Ідентифікація транспортних засобів у проектах сільськогосподарського виробництва
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Дата
2018
ORCID
DOI
Науковий ступінь
Рівень дисертації
Шифр та назва спеціальності
Рада захисту
Установа захисту
Науковий керівник
Члени комітету
Видавець
НТУ "ХПІ"
Анотація
Запропоновано ідентифікацію транспортних засобів для перевезення сільськогосподарських вантажів виконувати за допомогою нейронної мережі у вигляді багатошарового персептрона. Перший шар здійснює вибір транспортного засобу за видом вантажу, другий враховує можливість використання в дорожніх умовах маршруту, третій здійснює вибір транспортних засобів за обсягом партії перевезення. Вихідний нейрон здійснює вибір транспортного засобу, який забезпечує досягнення мінімальних витрат на транспортування вантажу в заданих умовах.
Agricultural cargoes, by their physical and mechanical properties, loading and unloading methods; conditions of transportation and storage, the possibility of using the carrying capacity of vehicles, their preservation during transportation, the degree of danger during loading, unloading, and transportation cover the whole possible range of variation. This causes the need to attract practically all types of tractor and motor vehicles for their transportation. Identification of vehicles in agricultural production projects involves taking into account a significant number of factors and restrictions that are determined by the properties of the cargo, the volumes of the consignment and the conditions of the route of the carriage. The presence of a large number of tractor and motor vehicles used in agricultural production, as well as a large number of factors that determine the effectiveness of their use, necessitates the use of the theory of neural networks for the identification of vehicles in agricultural production projects. The identification of vehicles for the transportation of agricultural cargoes is proposed using a neural network in the form of a multilayered perceptron. The first layer of network neurons performs a function of choice among a plurality of available vehicles, a set of such means that provide the transportation of a given type of cargo. The second layer of neurons checks each vehicle for the possibility of using them in the road conditions of the transportation route and removes those that can not carry out a transport operation under the given road conditions. The third layer of neurons is designed to take into account the size of the consignment and the efficiency of the use of the load-carrying capacity of the vehicle. The initial neuron carries out the choice of the vehicle, which ensures achievement of minimal expenses for transportation of cargo under the given conditions.
Agricultural cargoes, by their physical and mechanical properties, loading and unloading methods; conditions of transportation and storage, the possibility of using the carrying capacity of vehicles, their preservation during transportation, the degree of danger during loading, unloading, and transportation cover the whole possible range of variation. This causes the need to attract practically all types of tractor and motor vehicles for their transportation. Identification of vehicles in agricultural production projects involves taking into account a significant number of factors and restrictions that are determined by the properties of the cargo, the volumes of the consignment and the conditions of the route of the carriage. The presence of a large number of tractor and motor vehicles used in agricultural production, as well as a large number of factors that determine the effectiveness of their use, necessitates the use of the theory of neural networks for the identification of vehicles in agricultural production projects. The identification of vehicles for the transportation of agricultural cargoes is proposed using a neural network in the form of a multilayered perceptron. The first layer of network neurons performs a function of choice among a plurality of available vehicles, a set of such means that provide the transportation of a given type of cargo. The second layer of neurons checks each vehicle for the possibility of using them in the road conditions of the transportation route and removes those that can not carry out a transport operation under the given road conditions. The third layer of neurons is designed to take into account the size of the consignment and the efficiency of the use of the load-carrying capacity of the vehicle. The initial neuron carries out the choice of the vehicle, which ensures achievement of minimal expenses for transportation of cargo under the given conditions.
Опис
Ключові слова
сільськогосподарська продукція, транспортні операції, сільськогосподарські вантажі, нейронна мережа, vehicle, project, cargo, neural network
Бібліографічний опис
Тимочко В. О. Ідентифікація транспортних засобів у проектах сільськогосподарського виробництва / В. О. Тимочко, Р. І. Падюка, І. М. Городецький // Вісник Національного технічного університету "ХПІ". Серія: Стратегічне управління, управління портфелями, програмами та проектами = Bulletin of the National Technical University "KhPI". Series: Strategic management, portfolio, program and project management : зб. наук. пр. – Харків : НТУ "ХПІ", 2018. – № 1 (1277). – С. 75-79.