система підтримки прийняття рішень

The work carried out a comparative analysis of scientific publications regarding the possibility of predicting the direction of the cryptocurrency exchange rate using the data of open numerical indicators, based on the results of which it can be concluded that due to the volatility of the cryptocurrency market and the need for accurate forecasting, there is a need to create an aggregated indicator that will take into account the current price exchange rate asset, parameters of simple indicators, trading volume, etc.

The National Cybersecurity Cluster of Ukraine is functionally oriented towards building systems to protect various platforms of information infrastructure, including the creation of secure technologies for detecting deepfake modifications of biometric images based on neural networks in cyberspace. 

This space proposes a conceptual approach to detecting deepfake modifications, which is deployed based on the functioning of a convolutional neural network and the classifier algorithm for biometric images structured as “sensitivity-Yuden index-optimal threshold-specificity”.

Для прийняття об’єктивних обґрунтованих рішень у всіх сферах діяльності необхідно створювати інформаційні системи підтримки прийняття рішень на основі статистичних даних і експертних оцінок та з використанням відповідних математичних моделей та методів. Запропоновано процедуру побудови інформаційної системи підтримки прийняття рішень за методологією системного аналізу на основі сучасних методів і моделей прогнозування, яка надає можливість оцінювати та прогнозувати фінансово- економічні та інші процеси в умовах впливу збурень довільних типів та різної природи.

Описано методології планування потреб у ресурсах. Проаналізовано програмні комплекси систем розподілу ресурсів і обґрунтовано потребу в розробленні своєї системи підтримки прийняття рішень. Проведено тестування прототипу СППР розподілу обмежених ресурсів, яка реалізує розроблені моделі та алгоритми.

To form a knowledge base is complicated problem traditionally. There are a lot kind of objects that are possibly used for forming a knowledge base. These objects may have different structures, formats, ways of data representation, languages. The simple conjunction is not effective and suitable. In general case the knowledge base has got as an unordered knowledge base. There are uncategorized documents in such unordered knowledge base with different formats that causes the special and particular approaches for recognition, systematization and next processing of some textual information.

A typical standard architecture of the support system has been proposed, making decisions on forming and implementing solutions based on cross-programming and heavy calculations and similar functional capabilities before it. The technology for disaggregating such systems on the basis of cross- programming and efficient calculations, as well as reducing costs/hours/resources for disaggregation, promotion and support of such support systems to support the adoption of a solution, has also been proposed.

This article describes the classification and approaches to the construction of DSS that take into account various aspects of the uncertainty of the development of DSS. Features of the classification were proposed and described. Generalized classification of DSS was improved. The analysis of the types of architecture, architecture reviewed information resource decision support systems, based on the principles of building a data warehouse.