The book "Methods of identification of fuzzy and stochastic systems", written by a team of authors, is a unique and in-depth study in the field of management theory and system analysis. This edition will be a real find for specialists, students and researchers interested in modern methods of identification, which are used in conditions of uncertainty and randomness. In today's world, where technology is developing at an incredible speed, the need for effective methods of management and analysis of systems is becoming increasingly urgent. The book covers a wide range of topics related to fuzzy and stochastic systems, and offers readers the tools to identify them. The authors examine in detail various approaches, including fuzzy logic, statistical methods and machine learning algorithms, which allow to create models capable of responding adequately to changing conditions. Readers interested in areas such as automation, robotics, artificial intelligence, and control theories will find a wealth of useful information in this book. It is suitable for both technical students and experienced professionals seeking to expand their knowledge and skills in the field of system analysis. The book will be especially useful for those who work in areas where the processing and analysis of large amounts of data is required, as well as in situations where it is necessary to make decisions in conditions of uncertainty. The topics raised in the book cover not only theoretical aspects, but also practical applications of identification methods. The authors share examples from real practice, which allows the reader to better understand how to apply the knowledge gained in their work. The book also addresses important issues related to data quality, which is a critical aspect in modern research and development. The style of the authors is distinguished by clarity and accessibility, which makes complex concepts understandable even for those who are just beginning to get acquainted with this topic. The book is written taking into account current trends and achievements in science and technology, which allows the reader to be aware of current research and development. The team of authors includes experts with many years of experience in various fields, which gives the book additional value and authority. If you are looking for literature that will help you understand the complex issues of identifying systems, then “Methods for identifying fuzzy and stochastic systems” will be an excellent choice. This book will not only expand your knowledge, but also inspire new ideas and projects. It will be interesting not only for those who already work in this field, but also for those who are just starting their way in the world of science and technology. In conclusion, it is worth noting that this publication is an important contribution to the literature on system analysis and management. It opens new horizons for the research and application of identification methods, making it an indispensable resource for all who seek professional growth and development in this dynamically developing field. Do not miss the opportunity to get acquainted with this book and immerse yourself in the fascinating world of fuzzy and stochastic systems!