... interaction platform ship production neural network machine learning month 2023 journal ship production and design engineering experiment offshore platform accommodation cabin offshore platform evaluation industrial ergonomic operator module kansei engineering participant Journal of Ship...

...Jinho Song; Junhee Lee; Daewoon Kim; Won-Don Kim; Tae-Won Kang; Jeung-Youb Kim; Jong-Ho Nam; Kwanghee Ko This article introduces an artificial neural network (ANN) model to determine cycle-times for forming curved hull plates when the target shape is known. The proposed model aids shipbuilding...

... into a competitive advantage through predictive analytics. Not only can this data be literally mined, but machine learning algorithms, such as Artificial Neural Networks (ANN), can now process it for a speedy and preliminary estimate through faster and cheaper computing power. To be clear, the purpose...

... to various hull plate types, with the performance of each classifier evaluated using cross-validation. A classifier applying a convolution neural network as a deep learning technology was found to have the highest prediction accuracy, which exceeded the accuracies obtained in previous hull plate...

... reduced on application of TMT to a welding process, reducing the tendency of plate buckling due to welding. In the present work, an artificial neural network (ANN)-based modeling of the TMT process was also carried out to predict the weld-induced out-of-plane deformation for different rates of heat inputs...

...Amith Gadagi; Nisith Ranjan Mandal The present work deals with the prediction of heat source parameters of Goldak's double ellipsoidal model for flux cored arc welded fillet joints through an artificial neural network (ANN). Extensive experiments were carried out on low-carbon mild steel plates...

... neural network human computer interaction design process operation mapping stakeholder knowledge management marine transportation ship design process requirement designer Artificial Intelligence ship production architecture Ship Operation Engineering proceedings field study human...

... of Naval Architects and Marine Engineers machine learning neural network Upstream Oil & Gas Engineering prediction heating process heating line fuzzy logic heat source heating Artificial Intelligence marine transportation Simulation line heating ship production Laser Shen sheet...

... proposition rsc method neural network information ship production Ross value proposition epoch responsive system comparison method value robustness stakeholder Changeability design problem Journal of Ship Production and Design, Vol. 34, No. 1, February 2018, pp. 72 83 httpdx.doi.org/10.5957...

...Dejan V. Radojcic; Milan D. Kalajdzic; Antonio B. Zgradic; Aleksandar P. Simic Recent advances in high-speed computing, combined with the emergence of artificial neural network (ANN) techniques for the analysis of large data sets, has enabled researchers to provide the design community with higher...

...Dejan V. Radojcic; Antonio B. Zgradic; Milan D. Kalajdzic; Aleksandar P. Simic Recent advances in high-speed computing, combined with the emergence of artificial neural network (ANN) techniques, for the analysis of large data sets have enabled researchers to provide the design community with higher...

...Le Thanh Tung Ship autopilots play an important role in insurance of safe navigation and efficient transportation as else. For their successful design and development, many control techniques were and are being developed. In this paper, the application of artificial neural network (ANN...

..., this article established a model based on the Bayesian regularization back propagation (BP) neural network to predict the curve radius of shape formed. With this model and the test sample recorded in the experiment, the calculation results showed that the model could reflect the relationship between...

.... In the present study, mathematical representations are developed for the Series 50 as an alternative to using charts or data tables. Two methods are used, regression analysis and artificial neural networks. This study provides a useful resistance prediction method for designers and an opportunity to compare...

... 11 2011 2011. The Society of Naval Architects and Marine Engineers Fluid Dynamics Simulation neural network computational fluid dynamic prediction Upstream Oil & Gas CFD Simulation CFD Engineer Artificial Intelligence modeling optimization proceedings cavitation complex...

...Dunja Matulja; Roko Dejhalla; Ozren Bukovac The idea of the present study is to apply the advantages of neural networks to the choice of an optimum ship screw propeller as an introduction to more complex ship design problems. The neural network was created and trained to provide the characteristics...

... methodology reveals the benefits of a holistic scientific approach to the optimization of complicated transportation problems. 1 2 2010 1 2 2010 freight & logistics services marine transportation road detail machine learning neural network new sea route optimization problem...

... computing time is necessary. In this study, simplification of the prediction was done using a neural network model, in which the calculation result of the FEM analysis was incorporated in teacher data, for the fillet welding of T-type buildup structure, etc. This program would be able to estimate...

...Nancy C. Porter; J. Allan Cote; Timothy D. Gifford; Wim Lam Based on the orientation and travel speed of a welding torch, virtual reality technology simulates gas metal arc welding in near-real time using a neural network. Artificial Intelligence weld pool Upstream Oil & Gas curriculum...

... with specifications for fairness. The Portable Automated Plate Straightener (N.A. Tech, Golden, CO) is an application of flexible automation. It is able to straighten the deckplates without operator intervention. Artificial Intelligence metals & mining transfer function machine learning neural network...