Real estate value estimation method based on artificial neural network statistic model
An artificial neural network and statistical model technology, applied in the field of real estate valuation, can solve problems such as non-standard valuation results, unscientific valuation models, and inconsistent valuation standards
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[0016] 1. Design the composition of the artificial neural network model for house price valuation, including the input layer, output layer, middle layer, and the determination of the number of nodes in the middle layer.
[0017] 2. The input layer is the average transaction price of real estate and various factors that affect housing prices, including basic factors and adjustment factors. Basic factors are the basic determinants of property prices, including: land acquisition costs, preliminary engineering costs, supporting costs, construction and installation costs, management costs, sales costs, taxes, interest and profits, etc. For second-hand real estate, these factors reflect the value when the property was built, and have extremely limited reference value for the current market price, so we can use the current market price of the property or the market price of similar properties as a parameter. Adjustment factors are environmental adjustment factors for property prices,...
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