A Radial Basis Function-Generated Finite Difference Method to Evaluate Real Estate Index Options

He, Xubiao; Gong, Pan

doi:10.1007/s10614-019-09924-9

Cited by 4 publications

(2 citation statements)

References 47 publications

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“…He et al designed and described a method of generating finite difference (rbf-fd) based on multi quadratic radial basis function of local RBF format. The results show that rbf-fd method is effective and stable in terms of pre-real estate valuation accuracy [10]. Sabina et al applied fuzzy logic theory to estimate the land value of agricultural land market.…”

Section: Related Workmentioning

confidence: 99%

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Modeling and Simulation of Real Estate Valuation Based on Genetic Neural Network Model

Shen

2022

Journal of Function Spaces

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China’s real estate market is developing rapidly, but the house price is abnormal. The nonlinear relationship between housing characteristics and real estate value is difficult to calculate, resulting in the difficulty of house price prediction. Based on this, the relationship model between characteristic variables and house prices is constructed by using the machine learning method. At the same time, genetic algorithm is used to screen the specific values. The experimental results show that the optimized model converges in 56 iterations; in the application test, the research model found that in 90% of the test samples, the error between the predicted value and the actual measured value shall not exceed 10%. Experiments show that the genetic algorithm is effective in optimizing the BP house price valuation model and improves the calculation efficiency and valuation accuracy of the valuation model.

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Section: Related Workmentioning

confidence: 99%

“…The selection operation is repeated until the size of the population reaches the specified size. The mathematical model is shown in equation (10).…”

Section: Establishment Of Bp Neural Network Algorithm Modelmentioning

confidence: 99%