{"id":"https://openalex.org/W3008197164","doi":"https://doi.org/10.3390/e22030261","title":"A Method Based on GA-CNN-LSTM for Daily Tourist Flow Prediction at Scenic Spots","display_name":"A Method Based on GA-CNN-LSTM for Daily Tourist Flow Prediction at Scenic Spots","publication_year":2020,"publication_date":"2020-02-25","ids":{"openalex":"https://openalex.org/W3008197164","doi":"https://doi.org/10.3390/e22030261","mag":"3008197164","pmid":"https://pubmed.ncbi.nlm.nih.gov/33286035"},"language":"en","primary_location":{"id":"doi:10.3390/e22030261","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e22030261","pdf_url":"https://www.mdpi.com/1099-4300/22/3/261/pdf?version=1584026583","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1099-4300/22/3/261/pdf?version=1584026583","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101095353","display_name":"Wenxing Lu","orcid":"https://orcid.org/0000-0002-2273-430X"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenxing Lu","raw_affiliation_strings":["Ministry of Education Key Laboratory of Process Optimization and Intelligent Decision-Making, Hefei University of Technology, Hefei 230009, China","School of Management, Hefei University of Technology, Hefei 230009, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ministry of Education Key Laboratory of Process Optimization and Intelligent Decision-Making, Hefei University of Technology, Hefei 230009, China","institution_ids":["https://openalex.org/I16365422"]},{"raw_affiliation_string":"School of Management, Hefei University of Technology, Hefei 230009, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076645249","display_name":"Haidong Rui","orcid":null},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Haidong Rui","raw_affiliation_strings":["School of Management, Hefei University of Technology, Hefei 230009, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Management, Hefei University of Technology, Hefei 230009, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102023161","display_name":"Changyong Liang","orcid":"https://orcid.org/0000-0001-9156-3885"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changyong Liang","raw_affiliation_strings":["Ministry of Education Key Laboratory of Process Optimization and Intelligent Decision-Making, Hefei University of Technology, Hefei 230009, China","School of Management, Hefei University of Technology, Hefei 230009, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ministry of Education Key Laboratory of Process Optimization and Intelligent Decision-Making, Hefei University of Technology, Hefei 230009, China","institution_ids":["https://openalex.org/I16365422"]},{"raw_affiliation_string":"School of Management, Hefei University of Technology, Hefei 230009, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040813960","display_name":"Li Jiang","orcid":"https://orcid.org/0000-0001-5599-7395"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Jiang","raw_affiliation_strings":["Ministry of Education Key Laboratory of Process Optimization and Intelligent Decision-Making, Hefei University of Technology, Hefei 230009, China","School of Management, Hefei University of Technology, Hefei 230009, China"],"raw_orcid":"https://orcid.org/0000-0001-5599-7395","affiliations":[{"raw_affiliation_string":"Ministry of Education Key Laboratory of Process Optimization and Intelligent Decision-Making, Hefei University of Technology, Hefei 230009, China","institution_ids":["https://openalex.org/I16365422"]},{"raw_affiliation_string":"School of Management, Hefei University of Technology, Hefei 230009, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063314671","display_name":"Shuping Zhao","orcid":"https://orcid.org/0000-0002-9832-9861"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuping Zhao","raw_affiliation_strings":["Ministry of Education Key Laboratory of Process Optimization and Intelligent Decision-Making, Hefei University of Technology, Hefei 230009, China","School of Management, Hefei University of Technology, Hefei 230009, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ministry of Education Key Laboratory of Process Optimization and Intelligent Decision-Making, Hefei University of Technology, Hefei 230009, China","institution_ids":["https://openalex.org/I16365422"]},{"raw_affiliation_string":"School of Management, Hefei University of Technology, Hefei 230009, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026208453","display_name":"Keqing Li","orcid":"https://orcid.org/0000-0001-5398-4486"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Keqing Li","raw_affiliation_strings":["School of Management, Hefei University of Technology, Hefei 230009, China"],"raw_orcid":"https://orcid.org/0000-0001-5398-4486","affiliations":[{"raw_affiliation_string":"School of Management, Hefei University of Technology, Hefei 