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周烨1, 2, 3, 詹宝强4, 杨晓光1, 2
周烨, 詹宝强, 杨晓光. 基于机器学习的土地估值方法[J]. 系统科学与数学, 2023, 43(4): 841-857.
ZHOU Ye, ZHAN Baoqiang, YANG Xiaoguang. Land Value Appraisal Based on Machine Learning[J]. Journal of Systems Science and Mathematical Sciences, 2023, 43(4): 841-857.
ZHOU Ye1, 2, 3, ZHAN Baoqiang4, YANG Xiaoguang1, 2
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[1] 毛中根, 林哲. 土地储备制度与房地产开发——兼论地价与房价的关系. 上海经济研究, 2005, (8):58-63. (Mao Z G, Lin Z. Land reserving system and real estate development-Relation between land price and house price. Shanghai Economic Review, 2005, (8):58-63.) [2] 卢新海, 黄善林, 冯广京. 不动产估价师培养与土地资源管理专业建设. 中国土地科学, 2006, 20(3):55-60. (Lu X H, Huang S L, Feng G J. Training of real estate appraisers and subject construction of land resource management. China Land Science, 2006, 20(3):55-60.) [3] Vandell K D. Optimal comparable selection and weighting in real property valuation. Real Estate Economics, 1991, 19(2):213-239. [4] Lisec A, Ferlan M, Lobnik F, et al. Modelling the rural land transaction procedure. Land Use Policy, 2008, 25(2):286-297. [5] 龙开胜, 李敏. 长三角城市土地稀缺与土地利用效率的交互影响. 中国土地科学, 2018, 32(9):74-80. (Long K S, Li M. The interactive effect between urban land scarcity and land use efficiency in the Yangtze River Delta, China. China Land Science, 2018, 32(9):74-80.) [6] 王雪峰. 垄断, 信息不对称及土地拍卖定价偏好的差异——以南昌市为例. 中国土地科学, 2018, 32(9):43-50. (Wang X F. Monopoly, information asymmetry and price preference difference of land auction in Nanchang city. China Land Science, 2018, 32(9):43-50.) [7] Capozza D R, Israelsen R D, Thomson T A. Appraisal, agency and atypicality:Evidence from manufactured homes. Real Estate Economics, 2005, 33(3):509-537. [8] Gau G W, Lai T Y, Wang K. Optimal comparable selection and weighting in real property valuation:An extension. Real Estate Economics, 1992, 20(1):107-123. [9] Shimizu C, Karato K, Nishimura K. Nonlinearity of housing price structure:Assessment of three approaches to nonlinearity in the previously owned condominium market of Tokyo. International Journal of Housing Markets and Analysis, 2014, 7(4):459-488. [10] 先倚懿, 金升平. 混合效应模型在新建住宅房价指数中的应用. 统计与决策, 2016, (15):87-90. (Xian Y Y, Jin S P. Application of mixed-effects model on new residential house price index. Statistic & Decision, 2006, (15):55-60.) [11] 秦波, 孙亮. 容积率和出让方式对地价的影响——基于特征价格模型. 中国土地科学, 2010, 24(3):70-74. (Qin B, Sun L. The impacts of floor area ratio and transfer modes on land prices:Based on hedonic price model. China Land Science, 2010, 24(3):70-74.) [12] Ahn J J, Byun H W, Oh K J, et al. Using ridge regression with genetic algorithm to enhance real estate appraisal forecasting. Expert Systems with Applications, 2012, 39(9):8369-8379. [13] 申慧敏, 夏赞才, 刘婷, 等. MWTP计量模型研究与应用进展. 统计与决策, 2020, 36(23):37-41. (Shen H M, Xia Z C, Liu T, et al. Research and application advancements of MWTP measurement models. Statistic & Decision, 2020, 36(23):37-41.) [14] Hu S G, Yang S F, Li W D, et al. Spatially non-stationary relationships between urban residential land price and impact factors in Wuhan city, China. Applied Geography, 2016, 68:48-56. [15] You Q Z, Pang R, Cao L L, et al. Image-based appraisal of real estate properties. IEEE Transactions on Multimedia, 2017, 19(12):2751-2759. [16] Afonso B, Melo L, Oliveira W, et al. Housing prices prediction with a deep learning and random forest ensemble. Anais do XVI Encontro Nacional de Inteligbência Artificial e Computacional. SBC, 2019, 389-400. [17] Yuan F, Wei Y D, Xiao W Y. Land marketization, fiscal decentralization, and the dynamics of urban land prices in transitional China. Land Use Policy, 2019, 89:104208. [18] Nichols J B, Oliner S D, Mulhall M R. Swings in commercial and residential land prices in the United States. Journal of Urban Economics, 2013, 73(1):57-76. [19] Bao H X H, Glascock J L, Zhou S Z, et al. Land value determination in an emerging market:Empirical evidence from China. International Journal of Managerial Finance, 2014, 10(2):180- 199. [20] 李志, 周生路, 张红富, 等. 