Ahn, J. J., Byun, H. B., Oh, K. Y., & Kim, Y. K. (2012). Using ridge regression with genetic algorithm to enhance real estate appraisal forecasting. Expert Systems with Applications, 39, 8369–8379. https://doi.org/10.1016/j.eswa.2012.01.18310.1016/j.eswa.2012.01.183
Antipov, E. A., & Pokryshevskaya, E. B. (2012). Mass appraisal of residential apartments: An application of random forest for valuation and a cart-based approach for model diagnostics. Expert Systems with Applications, 39(2), 1772–1778. https://doi.org/10.1016/j.eswa.2011.08.07710.1016/j.eswa.2011.08.077
Appraisal Institute. (1996). The appraisal of real estate. Appraisal Institute.
[+]
Ahn, J. J., Byun, H. B., Oh, K. Y., & Kim, Y. K. (2012). Using ridge regression with genetic algorithm to enhance real estate appraisal forecasting. Expert Systems with Applications, 39, 8369–8379. https://doi.org/10.1016/j.eswa.2012.01.18310.1016/j.eswa.2012.01.183
Antipov, E. A., & Pokryshevskaya, E. B. (2012). Mass appraisal of residential apartments: An application of random forest for valuation and a cart-based approach for model diagnostics. Expert Systems with Applications, 39(2), 1772–1778. https://doi.org/10.1016/j.eswa.2011.08.07710.1016/j.eswa.2011.08.077
Appraisal Institute. (1996). The appraisal of real estate. Appraisal Institute.
Arribas, I., García, F., Guijarro, F., Oliver, J., & Tamosiuniene, R. (2016). Mass appraisal of residential real estate using multilevel modelling. International Journal of Strategic Property Management, 20(1), 77–87. https://doi.org/10.3846/1648715X.2015.113470210.3846/1648715X.2015.1134702
Aznar, J., Ferrís-Oñate, J., & Guijarro, F. (2010). An ANP framework for property pricing combining quantitative and qualitative attributes. The Journal of the Operational Research Society, 61(5), 740–755. https://doi.org/10.1057/jors.2009.3110.1057/jors.2009.31
Aznar, J., & Guijarro, F. (2007). Estimating regression parameters with imprecise input data in an appraisal context. European Journal of Operational Research, 176(3), 1896–1907. https://doi.org/10.1016/j.ejor.2005.10.02910.1016/j.ejor.2005.10.029
Aznar, J., Guijarro, F., & Moreno-Jiménez, J. M. (2011). Mixed valuation methods: A combined AHPGP procedure for individual and group multicriteria agricultural valuation. Annals of Operations Research, 190(1), 221–238. https://doi.org/10.1007/s10479-009-0527-210.1007/s10479-009-0527-2
Baldominos, A., Blanco, I., Moreno, A. J., Iturrarte, R., Bernárdez, Ó., & Afonso, C. (2018). Identifying real estate opportunities using machine learning. Applied Sciences (Basel, Switzerland), 8(11), 2321. https://doi.org/10.3390/app811232110.3390/app8112321
Brown, K., & Uyar, B. (2004). A hierarchical linear model approach for assessing the effects of house and neighborhood characteristics on housing prices. Journal of Real Estate Practice and Education, 7(1), 15–24. https://doi.org/10.1080/10835547.2004.1209160310.1080/10835547.2004.12091603
Cupal, M., Sedlacik, M., & Michalek, J. (2019). The assessment of a building’s insurable value using multivariate statistics: The case of the Czech Republic. Real Estate Management and Valuation, 27(3), 81–96. https://doi.org/10.2478/remav-2019-002710.2478/remav-2019-0027
d’Amato, M. (2002). Appraising property with rough set theory. Journal of Property Investment & Finance, 20(4), 406–418. https://doi.org/10.1108/1463578021043507410.1108/14635780210435074
d’Amato, M. (2004). A comparison between MRA and rough set theory for mass appraisal. A case in Bari. International Journal of Strategic Property Management, 8(4), 205–217. https://doi.org/10.3846/1648715X.2004.963751810.3846/1648715X.2004.9637518
d’Amato, M. (2007). Comparing rough set theory with multiple regression analysis as automated valuation methodologies. International Real Estate Review, 10(2), 42–65.
Dmytrow, K., & Gnat, S. (2019). Application of AHP method in assessment of the influence of attributes on value in the process of real estate valuation. Real Estate Management and Valuation, 27(4), 15–26. https://doi.org/10.2478/remav-2019-003210.2478/remav-2019-0032
Ebru, C., & Eban, A. (2011). Determinants of house prices in Istanbul: A quantile regression approach. Quality & Quantity, 45(2), 305–317. https://doi.org/10.1007/s11135-009-9296-x10.1007/s11135-009-9296-x
Eckert, J. K., Gloudemans, R. J., & Almy, R. R. (1990). Property appraisal and assessment administration. International Association of Assessing Officers.
