,123],"in":[10,59,70,92,110,139,164],"time.":[11],"Advanced":[12],"modelling":[13],"is":[14,33],"essential":[15],"to":[16,35,72,160],"predict":[17,36],"increasingly":[18],"frequent":[19],"intense":[21],"events,":[23],"enabling":[24],"better":[25],"response":[26],"recovery":[28],"strategies.":[29],"Hybrid":[30],"machine":[31,67,78],"learning":[32,68,79],"used":[34,58],"floods,":[37],"assess":[38],"earthquake":[39,108],"damage,":[40],"control":[42],"wildfires.":[43],"Convolutional":[44],"Neural":[45],"Networks":[46],"(CNNs),":[47],"Gradient":[48],"Boosting":[49],"Machines":[50,55],"(GBMs)":[51],"Support":[53],"Vector":[54],"(SVMs)":[56],"are":[57],"the":[60,65,105,135],"proposed":[61,66,82,153],"model.":[62],"We":[63],"evaluate":[64],"model":[69,84,155],"comparison":[71],"conventional":[73,157],"statistical":[74],"analysis":[75],"single":[77],"techniques.":[80],"The":[81,152],"hybrid":[83,154],"provided":[85],"90%":[86,122],"correct":[87],"predictions":[88],"for":[89],"flood":[90],"events":[91],"Bangladesh":[93],"with":[94,118,128,145],"precision":[95,120,147],"recall":[97,125],"values":[98],"of":[99,107,114,121,126,132,137,143,148],"88%":[100,144],"85%,":[102],"respectively.":[103],"In":[104,134],"assessment":[106],"damage":[109],"Japan,":[111],"an":[112,129,141],"accuracy":[113,142],"92%":[115],"was":[116],"achieved":[117],"a":[119,124,146],"89%":[127],"F1":[130],"score":[131],"89%.":[133],"management":[136],"wildfires":[138],"California,":[140],"85%":[149],"were":[150],"achieved.":[151],"outperforms":[156],"techniques":[158],"due":[159],"its":[161],"higher":[162],"reliability":[163],"predicting":[165],"floods.":[166]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":5}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}