Journal
MARINE TECHNOLOGY SOCIETY JOURNAL
Volume 49, Issue 1, Pages 148-153Publisher
MARINE TECHNOLOGY SOC INC
DOI: 10.4031/MTSJ.49.1.5
Keywords
energy efficiency; artificial neural network; sensitivity
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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
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