Fan, G. Z., Ong, S. E., & Koh, H. C. (2006). Determinants of house price: A decision tree approach. Urban Studies (Edinburgh, Scotland), 43(12), 2301–2315. https://doi.org/10.1080/0042098060099092810.1080/00420980600990928
García, N., Gámez, M., & Alfaro, E. (2008). ANN+GIS: An automated system for property valuation. Neurocomputing, 71(4-6), 733–742. https://doi.org/10.1016/j.neucom.2007.07.03110.1016/j.neucom.2007.07.031
Gu, J., Zhu, M., & Jiang, L. (2011). Housing price forecasting based on genetic algorithm and support vector machine. Expert Systems with Applications, 38(4), 3383–3386. https://doi.org/10.1016/j.eswa.2010.08.12310.1016/j.eswa.2010.08.123
Guijarro, F. (2019). Assessing the impact of road traffic externalities on residential price values: A case study in Madrid, Spain. International Journal of Environmental Research and Public Health, 16(24), 5149. https://doi.org/10.3390/ijerph16245149 PMID:3186105510.3390/ijerph16245149
Hausler, J., Ruscheinsky, J., & Lang, M. (2018). News-based sentiment analysis in real estate: A machine learning approach. Journal of Property Research, 35(4), 344–371. https://doi.org/10.1080/09599916.2018.155192310.1080/09599916.2018.1551923
Hu, L., He, S., Han, Z., Xiao, H., Su, S., Weng, M., & Cai, Z. (2019). Monitoring housing rental prices based on social media: An integrated approach of machine-learning algorithms and hedonic modeling to inform equitable housing policies. Land Use Policy, 82, 657–673. https://doi.org/10.1016/j.landusepol.2018.12.03010.1016/j.landusepol.2018.12.030
Guo, J., Xu, S., & Bi, Z. (2013). An integrated cost-based approach for real estate appraisals. Information Technology and Management, 15(2), 131–139. https://doi.org/10.1007/s10799-012-0152-710.1007/s10799-012-0152-7
IAAO. (2003). Standard on automated valuation models (AVMs). International Association of Assessing Officers.
Kane, M. S., Linne, M. R., & Johnson, J. A. (2004). Practical Applications in Appraisal Valuation Modeling: Statistical Methods for Real Estate Practitioners. Appraisal Institute.
Kontrimas, V., & Verikas, A. (2011). The mass appraisal of the real estate by computational intelligence. Applied Soft Computing, 11(1), 443–448. https://doi.org/10.1016/j.asoc.2009.12.00310.1016/j.asoc.2009.12.003
Lins, M. P. E., Novaes, L. F. L., & Legey, L. F. L. (2005). Real estate appraisal: A double perspective data envelopment analysis approach. Annals of Operations Research, 138(1), 79–96. https://doi.org/10.1007/s10479-005-2446-110.1007/s10479-005-2446-1
Liu, F., Liu, D., Malekian, R., Li, Z., & Wang, D. (2017). A measurement model for real estate bubble size based on the panel data analysis: An empirical case study. PLoS One, 12(3), e0173287. https://doi.org/10.1371/journal.pone.0173287 PMID:2827314110.1371/journal.pone.0173287
Liu, L., & Wu, L. (2020). Predicting housing prices in China based on modified Holt’s exponential smoothing incorporating whale optimization algorithm. Socio-Economic Planning Sciences, 72, 100916. Advance online publication. https://doi.org/10.1016/j.seps.2020.10091610.1016/j.seps.2020.100916
Liu, R., & Liu, L. (2019). Predicting housing price in China based on long short-term memory incorporating modified genetic algorithm. Soft Computing, 23(22), 11829–11838. https://doi.org/10.1007/s00500-018-03739-w10.1007/s00500-018-03739-w
Markowitz, H. (1952). Portfolio selection. The Journal of Finance, 7(1), 77–91. https://doi.org/10.1111/j.1540-6261.1952.tb01525.x10.1111/j.1540-6261.1952.tb01525.x
Narula, S. C., Wellington, J. F., & Lewis, S. A. (2012). Valuating residential real estate using parametric programming. European Journal of Operational Research, 217(1), 120–128. https://doi.org/10.1016/j.ejor.2011.08.01410.1016/j.ejor.2011.08.014
Park, B., & Bae, J. K. (2015). Using machine learning algorithms for housing price prediction: The case of Fairfax County, Virginia housing data. Expert Systems with Applications, 42(6), 2928–2934. https://doi.org/10.1016/j.eswa.2014.11.040; https://doi.org/10.1016/j.eswa.2015.03.005
Pérez-Rave, J. I., Correa-Morales, J. C., & González-Echavarría, F. (2019). A machine learning approach to big data regression analysis of real estate prices for inferential and predictive purposes. Journal of Property Research, 36(1), 59–96. https://doi.org/10.1080/09599916.2019.158748910.1080/09599916.2019.1587489
Plakandaras, V., Gupta, R., Gogas, P., & Papadimitriou, T. (2015). Forecasting the US real house price index. Economic Modelling, 45, 259–267. https://doi.org/10.1016/j.econmod.2014.10.05010.1016/j.econmod.2014.10.050
Raslanas, S., Zavadskas, E. K., Kaklauskas, A., & Zabulenas, A. R. (2010). Land value tax in the context of sustainable urban development and assessment. Part II - Analysis of land valuation techniques: The case of Vilnius. International Journal of Strategic Property Management, 14(2), 173–190. https://doi.org/10.3846/ijspm.2010.1310.3846/ijspm.2010.13
Selim, H. (2009). Determinants of house prices in turkey: Hedonic regression versus artificial neural network. Expert Systems with Applications, 36(2), 2843–2852. https://doi.org/10.1016/j.eswa.2008.01.04410.1016/j.eswa.2008.01.044
Valier, A. (2020). Who performs better? AVMs vs hedonic models. Journal of Property Investment & Finance, 38(3), 213–225. https://doi.org/10.1108/JPIF-12-2019-015710.1108/JPIF-12-2019-0157
Wiltshaw, D. (1995). A comment on methodology and valuation. Journal of Property Research, 12(2), 157–161. https://doi.org/10.1080/0959991950872413910.1080/09599919508724139
Wu, C., Ye, X., Ren, F., Wan, Y., Ning, P., & Du, Q. (2016). Spatial and social media data analytics of housing prices in Shenzhen, China. PLoS One, 11(10), e0164553. https://doi.org/10.1371/journal.pone.0164553 PMID:2778364510.1371/journal.pone.0164553
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