Intelligent Processing Methods

Nowadays, in the era of information technology, intelligent data processing methods play an important role in various spheres of life. These methods, together with modern algorithms and computer models, allow extracting valuable information from huge volumes of raw data, as well as analyzing and forecasting various phenomena and trends. The key concepts and principles of operation of the wavelet transform and stochastic methods, as well as their interrelation and possibilities of combined application in solving data processing problems are considered. Intelligent data processing methods focused on the wavelet transform and stochastic methods, which have become an integral part of modern business processes, providing forecasts essential for informed decisions, are investigated. The study used the wavelet transform and stochastic methods to detect hidden patterns and trends in data. These methods provided an opportunity to analyze data of various structures and scales, including texts, images, sound and video. The wavelet transform provided efficient data representation and multiscale analysis, while stochastic methods were used to model uncertainty and perform probabilistic analysis. It was demonstrated that the use of the wavelet transform contributed to the identification of significant features in the analyzed data, while stochastic methods provided reliable forecasts based on statistical models. Practical application of these methods on examples from various fields showed their high efficiency and significance in scientific and applied applications, which confirmed the relevance and prospects of further study and development of intelligent data processing methods. The importance of the wavelet transform and stochastic methods in the context of analyzing large amounts of data and predicting various phenomena was confirmed.