Industrial lot estimation method based on big data and intelligent decision-making mechanism

Abstract

The present invention discloses an industrial lot estimation method based on big data and an intelligent decision-making mechanism. The method comprises the following steps of: the step 1, confirmingfactors influencing land prices; the step 2, performing collection, conversion, quantification and storage of factor data; and the step 3, constructing a model to perform iteration and operation, wherein in the step 1, the factors influencing land prices are confirmed, the factors comprise five classes consisting of an area factor, a traffic factor, a surrounding facility factor, a policy factor and a historical deal condition, in the step 3, the model being configured to perform iteration and operation comprises establishing a feature engineering, establishing a model and employing an XGBoostalgorithm to analyze the land prices. Through combination of the newest big data and an intelligent estimation algorithm to perform estimation of the land prices and obtain a good effect.

Description

technical field [0001] The present invention proposes a method for estimating industrial plots based on big data and an intelligent decision-making mechanism. Background technique [0002] With the continuous development of the socio-economic level and the continuous advancement of urbanization and industrialization, the industrial land transactions in the secondary market have also increased. Valuation has always been a pain point in the industry. [0003] The valuation of industrial plots has the characteristics of "three highs, two highs, and two lows", which are specifically manifested in: many individual factors, various disposal methods, and various development and construction methods; the target amount is high and risk factors are high; the basis for reference There are few materials and few standards for reference. Therefore, the current industrial land value estimation basically relies on manual + some traditional valuation algorithms, roughly as follows: [000...

AI Technical Summary

Problems solved by technology

[0008] 1. Manual errors caused by different personnel in the evaluation process due to different focus, consideration and experience

[0009] 2. It is impossible to quickly, accurately and comprehensively obtain land price influencing factors and market information in a short period of time, and cannot make judgments on real estate price trends in the medium and long term

[0010] 3. According to the requirements of different projects, manual evaluation is carried out each time, which consumes a lot of resources, takes a long time and is inefficient

[0011] 4. Various decision-making information cannot be displayed intuitively digitally, mathematical models are rarely used in calculations, and there are many human interference factors

Nothing to provide comprehensive decision-making basis for decision-makers

[0012] 5. Land valuation algorithms such as cost method, income reduction method, and market comparison method have various defects in the application of land valuation, and the scope of use is limited

[0013] 6. The above algorithms are based on the western land market, and may not be applicable to the actual land market in our country

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