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Browsing by Keyword artificial intelligence:

  • Łosiewicz, Zbigniew; Pielka, Dariusz (Scientific Journals of the Maritime University of Szczecin, Zeszyty Naukowe Akademii Morskiej w Szczecinie, 2009)
    In the modern systems of operation monitoring and of early detection of technical condition changes, additionally to the monitoring and measuring function, there is required the analysis of information in purpose to support the operator in making decisions. Such high complexity of a problem needs application of the fast methods of analysing the information in variety of aspects. Presently, in monitoring of a marine piston diesel engine tremendous importance the methods have, which are based on artificial intelligence both in a meaning of analysis of the individual processes and in complex analysis of a whole object. Merits of the artificial intelligence methods are – high flexibility, versatility and possibility to use the object for analysis with no need to have a mathematical description of the examined object, or occurring processes, what often imposes the considerable difficulty and restrictions in examination to be carried out
  • Lisowski, Józef (Scientific Journals Maritime University of Szczecin, Zeszyty Naukowe Akademia Morska w Szczecinie, )
    This paper describes an application of the dynamic programming method to determine the safety of one’s own ship trajectory during encounter of other ships. A dynamic model of the process, with kinematic constraints of state and determined by a three-layer artificial neural network has been used for the development of control pro- cedures. Non-linear activation functions in the first and second layers may be characterised by a tangent curve while the output layer is of a sigmoidal nature. The Neural Network Toolbox of the Matlab software has been used to model the network. The learning process used an algorithm of backward propagation of the error with an adaptively selected learning step. The considerations have been illustrated through an example implemented in a computer simulation using the algorithm for the determination of the safe ship trajectory in situations of en- counter of multiple ships, recorded on the ship’s radar screen in real navigational situation in the Kattegat Strait.
  • Łącki, Mirosław (Scientific Journals Maritime University of Szczecin, Zeszyty Naukowe Akademia Morska w Szczecinie, )
    The goal of research presented in this article is to check if a neuroevolutionary method with direct encoding is able to be a part of autopilot of the vessel. One of the important tasks of vessel autopilots is to keep a course as straight as possible or to bring the ship back on the route as efficiently as possible. In this paper, the adaptive neuroevolutionary autopilot is described and tested on a simulation model of a ferry. Neuroevolution is a combination of two different but related fields of artificial machine learning: evolution and neural networks. The combined method is very flexible and can be applied to other ship control tasks. The results of computer simulation of the neuroevolutionary course-keeping system have been included.

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