Scientific Journal of KubSAU

The article deals with a set of basic patterns of technical analysis and reviews their recognition techniques using neural network methods. The existing approaches to the problem have been set. The reasons of relevance of the described technique have been shown

This article discloses the use of hybrid neural / expertnetwork systems to the problem of finding the significant events of these studies market behavior. The neural network is trained by back propagation, and is used to highlight trends over time. The expert system is used to determine the degree of significance of data

Recent research shows that patterns of stock market indices may contain useful information for the prediction of the stock market price. Currently, there are two basic pattern recognition algorithm: Match the rule and pattern matching. However, both algorithms require the participation of experts in the subject area. To solve these problems, the proposed approach is the recognition of patterns stock exchange indexes based on artificial neural networks. The experiment shows that the neural network is able to effectively study the characteristics of patterns and recognize them with high accuracy

This article discloses the use of neural networks to recognize patterns in control charts. To recognize unnatural situation under control is possible by analyzing the chart pattern. Neural networks with reinforcements are the third generation of neural networks. In this study they are available for recognition in the management chart patterns. The article also discusses options for improvement of the learning algorithm in the form of additional rules for the synoptic pauses, time constants and switching threshold neurons

The article is an example of planning funds for the maintenance and repair of roads in the asphalt performance given their excessive wear during winter