Predictive analysis of heat exchange capacity of underwater spiral coil heat exchanger based on GA-XGBoost modeling
A heat exchange prediction method for underwater spiral coil heat exchanger based on the GA-XGBoost model is proposed.Firstly,an experimental test platform based on PLC and Wince host computer is built for simulating the joint operation process of underwater spiral coil heat exchanger and surface water heat pump,from which the experimental datasets under different working conditions are obtained;then,a composite model based on genetic algorithm and XG-Boost is proposed for predicting heat exchanger capacity,which adopts genetic algorithm to opti-mize the XGBoost model,and introduces a new composite model to predict heat exchanger capaci-ty,and a new composite fitness function is introduced to guide the parameter optimization process of the genetic algorithm;finally,a validation is carried out based on the collected experimental dataset,with multiple features of the heat exchanger as the model inputs and heat exchanger ca-pacity as the outputs,and an average absolute percentage error of 3.21％is obtained,the root-mean-square error is 0.476,and the coefficient of determination reaches 0.974,and the results show that the method has a good prediction performance and generalization ability on the dataset,which provides a reference basis for the design and performance optimization of underwater heat exchangers and has high value for engineering applications.
万方数据
维普
