Development of a method for assessing the state of dynamic objects using a population algorithm
Year: 2024
Type: article
Abstract: The object of the study is complex dynamic objects with a hierarchical structure. A method for assessing the state of dynamic objects using a population algorithm is proposed. The study is based on the snake optimization algorithm for finding a solution to the state of dynamic objects with a hierarchical structure. For training snake agents (SA), evolving artificial neural networks are used. The originality of the method lies in using additional advanced procedures that allow you: – to determine the initial position of SA, taking into account the type of uncertainty by using a correction factor for the degree of awareness of the state of the initial situation in relation to the object of analysis; – to take into account the initial velocity of each SA, which allows studying complex functions; – to ensure the universality of SA food location search strategies, which allows classifying the type of data to be processed; – to adjust the SA velocity by adjusting the ambient temperature, which allows priorizing the search for a solution in a certain plane; – to explore the solution spaces of functions described by non-typical functions, using exploitation mode procedures; – to flexibly adjust the transition from the SA fighting mode to the mating mode using the food saturation coefficient; – to replace individuals unsuitable for search using the SA fertility rate; – to conduct a simultaneous search for a solution in different directions, by changing the ambient temperature and adjusting the food saturation coefficient. Modeling showed a 13–19 % increase in data processing efficiency by using additional improved procedures.
Institutions: National University "Kyiv Aviation Institute", National Defence University of Ukraine, Military Institute of Telecommunications and Informatization, National University "Yuri Kondratyuk Poltava Polytechnic", Kharkiv National Automobile and Highway University, University of Applied Sciences Technikum Wien
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $242
OpenAlex ID: W4402172475