Add to ORKGThe 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
This paper investigated the resistance performance of a submersible surface ship (SSS) in different ...
It has been found that an artificial neural network is able to produce results of sufficient accurac...
As interest in eco-friendly ships increases, methods for status monitoring and forecasting using in-...
The possibility to use Artificial Neural Network for estimating ship resistance and propulsion coeff...
Ship resistance is one of the major components of the ship which hampers its motion. This resistance...
This thesis focuses on resistance of fast displacement catamarans, with the purpose of developing an...
The maritime industry is one of the most competitive industries today. However, there is a tendency ...
The Holtrop & Mennen method is widely used at the initial design stage of ships for estimating the r...
This paper proposes the usage of an Artificial neural network (ANN) to predict the values of the res...
This paper proposes the usage of an Artificial neural network (ANN) to predict the values of the res...
This study deals with an artificial neural network (ANN) modelling of a marine diesel engine to pred...
Resistance of the bare hull of the tourist submarine with spherical heads, moving in forward and tra...
One of the biggest challenges facing the shipping industry in the coming decades is the reduction of...
The investigation of marine diesel engines is still limited and considered new in both: physical tes...
In this work we will be based on two experimental-based statistical techniques, which allow us to de...
This paper investigated the resistance performance of a submersible surface ship (SSS) in different ...
It has been found that an artificial neural network is able to produce results of sufficient accurac...
As interest in eco-friendly ships increases, methods for status monitoring and forecasting using in-...
The possibility to use Artificial Neural Network for estimating ship resistance and propulsion coeff...
Ship resistance is one of the major components of the ship which hampers its motion. This resistance...
This thesis focuses on resistance of fast displacement catamarans, with the purpose of developing an...
The maritime industry is one of the most competitive industries today. However, there is a tendency ...
The Holtrop & Mennen method is widely used at the initial design stage of ships for estimating the r...
This paper proposes the usage of an Artificial neural network (ANN) to predict the values of the res...
This paper proposes the usage of an Artificial neural network (ANN) to predict the values of the res...
This study deals with an artificial neural network (ANN) modelling of a marine diesel engine to pred...
Resistance of the bare hull of the tourist submarine with spherical heads, moving in forward and tra...
One of the biggest challenges facing the shipping industry in the coming decades is the reduction of...
The investigation of marine diesel engines is still limited and considered new in both: physical tes...
In this work we will be based on two experimental-based statistical techniques, which allow us to de...
This paper investigated the resistance performance of a submersible surface ship (SSS) in different ...
It has been found that an artificial neural network is able to produce results of sufficient accurac...
As interest in eco-friendly ships increases, methods for status monitoring and forecasting using in-...