Abstract
In order to optimize the price evaluation of used sailboats, this paper collects and analyzes a large amount of relevant data, and adopts principal component analysis, multiple linear regression and neural network model to establish the linkage between price and each variable. The non-numerical data are quantified and processed, and the comprehensive evaluation model is constructed by entropy value method and linear weighting method. The TOPSIS method was used to revalue the price and optimize the model. The geographic location is quantified by spherical coordinates and analyzed by clustering to build a geographic-price model. Finally, taking Hong Kong as an example, the time series and support vector machine models are used for pricing.
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