Operation of Maritime Transport Operation of Maritime Transport Эксплуатация морского транспорта 1992-8181 53898 10.34046/aumsuomt102/21 Раздел 2 СУДОВЫЕ ЭНЕРГЕТИЧЕСКИЕ УСТАНОВКИ, СИСТЕМЫ И УСТРОЙСТВА ON BOARD POWER PLANTS, SYSTEMS AND DEVICES Раздел 2 СУДОВЫЕ ЭНЕРГЕТИЧЕСКИЕ УСТАНОВКИ, СИСТЕМЫ И УСТРОЙСТВА DEVELOPMENT OF NEURAL NETWORKS FOR PREDICTING THE RISK OF FAILURE OF COMPONENTS OF SHIP MACHINES AND MECHANISMS OF MARINE AUTONOMOUS SURFACE VESSELS РАЗРАБОТКА НЕЙРОННЫХ СЕТЕЙ ДЛЯ ПРОГНОЗИРОВАНИЯ РИСКА ВЫХОДА ИЗ СТРОЯ КОМПОНЕНТОВ СУДОВЫХ ТЕХНИЧЕСКИХ СРЕДСТВ МОРСКИХ АВТОНОМНЫХ НАДВОДНЫХ СУДОВ SCURTU Ionut Cristian SCURTU Ionut Cristian Епихин Алексей Иванович I Epikhin A I bsmbeton@mail.ru Хекерт Евгений Владимирович V Khekert E V zur_mga@nsma.ru Naval Academy ru Naval Academy ru ФГБОУ ВО «ГМУ им. адм. Ф.Ф. Ушакова» ru ФГБОУ ВО «ГМУ им. адм. Ф.Ф. Ушакова» ru ФГБОУ ВО «ГМУ им. адм. Ф.Ф. Ушакова» ru ФГБОУ ВО «ГМУ им. адм. Ф.Ф. Ушакова» ru 25 03 2022 25 03 2022 1 103 107 20 03 2022 20 03 2022 https://aumsu.editorum.ru/en/nauka/article/53898/view

В статье рассмотрены возможности применения подходов нейрокибернетики для осуществления интеллектуального прогнозирования риска выхода из строя компонентов судовых технических средств морских автономных надводных судов. В процессе исследования предложен алгоритм, который позволяет построить формальную модель рисков отказа наблюдаемых узлов и оборудования судовых установок на основании задач классификации и распознавания образов. Также предложен алгоритм инициализации нейронной сети, благодаря которому может быть достигнута заданная точность определения параметров работы технических средств, что дает возможность обеспечить гибкость настройки управления возникающими рисками на основании заранее определенных критериев.

The article discusses the possibilities of applying neurocybemetics approaches for the implementation of intelligent prediction of the risk of failure of components of ship technical means of autonomous sea surface ships. In the course of the research, a method was proposed that allows one to build a formal model of the observed units and equipment of ship installations based on the tasks of classification and pattern recognition. An algorithm for the initialization of a neural network is also proposed, which makes it possible to achieve a given accuracy of determining the parameters of the operation of technical means, which makes it possible to provide flexibility in setting up management of emerging risks based on predetermined criteria.

 риски узлы оборудование судно прогнозирование risks units equipment vessel forecasting management

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