Проблемы интеллектуализации решения задач моделирования и управления производственными процессами - Тимашова, Л.А. (Управляющие системы и машины, 2016)
Изложены проблемы интеллектуального моделирования для управления производственными процессами, найдены пути их решения с помощью новых методов, базирующихся на теории искусственного интеллекта. Показаны информационные технологии работы со знаниями, прецедентами, образами для задач управления производственными процессами и управления бизнес-аналитикой. Викладено проблеми інтелектуального моделювання для управління виробничими процесами, знайдено шляхи їх розв’язання за допомогою нових методів, що базуються на теорії штучного інтелекту. Показано інформаційні технології роботи зі знаннями, прецедентами, образами для задач управління виробничими процесами і управління бізнес-аналітикою. Methods. Existing computer-aided facilities are not always ready for the high-quality solving of the management problems, that are different from traditional problems in an algorithmic way. The intelligent modeling aids can be such a tool. Purpose. The approaches for the intelligent modeling include the use of both classic mathematical methods (fuzzy sets, multiagent systems, genetic algorithms and methods) and development of models for mentation as the main function of human intelligence. The classic methods mentioned above work efficiently under conditions of uncertainty of the management processes. A concept version for the intelligent modeling systems realization to make the executive production decisions is proposed. The simulation and artificial intelligence technologies are united. The simulation technologies proved to be efficient for the certain classes of day-to-day management problems. Artificial intelligence deals with the development of the systems based on knowledges. Such systems include both knowledges necessary for qualified research for the simulation of the corresponding classes objects and knowledges of the personnel management that makes management decisions. Thus, the limits of simulation application methods extend considerably because the end-users of these systems should not have any special knowledge in the field of programming and simulation anymore. Conclusion. The results of this research can be used as a theoretical and methodological base by the enterprises managers, scientific bodies in the process of research and realization of the approaches for management of enterprises to control the innovation processes, to teach students and post-graduate students.