The Use of Artificial Intelligence in Automation of Planning and Operational Management of Organizational and Technical Systems in the COVID-19 Pandemic

2022 ◽  
pp. 187-201
Author(s):  
Oleg V. Balashov ◽  
Dmitriy S. Bukachev ◽  
Julia V. Gnezdova
Keyword(s):  
Artificial Intelligence ◽  
Operational Management ◽  
Technical Systems

Practical experience in the technical systems creating with the artificial intelligence elements

2021 ◽  
Vol 26 (jai2021.26(1)) ◽  
pp. 95-101
Author(s):  
Pisarenko V ◽  
◽  
Pisarenko J ◽  
Gulchak O ◽  
Chobotok T ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Extreme Environments ◽  
Practical Experience ◽  
Mine Safety ◽  
Technical Equipment ◽  
Rescue Work ◽  
Safety Control ◽  
Artificial Brain ◽  
Technical Systems ◽  
The Creation

The practical experience of solving scientific tasks using artificial intelligence technologies is presented. The authors offered their understanding of the term "artificial intelligence". Describes the development of the dept. №265 of Mathematical Problems of Applied Informatics V.M. Glushkov Institute of Cybernetics of the NAS of Ukraine in the creation of technical systems with elements of AI mainly to work in extreme environments. The purpose of the authors is to provide useful information to develop a strategy for the development of AI in the Ukraine. Some of these studies: monitoring the territory and management of land use technologies using remote sensing technologies from aircraft, spacecraft, unmanned aerial vehicles; monitoring the technical equipment of the underwater environment (technical means of searching for a sunken object of the submarine type for emergency operations are being developed); mine safety control (risk research during mining, creating robotic systems with elements of artificial intelligence for studying the conditions of work in the mine, warning accidents and emergency rescue work). The next direction is the diagnosis and treatment of addictive patients using the principles of therapeutic methods BiofeedBack. Attention is paid to the development of robotic technical systems with AI for servicing cosmic long missions. For this, theoretical studies have been conducted on the creation of a live brain mathematical model for its use in the development of the "artificial brain" of robots. The authors gave a list of tasks that can solve AI in programs for long-term space flights, technologies and systems that should develop in the first place to implement these tasks

scholarly journals Artificial intelligence in the synthesis of creative solutions

10.31519/1404 ◽  
2019 ◽  
Author(s):  
Александр Андрейчиков ◽  
Aleksandr Andreychikov ◽  
Ольга Андрейчикова ◽  
Olga Andreichicova
Keyword(s):  
Artificial Intelligence ◽  
Problem Solving ◽  
Present Article ◽  
High Efficiency ◽  
Knowledge Bases ◽  
Computing Technology ◽  
Creative Solutions ◽  
Computer Aided ◽  
Physical Effects ◽  
Technical Systems

Invention problem solving is connected to essential expenses of labour and time, which is spent on the procedures of search and ordering of necessary knowledge, on generation of probable vari-ants of projected systems, on the analysis of offered ideas and de-cisions and understanding perspectiveness of them. The present article outlines the results of the developments in the field of cre-ating computing technology of the synthesis of new engineering on the level of invention. The most attention is paid to problem of computer aided designing on initial stages, where synthesis of new on principal technical systems is carried out. Computer-aided con-struction of new technical system is based on using of data- and knowledge bases of physical effects and of technical decisions as well as different heuristic systematization procedures. The synthe-sis of principles of function of the technical new systems is carried out with using experts knowledge and requires the application of the artificial intelligence methods and the methods of the deci-sions making theory for invention's tasks. Considered approach has been used for synthesis of new technical systems of different functional purposes and had shown high efficiency in computer-aided construction.

scholarly journals Artificial intelligence and machine learning in dynamic cyber risk analytics at the edge

2020 ◽  
Vol 2 (11) ◽  
Author(s):  
Petar Radanliev ◽  
David De Roure ◽  
Rob Walton ◽  
Max Van Kleek ◽  
Rafael Mantilla Montalvo ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Academic Literature ◽  
The Past ◽  
Technological Advances ◽  
New Process ◽  
Technical Systems ◽  
Iot Devices ◽  
Cyber Risk

AbstractWe explore the potential and practical challenges in the use of artificial intelligence (AI) in cyber risk analytics, for improving organisational resilience and understanding cyber risk. The research is focused on identifying the role of AI in connected devices such as Internet of Things (IoT) devices. Through literature review, we identify wide ranging and creative methodologies for cyber analytics and explore the risks of deliberately influencing or disrupting behaviours to socio-technical systems. This resulted in the modelling of the connections and interdependencies between a system's edge components to both external and internal services and systems. We focus on proposals for models, infrastructures and frameworks of IoT systems found in both business reports and technical papers. We analyse this juxtaposition of related systems and technologies, in academic and industry papers published in the past 10 years. Then, we report the results of a qualitative empirical study that correlates the academic literature with key technological advances in connected devices. The work is based on grouping future and present techniques and presenting the results through a new conceptual framework. With the application of social science's grounded theory, the framework details a new process for a prototype of AI-enabled dynamic cyber risk analytics at the edge.

Improvement of the methods of operational management reliability of technical systems in agriculture

2020 ◽  
Vol 1 (1) ◽  
pp. 71-76
Author(s):  
А.Т. Lebedev ◽  
◽  
А.А. Seregin ◽  
А.G. Arzhenovskij ◽  
◽  
...  
Keyword(s):  
Operational Management ◽  
Technical Systems

Artificial intelligence and human rights: Between law and ethics

2020 ◽  
pp. 1023263X2098156
Author(s):  
Giovanni Sartor
Keyword(s):  
Artificial Intelligence ◽  
Human Rights ◽  
Social Values ◽  
Human Action ◽  
Fundamental Rights ◽  
Legal Rules ◽  
Law And Ethics ◽  
Dialectical Tension ◽  
Technical Systems ◽  
Normative Issues

The ethics and law of AI address the same domain, namely, the present and future impacts of AI on individuals, society, and the environment. Both are meant to provide normative guidance, proposing rules and values on which basis to govern human action and determine the constrains, structures and functions of AI-enabled socio-technical systems. This article examines the way in which AI is addressed by ethical and legal rules, principles and arguments. It considers the extent to which the demands of law and ethics may pull in different directions or rather overlap, and examines how they can be coordinated, while remaining in a productive dialectical tension. In particular, it argues that human/fundamental rights and social values are central to both ethics and law. Even though can be framed in different ways, they can provide a useful normative reference for linking ethics and law in addressing the normative issues arising in connection with AI.

scholarly journals EVOLUTIONAL METHODS FOR CREATING ARTIFICIAL INTELLIGENCE OF ROBOTIC TECHNICAL SYSTEMS

2018 ◽  
Vol 16 (2) ◽  
pp. 148-152 ◽  
Author(s):  
Askhat I. Diveev ◽  
Sabit Ibadulla
Keyword(s):  
Artificial Intelligence ◽  
Genetic Programming ◽  
Control Systems ◽  
Intelligent Control ◽  
Symbolic Regression ◽  
Robotic Systems ◽  
Basic Solution ◽  
Intelligent Control Systems ◽  
Intellectual Control ◽  
Technical Systems

This paper considers evolutionary methods of symbolic regression for the creation of artificial intelligence of robotic systems. Methods of symbolic regression are reviewed and the features of their application to the solution of the problem of synthesis of control of robotic systems are indicated. The measure of the complexity of artificial intelligence is determined and the advantage of using the principle of small variations of the basic solution is shown, while creating intelligent control systems. A method of variational genetic programming is described and an example of its use for the synthesis of intellectual control is given.

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