DECISION SUPPORT SYSTEMS: MATHEMATICAL SUPPORT
- 发表年份
- 2025
- 引用次数
- 2
摘要
The high dynamism of the development of social processes and phenomena determines the formation of a new system of the worldview of mankind, the modification (change) of the hierarchy of needs and values, challenges to the pace and quality of development. Solving complex problems associated with meeting the requirements of our time requires the use of innovative scientific approaches. Today, the use of modern intellectual technologies, such as neural networks, deep learning and artificial intelligence, is a prerequisite for the proactive development of all spheres of human activity: medicine, technology, business, environmental protection, education, transport and communication, etc. Thus, the intellectualization of technical and managerial systems can be considered one of the key foundations of the new paradigm of science and technology. The phrase "artificial intelligence systems" today is understandable to everyone. The context of this term is associated with such concepts as robotics, forecasting, processing of large information flows, expert systems, diagnostics, smart home or smart tools projects, cyberphysical space and cyberphysical systems, computer translation, etc. There is a positive dynamics of the development and implementation of artificial intelligence elements in most types of software: mobile applications, information systems, electronic devices, etc. This process of "intellectualization" allows us to talk about a gradual increase in the intelligence of modern computer systems capable of performing functions that are traditionally considered intellectual: understanding language, logical inference, using the accumulated knowledge, learning, pattern recognition, as well as learning and explaining their decisions. The monograph presents the scientific and methodological apparatus of intellectual assessment of the state of complex systems. During the study, the authors proposed: a methodological approach to assess the state of hierarchical systems using a metaheuristic algorithm; a technique for analyzing and predicting the state of multidimensional objects using a metaheuristic algorithm and a technique for increasing the reliability of estimating the state of an object. A separate section presents a comprehensive model for processing diverse data in intelligent decision support systems; method of processing different types of data in intelligent network and server architecture management systems, as well as a technique for increasing the efficiency of processing different types of data in intelligent network and server architecture management systems. The next section of this monograph proposes a set of methods for improving the efficiency of information processing in intelligent decision support systems. During the study, the authors proposed: a method for managing information flows in intelligent decision support systems using a population algorithm; method of evaluating the efficiency of processing different types of data in decision support systems; method of evaluation and forecasting in intelligent decision support systems. A separate section of the study proposes a scientific and methodological apparatus for processing various types of data in automated control systems. feasibility of using artificial intelligence theory for processing different types of data in automated control systems is substantiated; developed a method of data distribution in automated control systems; a model of the process of evaluating the processing of different types of data in automated command and control systems using expert information has been developed, and the methodology for setting up an information system for evaluating the process of processing different types of data in automated control systems under conditions of uncertainty has been improved. The next section of the monograph is devoted to intellectual methods for assessing the state of channels of unmanned aerial vehicles. In the course of the study, the authors
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