Used sailboat pricing research based on BP neural network optimized by ant colony algorithm

<p style="text-align:center;"> <span><strong>(Communicated by Aifan Ling)</strong></span> <p style="text-align:center;"> <span><strong><br /> </strong></span> <p style="text-align:justify;"> <span><span> We developed a sailboat pricing model that takes into account the different impacts of different boat characteristics on pricing, as well as the important role of brokers and pricing strategies in the boat selling process. The main points of the methodology are: first, we performed feature screening to filter out the main factors affecting pricing, then we constructed a BP neural network regression model to analyze the impact of various factors on pricing, and finally, we used an ant colony algorithm to optimize the parameters of the BP neural network regression model to produce the results. Prior to this, we preprocessed the collected data and introduced dummy variables to improve the quality of the data as the data substituted into the model is highly susceptible to noise, missing values and inconsistent data. Next, we apply the model to evaluate the weights of each factor affecting pricing between single-hull and double-hull vessels. Immediately after we substitute different ship types from different regions into the model, the results show that the weights predicted by our developed model are closer to the actual values than those predicted by the BP neural network model, the random forest model, the XGBoost model, and the LightGBM model, which proves the value of the model when it is applied to the pricing of sailing vessels. Finally we use the model to predict the price of single hull and double hull vessels in different regions using box plots to show the average price and the results show that Caribbean is the cheapest among Catamarans and the most expensive among Monohulled Sailboats.And we show that the stability of the model is greatly improved with the introduction of dummy variables, making the model highly adaptable.</span><br /> </span>