230009, China","institution_ids":["https://openalex.org/I16365422"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5076645249"],"corresponding_institution_ids":["https://openalex.org/I16365422"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":12.2941,"has_fulltext":true,"cited_by_count":55,"citation_normalized_percentile":{"value":0.98505827,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"22","issue":"3","first_page":"261","last_page":"261"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10055","display_name":"Diverse Aspects of Tourism Research","score":0.992900013923645,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10055","display_name":"Diverse Aspects of Tourism Research","score":0.992900013923645,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T14413","display_name":"Advanced Technologies in Various Fields","score":0.9308000206947327,"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/T11490","display_name":"Hydrological Forecasting Using AI","score":0.9254999756813049,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.756422758102417},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7418220043182373},{"id":"https://openalex.org/keywords/mean-absolute-percentage-error","display_name":"Mean absolute percentage error","score":0.6478205919265747},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6143600940704346},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6039831638336182},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5655410289764404},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.5510469675064087},{"id":"https://openalex.org/keywords/correlation-coefficient","display_name":"Correlation coefficient","score":0.4648861587047577},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4350753128528595},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.4326440691947937},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4193156361579895},{"id":"https://openalex.org/keywords/pearson-product-moment-correlation-coefficient","display_name":"Pearson product-moment correlation coefficient","score":0.41690096259117126},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.24198183417320251},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.16234317421913147},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15371695160865784}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.756422758102417},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7418220043182373},{"id":"https://openalex.org/C150217764","wikidata":"https://www.wikidata.org/wiki/Q6803607","display_name":"Mean absolute percentage error","level":3,"score":0.6478205919265747},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6143600940704346},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6039831638336182},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5655410289764404},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.5510469675064087},{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.4648861587047577},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4350753128528595},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.4326440691947937},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4193156361579895},{"id":"https://openalex.org/C55078378","wikidata":"https://www.wikidata.org/wiki/Q1136628","display_name":"Pearson product-moment correlation coefficient","level":2,"score":0.41690096259117126},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.24198183417320251},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.16234317421913147},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15371695160865784},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/e22030261","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e22030261","pdf_url":"https://www.mdpi.com/1099-4300/22/3/261/pdf?version=1584026583","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},{"id":"pmid:33286035","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33286035","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:f11ce96982bc42d29ca17eaef38bcb87","is_oa":true,"landing_page_url":"https://doaj.org/article/f11ce96982bc42d29ca17eaef38bcb87","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":"Entropy, Vol 22, Iss 3, p 261 (2020)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1099-4300/22/3/261/","is_oa":true,"landing_page_url":"http://dx.doi.org/10.3390/e22030261","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:7838789","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/7838789","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/e22030261","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e22030261","pdf_url":"https://www.mdpi.com/1099-4300/22/3/261/pdf?version=1584026583","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1656221728","display_name":null,"funder_award_id":"PA2019GDQT0005","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G4475484651","display_name":"\u57fa\u4e8e\u5065\u5eb7\u5927\u6570\u636e\u7684\u8001\u5e74\u6162\u6027\u75c5\u77e5\u8bc6\u7ec4\u7ec7\u4e0e\u670d\u52a1\u673a\u5236\u7814\u7a76","funder_award_id":"71771077","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5853817622","display_name":null,"funder_award_id":"71601061","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G7192888233","display_name":"\u57fa\u4e8e\u4e91\u7684\u7ba1\u7406\u4fe1\u606f\u7cfb\u7edf\u518d\u9020\u7814\u7