{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T03:52:42Z","timestamp":1783050762314,"version":"3.54.6"},"reference-count":32,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2020,8,10]],"date-time":"2020-08-10T00:00:00Z","timestamp":1597017600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the General Program of National Natural Science Foundation of China","award":["61603057"],"award-info":[{"award-number":["61603057"]}]},{"name":"the Natural Science Basic Research Plan in Shaanxi Province of China","award":["2020JM-255"],"award-info":[{"award-number":["2020JM-255"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>Based on the symmetrical public transportation network data of Xi\u2019an, China obtained by geographic information system (GIS) technology in 2019, three urban public transportation indexes of walking accessibility, bus accessibility, and metro accessibility were established, and a real estate price prediction model was built by using several machine learning algorithms to predict and analysis the housing price in Xi\u2019an, China. Firstly, the symmetrical road network data and real estate property data of Xi\u2019an were collected and preprocessed, secondly, the spatial syntax theory and distance calculation method were applied to establish three indexes of traffic accessibility; finally, taking the house property data and the calculated traffic accessibility indexes as the characteristic index, the real estate price prediction model of Xi\u2019an was constructed by using the random forest algorithm (RF), lightweight gradient lift algorithm (LGBM), and gradient lifting regression tree algorithm (GBDT). The prediction accuracy of the final model is 89.2% and the root-mean-square error is 1761.84. The results show that the accessibility of bus and metro to some extent represent the convenience of public transportation in different areas of urban space. The higher the accessibility index is, the more convenient the traffic is. The real estate price model has high prediction accuracy and can reflect the real situation of urban real estate price. The importance of the three accessibility features to the real estate price prediction model are nearly more than 20%, which indicates that the accessibility of urban public transportation has an important impact on the change of urban real estate price, and the development of urban public transportation plays an important role in the real estate economy.<\/jats:p>","DOI":"10.3390\/sym12081329","type":"journal-article","created":{"date-parts":[[2020,8,10]],"date-time":"2020-08-10T07:25:03Z","timestamp":1597044303000},"page":"1329","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Research on Accurate House Price Analysis by Using GIS Technology and Transport Accessibility: A Case Study of Xi\u2019an, China"],"prefix":"10.3390","volume":"12","author":[{"given":"Chao","family":"Xue","sequence":"first","affiliation":[{"name":"School of Electronic and Control Engineering, Chang\u2019an University, Xi\u2019an 710064, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yongfeng","family":"Ju","sequence":"additional","affiliation":[{"name":"School of Electronic and Control Engineering, Chang\u2019an University, Xi\u2019an 710064, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuguang","family":"Li","sequence":"additional","affiliation":[{"name":"School of Electronic and Control Engineering, Chang\u2019an University, Xi\u2019an 710064, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qilong","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Electronic and Control Engineering, Chang\u2019an University, Xi\u2019an 710064, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qingqing","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Periodical Offices, Chang\u2019an University, Xi\u2019an 710064, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,8,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1080\/0042098042000309720","article-title":"The effects of expected transport improvements on housing prices","volume":"42","author":"Yiuc","year":"2005","journal-title":"Urban Stud."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/j.trb.2014.02.007","article-title":"A Spatial Difference-in-differences estimator to evaluate the effect of change in public mass transit systems on house prices","volume":"64","author":"Dube","year":"2014","journal-title":"Transp. Res. Part B"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"379","DOI":"10.1007\/s11116-015-9580-7","article-title":"The effects of highway development on housing prices","volume":"43","author":"Levkovich","year":"2015","journal-title":"Transportation"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"2553","DOI":"10.1177\/0042098012474510","article-title":"Where do home buyers pay most for relative transit accessibility? Hong Kong, Taipei and Kaohsiung Compared","volume":"50","author":"Shyr","year":"2013","journal-title":"Urban. Stud."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1016\/j.tra.2016.05.002","article-title":"The value of transportation accessibility in a least developed country city\u2014The case of Rajshahi City, Bangladesh","volume":"89","author":"Mitra","year":"2016","journal-title":"Transp. Res. Part A Policy Pract."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1007\/BF01944043","article-title":"A reformulation of classical location theory and its relation to rent theory","volume":"19","author":"Alonso","year":"1967","journal-title":"Pap. Reg. Sci. Assoc."},{"key":"ref_7","first-page":"73","article-title":"How Accessibility shapes land use","volume":"25","author":"Hansen","year":"1959","journal-title":"J. Am. Plan. Assoc."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1016\/S1005-8885(07)60138-1","article-title":"Study on the share ratio between a service provider and two carriers","volume":"14","author":"Yue","year":"2007","journal-title":"J. China Univ. Posts Telecommun."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"66","DOI":"10.3141\/1994-09","article-title":"Effects of transportation accessibility on residential property values","volume":"1994","author":"Shin","year":"2007","journal-title":"Transp. Res. Rec. J. Transp. Res. Board"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1016\/j.retrec.2012.06.039","article-title":"The impacts of mass transit on land development in China: The case of Beijing","volume":"40","author":"Zhang","year":"2013","journal-title":"Res. Transp. Econ."