{"id":"https://openalex.org/W3009055137","doi":"https://doi.org/10.1109/icsai48974.2019.9010071","title":"Prediction of House Price Based on The Back Propagation Neural Network in The Keras Deep Learning Framework","display_name":"Prediction of House Price Based on The Back Propagation Neural Network in The Keras Deep Learning Framework","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W3009055137","doi":"https://doi.org/10.1109/icsai48974.2019.9010071","mag":"3009055137"},"language":"en","primary_location":{"id":"doi:10.1109/icsai48974.2019.9010071","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsai48974.2019.9010071","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 6th International Conference on Systems and Informatics (ICSAI)","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/A5063967158","display_name":"Zhongyun Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210154361","display_name":"Shanghai Jian Qiao University","ror":"https://ror.org/04xdqtw10","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210154361"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongyun Jiang","raw_affiliation_strings":["Information Technology Institute, Shanghai Jian Qiao University, SHANGHAI, P.R. CHINA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information Technology Institute, Shanghai Jian Qiao University, SHANGHAI, P.R. CHINA","institution_ids":["https://openalex.org/I4210154361"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012191010","display_name":"Guoxin Shen","orcid":"https://orcid.org/0000-0002-8919-6235"},"institutions":[{"id":"https://openalex.org/I44675526","display_name":"Shanghai Ocean University","ror":"https://ror.org/04n40zv07","country_code":"CN","type":"education","lineage":["https://openalex.org/I44675526"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoxin Shen","raw_affiliation_strings":["Information Institute, Shanghai Ocean University, SHANGHAI, P.R. CHINA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Information Institute, Shanghai Ocean University, SHANGHAI, P.R. CHINA","institution_ids":["https://openalex.org/I44675526"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":9.1595,"has_fulltext":false,"cited_by_count":47,"citation_normalized_percentile":{"value":0.98995929,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1408","last_page":"1412"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9426000118255615,"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"}},"topics":[{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.9426000118255615,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.692437469959259},{"id":"https://openalex.org/keywords/parsing","display_name":"Parsing","score":0.6707234978675842},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6221457123756409},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.599574863910675},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.5787002444267273},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.5043307542800903},{"id":"https://openalex.org/keywords/feed-forward","display_name":"Feed forward","score":0.5030578970909119},{"id":"https://openalex.org/keywords/feedforward-neural-network","display_name":"Feedforward neural network","score":0.4993884563446045},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4945177733898163},{"id":"https://openalex.org/keywords/approximation-error","display_name":"Approximation error","score":0.4714672863483429},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43439286947250366},{"id":"https://openalex.org/keywords/value-network","display_name":"Value network","score":0.422426700592041},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3436075448989868},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.26254650950431824},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1521831452846527}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.692437469959259},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.6707234978675842},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6221457123756409},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.599574863910675},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.5787002444267273},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.5043307542800903},{"id":"https://openalex.org/C38858127","wikidata":"https://www.wikidata.org/wiki/Q5441228","display_name":"Feed forward","level":2,"score":0.5030578970909119},{"id":"https://openalex.org/C47702885","wikidata":"https://www.wikidata.org/wiki/Q5441227","display_name":"Feedforward neural network","level":3,"score":0.4993884563446045},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4945177733898163},{"id":"https://openalex.org/C122383733","wikidata":"https://www.wikidata.org/wiki/Q865920","display_name":"Approximation error","level":2,"score":0.4714672863483429},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43439286947250366},{"id":"https://openalex.org/C89249532","wikidata":"https://www.wikidata.org/wiki/Q7912758","display_name":"Value network","level":3,"score":0.422426700592041},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3436075448989868},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.26254650950431824},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1521831452846527},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C4216890","wikidata":"https://www.wikidata.org/wiki/Q815823","display_name":"Business model","level":2,"score":0.0},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icsai48974.2019.9010071","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsai48974.2019.9010071","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 6th International Conference on Systems and Informatics (ICSAI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6100000143051147,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W2323929895","https://openalex.org/W2775541474","https://openalex.org/W2782769512","https://openalex.org/W2913380182","https://openalex.org/W2954790191","https://openalex.org/W2955497261"],"related_works":["https://openalex.org/W2115072676","https://openalex.org/W97768505","https://openalex.org/W4311212821","https://openalex.org/W2918103456","https://openalex.org/W1529660427","https://openalex.org/W2102065768","https://openalex.org/W2080531293","https://openalex.org/W2540883726","https://openalex.org/W4390752998","https://openalex.org/W3005666459"],"abstract_inverted_index":{"This":[0],"paper":[1,22],"uses":[2],"the":[3,7,13,24,29,34,40,60,72,80,85,92,96,100,112],"housing":[4,17],"data":[5,69],"of":[6,15,91],"chain":[8],"home":[9],"network":[10,48],"to":[11,27,66,70],"predict":[12,71],"price":[14,114],"second-hand":[16],"in":[18,111],"Shanghai.":[19],"Firstly,":[20],"this":[21],"use":[23],"crawler":[25],"technology":[26],"parse":[28],"URL":[30],"text":[31],"information":[32],"through":[33],"j":[35],"son":[36],"request":[37],"address":[38],"and":[39,99],"BeautifulSoup":[41],"parser.":[42],"Then":[43],"a":[44,108],"multi-layer":[45],"feedforward":[46],"neural":[47],"model":[49,81,106],"trained":[50],"by":[51],"error":[52,94],"inverse":[53],"propagation":[54],"algorithm":[55],"is":[56,103],"established":[57],"based":[58],"on":[59],"deep":[61],"learning":[62],"library":[63],"Keras.":[64],"Finally,":[65],"enter":[67],"standardized":[68],"price.":[73],"The":[74,105],"experimental":[75],"results":[76],"show":[77],"that":[78],"for":[79],"with":[82,87],"Gaussian":[83],"noise,":[84],"sample":[86],"an":[88],"absolute":[89],"value":[90,98,102],"relative":[93],"between":[95],"predicted":[97],"actual":[101],"95.59%.":[104],"has":[107],"good":[109],"effect":[110],"house":[113],"forecast.":[115]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":12},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":7}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