a76","funder_award_id":"71331002","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8630666544","display_name":null,"funder_award_id":"71771075","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G8655057573","display_name":"\u533b\u517b\u7ed3\u5408\u7684\u5065\u5eb7\u517b\u8001\u4fe1\u606f\u878d\u5408\u65b9\u6cd5\u4e0e\u4e91\u670d\u52a1\u6a21\u5f0f\u7814\u7a76","funder_award_id":"71771075","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G870014894","display_name":"\u667a\u6167\u65c5\u6e38\u73af\u5883\u4e0b\u57fa\u4e8e\u6e38\u5ba2\u504f\u597d\u7684\u65c5\u6e38\u4e91\u670d\u52a1\u7ec4\u5408\u4e0e\u63a8\u8350\u65b9\u6cd5\u7814\u7a76","funder_award_id":"71601061","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8759453252","display_name":null,"funder_award_id":"71771077","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G8859246467","display_name":null,"funder_award_id":"71331002","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3008197164.pdf","grobid_xml":"https://content.openalex.org/works/W3008197164.grobid-xml"},"referenced_works_count":36,"referenced_works":["https://openalex.org/W55902810","https://openalex.org/W1492417045","https://openalex.org/W1495593618","https://openalex.org/W1659842140","https://openalex.org/W1836465849","https://openalex.org/W1975788771","https://openalex.org/W1975961566","https://openalex.org/W1980799352","https://openalex.org/W1995875735","https://openalex.org/W2025391890","https://openalex.org/W2028702910","https://openalex.org/W2064675550","https://openalex.org/W2086691529","https://openalex.org/W2097227860","https://openalex.org/W2100653381","https://openalex.org/W2112796928","https://openalex.org/W2162042839","https://openalex.org/W2359672971","https://openalex.org/W2500086770","https://openalex.org/W2624413595","https://openalex.org/W2764769393","https://openalex.org/W2796813311","https://openalex.org/W2812669263","https://openalex.org/W2883305384","https://openalex.org/W2884741544","https://openalex.org/W2941376798","https://openalex.org/W2942954122","https://openalex.org/W2944681516","https://openalex.org/W2948490758","https://openalex.org/W2952174833","https://openalex.org/W2981092945","https://openalex.org/W2996089041","https://openalex.org/W3000218158","https://openalex.org/W4245071566","https://openalex.org/W6739879593","https://openalex.org/W7054991787"],"related_works":["https://openalex.org/W4318676890","https://openalex.org/W2039947585","https://openalex.org/W4385195237","https://openalex.org/W3178576217","https://openalex.org/W4285102093","https://openalex.org/W4210644201","https://openalex.org/W3111532652","https://openalex.org/W2510451507","https://openalex.org/W4283367183","https://openalex.org/W4381189085"],"abstract_inverted_index":{"Accurate":[0],"tourist":[1,39,47],"flow":[2,40,48],"prediction":[3,56],"is":[4,76,121,135,145,171,191],"key":[5],"to":[6,123],"ensuring":[7],"the":[8,22,25,33,104,126,131,178,198],"normal":[9],"operation":[10],"of":[11,24,32,37,128,143,162,200],"popular":[12],"scenic":[13],"spots.":[14],"However,":[15],"one":[16],"single":[17],"model":[18,170,190],"cannot":[19],"effectively":[20],"grasp":[21],"characteristics":[23,36],"data":[26,86],"and":[27,65,70,84,137,160,177],"make":[28],"accurate":[29],"predictions":[30],"because":[31],"strong":[34],"nonlinear":[35],"daily":[38,46],"data.":[41],"Accordingly,":[42],"this":[43],"study":[44],"predicts":[45],"in":[49,53,114,130],"Huangshan":[50],"Scenic":[51],"Spot":[52],"China.":[54],"A":[55],"method":[57],"(GA-CNN-LSTM)":[58],"which":[59],"combines":[60],"convolutional":[61,99],"neural":[62,100,181],"network":[63,68,79,101,112,182],"(CNN)":[64],"long-short-term":[66,110],"memory":[67,111],"(LSTM)":[69,113],"optimized":[71],"by":[72,98],"genetic":[73],"algorithm":[74],"(GA)":[75],"established.":[77],"First,":[78],"search":[80],"data,":[81,83],"meteorological":[82],"other":[85],"are":[87,96,107],"constructed":[88],"into":[89,109],"continuous":[90],"feature":[91,94,105],"maps.":[92],"Then,":[93],"vectors":[95,106],"extracted":[97],"(CNN).":[102],"Finally,":[103],"input":[108],"time":[115],"series":[116],"for":[117],"prediction.":[118,140],"Moreover,":[119],"GA":[120],"used":[122],"scientifically":[124],"select":[125],"number":[127],"neurons":[129],"CNN-LSTM":[132,196],"model.":[133],"Data":[134],"preprocessed":[136],"normalized":[138],"before":[139],"The":[141,184],"accuracy":[142],"GA-CNN-LSTM":[144,169,189],"evaluated":[146],"using":[147],"mean":[148,153],"absolute":[149,154],"percentage":[150],"error":[151,155],"(MAPE),":[152],"(MAE),":[156],"Pearson":[157],"correlation":[158],"coefficient":[159],"index":[161],"agreement":[163],"(IA).":[164],"For":[165],"a":[166],"fair":[167],"comparison,":[168],"compared":[172],"with":[173],"CNN-LSTM,":[174],"LSTM,":[175],"CNN":[176],"back":[179],"propagation":[180],"(BP).":[183],"experimental":[185],"results":[186],"show":[187],"that":[188],"approximately":[192],"8.22%":[193],"higher":[194],"than":[195],"on":[197],"performance":[199],"MAPE.":[201]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":16},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}