Research Article
Data Research Based on the Hong Kong Sailing Market
@INPROCEEDINGS{10.4108/eai.26-5-2023.2334411, author={Yangting Liu}, title={Data Research Based on the Hong Kong Sailing Market}, proceedings={Proceedings of the 2nd International Conference on Mathematical Statistics and Economic Analysis, MSEA 2023, May 26--28, 2023, Nanjing, China}, publisher={EAI}, proceedings_a={MSEA}, year={2023}, month={7}, keywords={arima model xgboost model k-means clustering grid search algorithm}, doi={10.4108/eai.26-5-2023.2334411} }- Yangting Liu
Year: 2023
Data Research Based on the Hong Kong Sailing Market
MSEA
EAI
DOI: 10.4108/eai.26-5-2023.2334411
Abstract
This article mainly conducted data research on the Hong Kong sailing market. First, we divided the factors that affect the price of sailboats into two categories. The first category is macro factors such as time and region, and the second category is micro factors that are specific to the attributes of a sailboat. For the former, we built an ARIMA model of time series distribution to predict the time forecast of the average price of sailboats, and for the latter, we built a Bayesian optimization XGBoost model based on machine learning to predict the price of a sailboat under different factors. Then, we apply the established model to Hong Kong and give the forecast of the Hong Kong market. At the same time, in view of the poor information obtained from the data, we evaluated a variety of prediction algorithms and gave the optimal solution. Next, we summarize innovative conclusions from natural conditions, economics, and sailboat design. Finally, we performed a sensitivity analysis and strengths and weaknesses analysis of the model, and evaluated the rationality of the model used at each step.