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Neural Networks Modelling of Municipal Real Estate Market Rent Rates

机译:市政房地产市场租金率的神经网络建模

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This paper presents the results of research on the application of neural networks modelling of municipal real estate market rent rates. The test procedure was based on selected networks trained on the local real estate market data and transformation of the detected dependencies – through established models – to estimate the potential market rent rates of municipal premises. On this basis, the assessment of the adequacy of the actual market rent rates of municipal properties was made. Empirical research was conducted on the local real estate market of the city of Olsztyn in Poland. In order to describe the phenomenon of market rent rates formation an unidirectional three-layer network and a network of radial base was selected. Analyses showed a relatively low degree of convergence of the actual municipal rent rents with potential market rent rates. This degree was strongly varied depending on the type of business ran on the property and its’ social and economic impact. The applied research methodology and the obtained results can be used in order to rationalize municipal property management, including the activation of rental policy.
机译:本文介绍了神经网络模型在市政房地产市场租金率中的应用研究结果。该测试程序基于对本地房地产市场数据进行了训练的选定网络,并通过已建立的模型对检测到的依赖关系进行了转换,以估算市政房屋的潜在市场租金。在此基础上,对市政物业的实际市场租金率进行了评估。对波兰奥尔什丁市的当地房地产市场进行了实证研究。为了描述市场租金形成的现象,选择了单向三层网络和径向基网络。分析表明,实际的市政租金与潜在的市场租金率的相对较低的融合程度。这个程度的差异很大,具体取决于经营该房地产的业务类型及其对社会和经济的影响。应用的研究方法和获得的结果可用于合理化市政物业管理,包括激活租赁政策。

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