基于GWR模型的南京市住宅地价影响因素及其边际价格作用研究. 中国土地科学, 2009, 23(10):20-25. (Li Z, Zhou S L, Zhang H F, et al. Exploring the factors impacting on the residential land price and measuring their marginal effects based on geographically weighted regression model:A case study of Nanjing. China Land Science, 2009, 23(10):20-25.) [21] Cai H B, Henderson J V, Zhang Q H. China's land market auctions:Evidence of corruption?. The Rand Journal of Economics, 2013, 44(3):488-521. [22] Qin Y, Zhu H J, Zhu R. Changes in the distribution of land prices in urban China during 2007- 2012. Regional Science and Urban Economics, 2016, 57:77-90. [23] Cheshire P, Sheppard S. On the price of land and the value of amenities. Economica, 1995, 62:247-267. [24] Chen Z C, Hu Y M, Zhang C J. An optimal rubrics-based approach to real estate appraisal. Sustainability, 2017, 9(6):909-927. [25] Ferlan N, Bastic M, Psunder I. Influential factors on the market value of residential properties. Engineering Economics, 2017, 28(2):135-144. [26] 沈昊婧, 冯长春, 侯懿珊. 城市间土地价格及影响因素的空间差异研究. 城市发展研究, 2014, 21(3):J0004-J0008. (Shen H J, Feng C C, Hou Y S. The study of spatial characteristics of urban land price and its influencing factors. Urban Development Research, 2014, 21(3):J0004-J0008.) [27] Cockx K, Canters F. Incorporating spatial non-stationarity to improve dasymetric mapping of population. Applied Geography, 2015, 63:220-230. [28] Du J, Peiser R B. Land supply, pricing and local governments' land hoarding in China. Regional Science and Urban Economics, 2014, 48:180-189. [29] Huang Z H, Du X J. Strategic interaction in local governments' industrial land supply:Evidence from China. Urban Studies, 2017, 54(6):1328-1346. [30] 张帅, 秦梦, 张少萍. 中国金融稳定性与土地价格动态关系研究. 金融发展研究, 2020, (8):20-27. (Zhang S, Qin M, Zhang S P. The dynamic relationship between financial stability and land price in China. Financial Development Research, 2020, (8):20-27.) [31] Feldstein M. Inflation, tax rules, and the prices of land and gold. Journal of Public Economics, 1980, 14(3):309-317. [32] 王伟, 谷伟哲, 翟俊, 等. 城市轨道交通对土地资源空间价值影响. 城市发展研究, 2014, 21(6):117-124. (Wang W, Gu W Z, Zhai J, et al. A study on the influence of rail transit on the spatial value of nearby land resources based on hedonic model. Urban Development Research, 2014, 21(6):117-124.) [33] Melkumova L E, Shatskikh S Y. Comparing ridge and LASSO estimators for data analysis. Procedia Engineering, 2017, 201:746-755. [34] Friedman J H. Greedy function approximation:A gradient boosting machine. Annals of Statistics, 2001, 29(5):1189-1232. [35] Chen T, Guestrin C. Xgboost:A scalable tree boosting system. Proceedings of the 22nd ACM Sigkdd International Conference on Knowledge Discovery and Data Mining, 2016, 785-794. [36] Ke G L, Meng Q, Finley T, et al. Lightgbm:A highly efficient gradient boosting decision tree. Advances in Neural Information Processing Systems, 2017, 30:3149-3157. [37] Prokhorenkova L, Gusev G, Vorobev A, et al. CatBoost:Unbiased boosting with categorical features. Advances in Neural Information Processing Systems, 2018, 31:6639-6649. |
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