Research On Real Estate Valuation Of Tourist Residences Based On KNN Algorithm And Hedonic Model

With the booming development of Chinese economy,various industries have made great progress,and people’s material life and income level have been steadily improved,more and more residents invest their spare funds in the real estate industry;meanwhile,the popularity of tourist scenic spots has been expanding,and the further development and utilization of tourism resources have promoted the integration of real estate industry and tourism.The two industries support each other,coordinate and advance to achieve a higher level of development,"tourism + real estate" mode of tourism real estate came into being.Among the various types of tourism real estate products that have sprung up,tourism residential real estate is the most representative product,which meets the long-term vacation needs of residents and realizes the effective combination of tourism landscape resources and residential real estate.As the consumer demand for tourism residential real estate rises gradually,the impact of tourism residential real estate on regional economy and consumers becomes more and more obvious,and it is urgent to conduct an in-depth study on the valuation of tourism residential real estate.In this paper,the KNN algorithm and the characteristic price model are used as the evaluation methods for tourism residential real estate.Firstly,by analyzing the current situation of domestic and foreign research,we gain an in-depth understanding of the relevant concepts and evaluation parameters of tourism residential real estate,KNN algorithm and characteristic price model,and on the basis of analyzing the characteristics of tourism residential real estate evaluation,we explain the limitations of the existing common evaluation methods for tourism residential real estate value evaluation.Secondly,this paper takes Mount Emei Tourism Scenic Area as an empirical case and introduces the KNN classification identification algorithm based on quantifying 4485 residential real estate data of the city where Mount Emei Tourism Scenic Area is located,and classifies and identifies them by two parameters,and more accurately screens out 1258 real estate sample data that meet the definition of tourism residential real estate.Finally,based on the screened tourist residential real estate sample data,this paper conducted a parametric regression in the form of linear logarithmic function using SPSS software,and validated the relevant estimation and testing of the model while establishing the characteristic price model,and verified the feasibility and advancement of the characteristic price evaluation model index system established in this paper by means of comparative analysis of case evaluation results.The study shows that the nine characteristic variables,namely area,building type,located floor interval,housing age,decoration condition,floor area ratio,greening rate,supporting facilities,and landscape view,can significantly affect the price of tourist residential real estate around the tourist scenic area of Mount Emei,and these nine characteristic variables can pass the relevant statistical and econometric tests,which are in line with the model settings and meet the research objectives of the paper.