Assessment of Hull and Propeller Performance Degradation Based on TSO-GA-LSTM

Assessment of Hull and Propeller Performance Degradation Based on TSO-GA-LSTM

Blog Article

Evaluating the degradation of hull and ship performance and exploring their degradation pathways is crucial for developing scientific and reasonable ship maintenance plans.This paper proposes a two-stage optimization (TSO) algorithm that combines the Genetic Algorithm (GA) and Long Short-Term Memory (LSTM) network, campicon.com capable of simultaneously optimizing input features and model parameters to enhance the accuracy and generalization ability of speed prediction models.Additionally, a performance degradation assessment method based on speed loss is provided, aimed at evaluating the degradation of 6-0 igora vibrance hull and propeller performance, as well as extracting the performance degradation paths.

The results indicated that the proposed TSO-LSTM-GA algorithm significantly outperformed existing baseline models.Furthermore, the provided performance degradation assessment method demonstrated certain effectiveness on the target ship data, with a measured degradation rate of 0.00344 kn/d and a performance degradation of 9.

569% over 478 days, corresponding to an annual speed loss of 1.257 kn.