Empirical prediction of resistance of fishing vessels

dc.contributor.advisor	Steen, Sverre
dc.contributor.author	Kleppestø, Kristoffer
dc.date.accessioned	2015-10-05T15:05:13Z
dc.date.available	2015-10-05T15:05:13Z
dc.date.created	2015-06-09
dc.date.issued	2015
dc.identifier	ntnudaim:12895
dc.identifier.uri	http://hdl.handle.net/11250/2350897
dc.description.abstract	The possibility to use Artificial Neural Network for estimating ship resistance and propulsion coefficients are investigated. Different ANNs are tested by varying input parameters, network size and complexity and division of data material into training and testing sets. ANN prediction methods are trained for Resistance (Cr), total propulsion efficiency (nD), open water efficiency (n0), hull efficiency (nH), wake fraction (w), thrust deduction (t) and relative rotative efficiency (nR). The data material for the thesis are model test results from MARINTEK and consist of 193 fishing vessels and loading conditions.
dc.language	eng
dc.publisher	NTNU
dc.subject	Marin teknikk, Marin hydrodynamikk
dc.title	Empirical prediction of resistance of fishing vessels
dc.type	Master thesis
dc.source.pagenumber	85