Analysis and forecastingof economic data with avariable structure base dona quasi-genetical gorithm

Abstract

Importance: in this article, a quasi-genetic algorithm (GA) is defined as an algorithm that implements a generalized and adaptive version of the classical genetic algorithm. This approach retains the key mechanisms and ideas of the GA, but allows for flexible changes in the structure and logic of operation, depending on the specific task at hand. Purpose: this article demonstrates an information system for analyzing and predicting large data sets based on a linear cellular automaton algorithm using the JavaScript programming language with TypeScript typing and the Angular framework. JavaScript libraries such as math.js for performing basic mathematical operations and chart.js for creating visualizations of data are used for mathematical calculations and modeling of linear cellular automata. These libraries provide the necessary accuracy and speed for processing calculations. Research design: based on the fact that cellular automata are discrete dynamic systems that change their state at successive discrete moments of time according to a certain law, depending on the state of the element under consideration and its neighbors at the previous discrete moment of time. These systems are actively used for modeling dynamic processes in economics, sociology, biology, computer science, etc. Results: a distinctive feature of the presented development, which implements the linear cellular automaton algorithm, is the ability to make predictions for a specified number of steps based on the identified long-term memory