генетичний алгоритм

INVESTIGATION OF SENSOR NODE PLACEMENT ON A PLANE USING A GENETIC ALGORITHM

The study focuses on investigating the efficiency of a genetic algorithm-based sensor node placement method for a random topology. The primary objective is to identify a node configuration that minimizes the number of "blind spots" and ensures the most efficient coverage of a given area. Random node placement is characterized by the potential for each node to establish connections with other nodes, resulting in a complex search space. For this study, 25 nodes with identical sensing radii were analyzed.

PERFORMANCE ANALYSIS OF CNN-ENHANCED GENETIC ALGORITHM FOR TOPOLOGICAL OPTIMIZATION IN METAMATERIAL DESIGN

The Combination of Convolutional Neural Networks (CNN) and Genetic Algorithms (GA) provides a promising approach for topological optimization of complex lattice structures. Lattice structures are commonly used as base in the design of high-performance metamaterials. This paper presents a review of the effectiveness and efficiency of the CNN-GA method. We will examine the ability of the method to generate optimal complex structures while minimizing material usage. CNN is utilized mainly as an analysis instrument.

COMBINED APPROACH TO BUILDING OPTIMAL ROUTES FOR INDIVIDUAL TRIPS IN A MOBILE APPLICATION

The paper deals with building optimal routes for individual trips under the influence of many factors and possible changes in the input parameters (such as weather conditions, traffic congestion, etc). We have analyzed four classes of algorithms for solving the traveling salesperson problem and evaluated their applicability in a tourist mobile application. The software should be a mobile application since only a few travelers take computers or laptops but most of them carry smartphones.

SEARCH FOR A DATA TRANSMISSION ROUTE IN A WIRELESS SENSOR NETWORK USING A GENETIC ALGORITHM

The article is devoted to the application of a genetic algorithm for determining the optimal route in a wireless sensor network. The paper presents a classification of data routing strategies based on: the method of determining routes, network structure, network operations, and communication organiser. The genetic algorithm is classified as a multi-path routing strategy, since its use allows obtaining a set of routes.

COMPUTATIONAL COMPLEXITY EVALUATION OF A GENETIC ALGORITHM

The article is devoted to the estimation of computational complexity of a genetic algorithm as one of the key tools for solving optimisation problems. The theoretical aspects of computational complexity of algorithms and the interrelation of elements of a genetic algorithm are considered. The main types of computational complexity of algorithms are described: time, simple and asymptotic. Five basic rules for calculating the asymptotic complexity are given.

Використання генетичних алгоритмів для апроксимації функцій дійсними поліномами

Наведено метод апроксимації функцій поліномами з дійсними степенями, в якому підбір степеня здійснюється за допомогою генетичного алгоритму.

The method of approximation of functions by polynomials with real powers, which is the power of selection with a genetic algorithm.

GENETIC ALGORITHM AS A TOOL FOR SOLVING OPTIMISATION PROBLEMS

The article focuses on the peculiarities of using the genetic algorithm (GA) for solving optimization problems. It provides a classification of optimization problems and offers a detailed description of the structural elements of the GA and their role in solving the traveling salesman problem. To assess the impact of GA parameters on its effectiveness, a study on the influence of population size on the length of the traveling salesman's route is conducted.

Design of the system of automated generation of poetry works

 Features of designing a system of automated generation of poetic works, which opens up new opportunities for artistic speech and show business, especially the preparation of poems and songs have been considered. Quite often lyrics without special content become successful due to the lack of complex plots, as well as due to the unobtrusiveness and ease of perception by listeners. Well-known literature sources and available software products that can generate poetic works by combining different methods and algorithms are analyzed.

Construction of Empirical Models of Complex Oscillation Processes with Non-Multiple Frequencies Based on the Principles of Genetic Algorithms

A method for constructing the empirical models of complex processes has been developed on the basis of genetic algorithms which, compared to the inductive method of self-organization of models, significantly reduces computer time for their implementation. An approach has been used that allows a complex model to be considered as a composition of three components, i.e. a linear trend, an oscillatory component with non-multiple frequencies and a regression equation which simplifies the process of building complex models.