Intelligent Recommendation of Overall Ship Performance APP
HONG Huajun
WANG Chunyan
Abstract：Considering the complexity and exploratory nature of scientific research in the professional field of ships,research-ers cannot screen out the suitable APP quickly for the current research objectives from various simulation computing software(APP)in the field of ship overall performance prediction,evaluation and optimization.An intelligent recommendation model of APP for ship overall performance based on deep learning is proposed.Multi-dimensional feature vectors of researchers'data and ship overall performance APP are constructed,personnel features and APP features are extracted through deep neural network,and the cosine similarity between features is calculated.And the fusion information such as APP score,APP computing task statistics and APP ac-cess statistics is used as the similarity measure standard to train the model and generate the recommendation model.The results show that the recommendation model can actively recommend accurate apps for researchers,help them find appropriate ship perfor-mance apps,and realize personalized intelligent recommendation of apps quickly.Compared with the other two traditional methods,this model performs well in terms of accuracy,error,and F1 score.
Keywords：intelligent recommendation systemdeep learningdeep neural networks
Publication Date：2025-11-20
Online Publishing Date：2026-01-28(First online date of this platform, not the publication date of the document)
Pages：6( 3179-3184 )