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"36","DOI":"10.3141\/2452-05","article-title":"Impact of bus rapid transit and metro rail on property values in Guangzhou, China","volume":"2452","author":"Salon","year":"2014","journal-title":"Transp. Res. Rec. J. Transp. Res. Board"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1291","DOI":"10.1007\/s11116-017-9834-7","article-title":"The impact of metro services on housing prices: A case study from Beijing","volume":"46","author":"Li","year":"2017","journal-title":"Transportation"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"185","DOI":"10.2307\/1230278","article-title":"Quality Factors influencing vegetable prices J","volume":"10","author":"Waugh","year":"1928","journal-title":"Farm Econ."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"132","DOI":"10.1086\/259131","article-title":"A new approach to consumer theory","volume":"74","author":"Lancaster","year":"1966","journal-title":"J. Political Econ."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1086\/260169","article-title":"Hedonic Prices and implicit markets: Product differentiation in pure competition","volume":"82","author":"Rosen","year":"1974","journal-title":"J. Political Econ."},{"key":"ref_16","first-page":"115","article-title":"A Research of Benchmark Town Land Price Based on the Hedonic Price Model","volume":"23","author":"Xinru","year":"2005","journal-title":"Syst. Eng."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"344","DOI":"10.1016\/S1007-0214(05)70079-1","article-title":"Influence of spatial features on land and housing prices","volume":"10","author":"Gao","year":"2005","journal-title":"Tsinghua Sci. Technol."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Durganjali, P., and Pujitha, M.V. (2019, January 14\u201315). House Resale Price Prediction Using Classification Algorithms. Proceedings of the 6th IEEE International Conference on Smart Structures and Systems, ICSSS 2019, Chennai, India.","DOI":"10.1109\/ICSSS.2019.8882842"},{"key":"ref_19","first-page":"81","article-title":"Real estate price prediction based on web search data","volume":"31","author":"Qian","year":"2014","journal-title":"Stat. Res."},{"key":"ref_20","first-page":"191","article-title":"Housing price prediction model based on integrated learning","volume":"13","author":"Bowen","year":"2017","journal-title":"Comput. Knowl. Technol."},{"key":"ref_21","unstructured":"Ke, G., Meng, Q., and Finley, T.W. (2017, January 4\u20139). LightGBM: A highly efficient gradient boosting decision tree. Proceedings of the Neural Information Processing Systems Annual Conference, Long Beach, CA, USA."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Li, C., Chen, Z., Liu, J., Gao, X., Di, F., Li, L., and Ji, X. (2020, July 01). Power Load Forecasting Based on the Combined Model of LSTM and XGBoost. Available online: https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3357777.3357792.","DOI":"10.1145\/3357777.3357792"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Banerjee, D., and Dutta, S. (2017, January 21\u201322). Predicting the housing price direction using machine learning techniques. Proceedings of the 2017 IEEE International Conference on Power, Control, Signals and Instrumentation Engineering, Chennai, India.","DOI":"10.1109\/ICPCSI.2017.8392275"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Vineeth, N., Ayyappa, M., and Bharathi, B. (2018). House price prediction using machine learning algorithms. Commun. Comput. Inf. Sci., 423\u2013433.","DOI":"10.1007\/978-981-13-1936-5_45"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Phan, T.D. (2018, January 3\u20137). Housing price prediction using machine learning algorithms: The case of Melbourne city, Australia. Proceedings of the International Conference on Machine Learning and Data Engineering, Sydney, Australia.","DOI":"10.1109\/iCMLDE.2018.00017"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"821","DOI":"10.1016\/S1574-0080(87)80006-8","article-title":"Chapter 20 The structure of urban equilibria: A unified treatment of the muth-mills model","volume":"2","author":"Brueckner","year":"1987","journal-title":"Handb. Reg. Urban Econ."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1080\/10835547.1991.12090645","article-title":"The Effect of school desegregation decisions on single-family housing prices","volume":"6","author":"Evans","year":"1991","journal-title":"J. Real Estate Res."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1002\/9780470690680.ch5","article-title":"Hedonic Pricing Models: A Selective and Applied Review","volume":"Volume 10","author":"Malpezzi","year":"2002","journal-title":"Housing Economics and Public Policy"},{"key":"ref_29","unstructured":"Diaz, R.B. (1999). Impacts of Rail Transit on Property Values, Booz Allen & Hamilton Inc."},{"key":"ref_30","first-page":"676","article-title":"Evaluation of factors influencing residential land price in Beijing based on structural equation model","volume":"065","author":"Wenjie","year":"2011","journal-title":"Acta Geogr. Sin."},{"key":"ref_31","unstructured":"Zhang, W., and Chen, Y. (2007, January 9\u201313). Analysing commerce traffic accessibility based on GIS. Proceedings of the ITS 14th World Congress on Intelligent Transport Systems, Beijing, China."},{"key":"ref_32","unstructured":"Wardlaw, A.C. (2000). Practical Statistics, John Wiley & Sons Ltd."}],"container-title":["Symmetry"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2073-8994\/12\/8\/1329\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:58:32Z","timestamp":1760176712000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2073-8994\/12\/8\/1329"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,8,10]]},"references-count":32,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2020,8]]}},"alternative-id":["sym12081329"],"URL":"https:\/\/doi.org\/10.3390\/sym12081329","relation":{},"ISSN":["2073-8994"],"issn-type":[{"value":"2073-8994","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,8,10]]}}}