Multiparameter Sensitivity Analysis of Operational Energy Efficiency for Inland River Ships Based on Backpropagation Neural Network Method

作者：Yan, Xinping^*; Sun, Xing; Yin, Qizhi

来源：Marine Technology Society Journal, 2015, 49(1): 148-153.

DOI：10.4031/MTSJ.49.1.5

• energy efficiency
• artificial neural network
• sensitivity

With the introduction of,energy effiCiency operational indicator (g01):to inland river ships, a Oultipararrieter sensitivity analysis rilethod: was proposed tO3analyZe the parameters affecting the operational energy efficiency of inland river Ships On the Oasis of experimental data, a,mod0 based on a,paCkpropagation 417t if ielat neural fletwbrki(BP-ANN) 1,10- predicting the EEGI,wat set Ca. The accuracy of this predictive' model was verified On the basis of weightSland threshOld, values of eachNariable parameter gained in the trained BP-ANN, a Gerson algorithm was used for calculating the parameter sensitivity faCtorfiesults showed that besides the engine speed, the " ehVironifient cenditiofis would alsb play a big part in the operational energy efficiency ofitilanaririvWships:The conclusion providesa foundation for engaging the energy efflp'encimprovemerit strategieSfor inland river Ships

• 出版日期2015-2
• 单位武汉理工大学