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      近年来，房地产行业飞速发展，房价市场也在不断改变。希望进一步促进我国房地产市场的发展，中国对房产税税收作出了大量调整，并积极推进了房产税改革。党的十九届五中全会报告指出，要完善现在税收制度，完善地方税、直接税的体制。中央政府将积极稳妥推动房产税立法与改革。可见，征收房产税的大趋势所在。而未来征收房产税的征收过程中，由于可能存在因买卖“阴阳合同”而产生的巨大税务风险，通过对住宅的计税价格评估，将能够为房产税税基评估工作提供理论、技术支撑，进而促进房地产行业的健康发展，并保障我国财政收入的平稳进行。因此，本文探索兰州市房产税税基价格的评估方法，评估出兰州市房产税税基价格，希望能为房产税税基评估提供理论依据，同时为税基评估、房地产评估提供价值参考。
       本文重点介绍了房产税、税基评估、批量评估、税基评估理论、随机森林模型、随机森林优化方法的有关概念和理论基础，并根据国内外部分国家和地区对房产税税基批量评估的实际经验，探讨了随机森林模型在税基批量评估中的适用性分析，以及兰州市房产税税基评估应用优化随机森林模型的可行性分析。接着以特征价格理论、地租论、区位理论为理论基础,并借鉴了以前学术界关于影响房地产价值特征变量的研究成果,在此基础上建立了税基估价指标体系,并对22个指标进行量化,最后建立了随机森林模型、优化随机森林模型、多元回归模型，利用670套住宅类房屋样本，对三个模型进行检验，利用最佳模型预测房屋市场价值，并计算出兰州市住宅类房产税税基。案例结果表明：①优化随机森林模型可应用于兰州市房产税税基评估中。②turnRF()函数能有效提高随机森林模型的预测准确性。③预测结果1.327万元/平方米可用于最近年度兰州市征收房产税的计税依据。基于此，可以考虑将评估出的均价和优化随机森林模型纳入到房产税征收与评估体系中。

    In recent years, the real estate industry has developed rapidly, and the housing market is constantly changing. Hoping to further promote the development of my country's real estate market, China has made a lot of adjustments to the property tax and actively promoted the reform of the property tax. The report of the Fifth Plenary Session of the 19th Central Committee of the Communist Party of China pointed out that it is necessary to improve the current tax system, and improve the system of local tax and direct tax. The central government will actively and steadily promote the legislation and reform of property tax. It can be seen that the general trend of property tax collection lies. In the process of collecting property tax in the future, since there may be huge tax risks arising from buying and selling "yin and yang contracts", the assessment of the taxable price of residences will be able to provide theoretical and technical support for the assessment of the tax base of property tax. In order to promote the healthy development of the real estate industry, and ensure the smooth progress of my country's fiscal revenue. Therefore, this paper explores the evaluation method of the real estate tax base price in Lanzhou, and evaluates the real estate tax base price in Lanzhou, hoping to provide a theoretical basis for the real estate tax base assessment, and at the same time provide a value reference for the tax base evaluation and real estate evaluation.
    This paper focuses on the related concepts and theoretical basis of property tax, tax base assessment, batch assessment, tax base assessment theory, random forest model, and random forest optimization method. Practical experience, discusses the applicability analysis of random forest model in batch assessment of tax base, and the feasibility analysis of the application of optimization random forest model in Lanzhou property tax base assessment. Then, based on hedonic price theory, land rent theory, and location theory, and drawing on previous academic research results on characteristic variables affecting real estate value, a tax-based valuation index system was established, and22indicators were quantified. , Finally, a random forest model, an optimized random forest model, and a multiple regression model were established. 670 residential housing samples were used to test the three models. The best model was used to predict the housing market value, and the residential property tax in Lanzhou City was calculated. tax base. The case results show that: ①The optimized random forest model can be applied to the assessment of the property tax base in Lanzhou. ②The turnRF() function can effectively improve the prediction accuracy of the random forest model. ③The forecast result of 13,270 RMB/square meter can be used as the tax basis for the property tax levied by Lanzhou in the recent year. Based on this, it can be considered to incorporate the estimated average price and the optimized random forest model into the property tax collection and evaluation system.