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Wyszukujesz frazę "neuroevolution" wg kryterium: Temat


Wyświetlanie 1-5 z 5
Tytuł:
Evolving co-adapted subcomponents in assembler encoding
Autorzy:
Praczyk, T.
Powiązania:
https://bibliotekanauki.pl/articles/929831.pdf
Data publikacji:
2007
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
sieci neuronowe
ewolucja
neuroewolucja
neural networks
evolution
neuroevolution
Opis:
The paper presents a new Artificial Neural Network (ANN) encoding method called Assembler Encoding (AE). It assumes that the ANN is encoded in the form of a program (Assembler Encoding Program, AEP) of a linear organization and of a structure similar to the structure of a simple assembler program. The task of the AEP is to create a Connectivity Matrix (CM) which can be transformed into the ANN of any architecture. To create AEPs, and in consequence ANNs, genetic algorithms (GAs) are used. In addition to the outline of AE, the paper also presents a new AEP encoding method, i.e., the method used to represent the AEP in the form of a chromosome or a set of chromosomes. The proposed method assumes the evolution of individual components of AEPs, i.e., operations and data, in separate populations. To test the method, experiments in two areas were carried out, i.e., in optimization and in a predator-prey problem. In the first case, the task of AE was to create matrices which constituted a solution to the optimization problem. In the second case, AE was responsible for constructing neural controllers used to control artificial predators whose task was to capture a fast-moving prey.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2007, 17, 4; 549-563
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Ship course-keeping with neuroevolutionary algorithms
Autorzy:
Łącki, M.
Powiązania:
https://bibliotekanauki.pl/articles/135344.pdf
Data publikacji:
2018
Wydawca:
Akademia Morska w Szczecinie. Wydawnictwo AMSz
Tematy:
ship course-keeping
neuroevolution
autopilot
ship maneuvering
artificial intelligence
algorithm
Opis:
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.
Źródło:
Zeszyty Naukowe Akademii Morskiej w Szczecinie; 2018, 54 (126); 70-74
1733-8670
2392-0378
Pojawia się w:
Zeszyty Naukowe Akademii Morskiej w Szczecinie
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
An adaptive island model of population for neuroevolutionary ship handling
Autorzy:
Łącki, Mirosław
Powiązania:
https://bibliotekanauki.pl/articles/2033282.pdf
Data publikacji:
2021
Wydawca:
Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:
artificial neural networks
evolutionary algorithms
neuroevolution
ship movement control
ship manoeuvring
Opis:
This study presents a method for the dynamic value assignment of evolutionary parameters to accelerate, automate and generalise the neuroevolutionary method of ship handling for different navigational tasks and in different environmental conditions. The island model of population is used in the modified neuroevolutionary method to achieve this goal. Three different navigational situations are considered in the simulation, namely, passing through restricted waters, crossing with another vessel and overtaking in the open sea. The results of the simulation examples show that the island model performs better than a single non-divided population and may accelerate some complex and dynamic navigational tasks. This adaptive island-based neuroevolutionary system used for the COLREG manoeuvres and for the finding safe ship’s route to a given destination in restricted waters increases the accuracy and flexibility of the simulation process. The time statistics show that the time of simulation of island NEAT was shortened by 6.8% to 27.1% in comparison to modified NEAT method.
Źródło:
Polish Maritime Research; 2021, 4; 142-150
1233-2585
Pojawia się w:
Polish Maritime Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Intelligent Prediction of Ship Maneuvering
Autorzy:
Łącki, M.
Powiązania:
https://bibliotekanauki.pl/articles/116074.pdf
Data publikacji:
2016
Wydawca:
Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
Tematy:
future of navigation
ship maneuvering
intelligent prediction
prediction of ship maneuvering
neuroevolution
navigational parameters
intelligent ship
autonomous control unit
Opis:
In this paper the author presents an idea of the intelligent ship maneuvering prediction system with the usage of neuroevolution. This may be also be seen as the ship handling system that simulates a learning process of an autonomous control unit, created with artificial neural network. The control unit observes input signals and calculates the values of required parameters of the vessel maneuvering in confined waters. In neuroevolution such units are treated as individuals in population of artificial neural networks, which through environmental sensing and evolutionary algorithms learn to perform given task efficiently. The main task of the system is to learn continuously and predict the values of a navigational parameters of the vessel after certain amount of time, regarding an influence of its environment. The result of a prediction may occur as a warning to navigator to aware him about incoming threat.
Źródło:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2016, 10, 3; 511-516
2083-6473
2083-6481
Pojawia się w:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Indirect encoding in neuroevolutionary ship handling
Autorzy:
Łącki, M.
Powiązania:
https://bibliotekanauki.pl/articles/117302.pdf
Data publikacji:
2018
Wydawca:
Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
Tematy:
ship handling
neuroevolutionary ship handling
artificial intelligence
artificial intelligence method
ship manoeuvering
Neuroevolution
evolutionary algorithms
direct encoding method
Opis:
In this paper the author compares the efficiency of two encoding schemes for artificial intelligence methods used in the neuroevolutionary ship maneuvering system. This may be also be seen as the ship handling system that simulates a learning process of a group of artificial helmsmen - autonomous control units, created with an artificial neural network. The helmsman observes input signals derived form an enfironment and calculates the values of required parameters of the vessel maneuvering in confined waters. In neuroevolution such units are treated as individuals in population of artificial neural networks, which through environmental sensing and evolutionary algorithms learn to perform given task efficiently. The main task of this project is to evolve a population of helmsmen with indirect encoding and compare results of simulation with direct encoding method.
Źródło:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2018, 12, 1; 71-76
2083-6473
2083-6481
Pojawia się w:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-5 z 5

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