{"title":"制定提高组织和技术系统决策效率的方法","authors":"Salman Rasheed Owaid, Yurii Zhuravskyi, Oleksandr Lytvynenko, A. Veretnov, D. Sokolovskyi, Ganna Plekhova, Volodymyr Hrinkov, Tetiana Pluhina, Serhii Neronov, Oleksii Dovbenko","doi":"10.15587/1729-4061.2024.298568","DOIUrl":null,"url":null,"abstract":"The object of the study is organizational and technical systems. The subject of the study is the decision-making process in the problems of management of organizational and technical systems. A method of increasing the efficiency of decision-making in organizational and technical systems using artificial intelligence is proposed. The research is based on the giant armadillo swarm algorithm to find a solution regarding the state of organizational and technical systems. Giant armadillo agents (GAA) are trained using evolving artificial neural networks, and an advanced genetic algorithm is used to select the best GAA. The method has the following sequence of actions:\n– input of initial data;\n– setting GAA on the search plane;\n– numbering GAA in the swarm;\n– determining the initial velocity of GAA;\n– preliminary evaluation of the GAA search area;\n– classification of food sources for GAA;\n– sorting the best GAA individuals;\n– attack on termite mounds by GAA;\n– digging termite mounds by GAA;\n– updating GAA positions;\n– checking for the presence of a GAA predator;\n– escape and fight against GAA predators;\n– checking the stop criterion;\n– training GAA knowledge bases;\n– determining the amount of necessary computing resources of the intelligent decision support system.\nThe originality of the proposed method lies in setting GAA taking into account the uncertainty of the initial data, advanced procedures of global and local search taking into account the noise degree of data on the state of organizational and technical systems. The method makes it possible to increase the efficiency of data processing at the level of 14–19 % using additional advanced procedures. The proposed method should be used to solve the problems of evaluating complex and dynamic processes","PeriodicalId":11433,"journal":{"name":"Eastern-European Journal of Enterprise Technologies","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Development of a method of increasing the efficiency of decision-making in organizational and technical systems\",\"authors\":\"Salman Rasheed Owaid, Yurii Zhuravskyi, Oleksandr Lytvynenko, A. Veretnov, D. Sokolovskyi, Ganna Plekhova, Volodymyr Hrinkov, Tetiana Pluhina, Serhii Neronov, Oleksii Dovbenko\",\"doi\":\"10.15587/1729-4061.2024.298568\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The object of the study is organizational and technical systems. The subject of the study is the decision-making process in the problems of management of organizational and technical systems. A method of increasing the efficiency of decision-making in organizational and technical systems using artificial intelligence is proposed. The research is based on the giant armadillo swarm algorithm to find a solution regarding the state of organizational and technical systems. Giant armadillo agents (GAA) are trained using evolving artificial neural networks, and an advanced genetic algorithm is used to select the best GAA. The method has the following sequence of actions:\\n– input of initial data;\\n– setting GAA on the search plane;\\n– numbering GAA in the swarm;\\n– determining the initial velocity of GAA;\\n– preliminary evaluation of the GAA search area;\\n– classification of food sources for GAA;\\n– sorting the best GAA individuals;\\n– attack on termite mounds by GAA;\\n– digging termite mounds by GAA;\\n– updating GAA positions;\\n– checking for the presence of a GAA predator;\\n– escape and fight against GAA predators;\\n– checking the stop criterion;\\n– training GAA knowledge bases;\\n– determining the amount of necessary computing resources of the intelligent decision support system.\\nThe originality of the proposed method lies in setting GAA taking into account the uncertainty of the initial data, advanced procedures of global and local search taking into account the noise degree of data on the state of organizational and technical systems. The method makes it possible to increase the efficiency of data processing at the level of 14–19 % using additional advanced procedures. 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Development of a method of increasing the efficiency of decision-making in organizational and technical systems
The object of the study is organizational and technical systems. The subject of the study is the decision-making process in the problems of management of organizational and technical systems. A method of increasing the efficiency of decision-making in organizational and technical systems using artificial intelligence is proposed. The research is based on the giant armadillo swarm algorithm to find a solution regarding the state of organizational and technical systems. Giant armadillo agents (GAA) are trained using evolving artificial neural networks, and an advanced genetic algorithm is used to select the best GAA. The method has the following sequence of actions:
– input of initial data;
– setting GAA on the search plane;
– numbering GAA in the swarm;
– determining the initial velocity of GAA;
– preliminary evaluation of the GAA search area;
– classification of food sources for GAA;
– sorting the best GAA individuals;
– attack on termite mounds by GAA;
– digging termite mounds by GAA;
– updating GAA positions;
– checking for the presence of a GAA predator;
– escape and fight against GAA predators;
– checking the stop criterion;
– training GAA knowledge bases;
– determining the amount of necessary computing resources of the intelligent decision support system.
The originality of the proposed method lies in setting GAA taking into account the uncertainty of the initial data, advanced procedures of global and local search taking into account the noise degree of data on the state of organizational and technical systems. The method makes it possible to increase the efficiency of data processing at the level of 14–19 % using additional advanced procedures. The proposed method should be used to solve the problems of evaluating complex and dynamic processes
期刊介绍:
Terminology used in the title of the "East European Journal of Enterprise Technologies" - "enterprise technologies" should be read as "industrial technologies". "Eastern-European Journal of Enterprise Technologies" publishes all those best ideas from the science, which can be introduced in the industry. Since, obtaining the high-quality, competitive industrial products is based on introducing high technologies from various independent spheres of scientific researches, but united by a common end result - a finished high-technology product. Among these scientific spheres, there are engineering, power engineering and energy saving, technologies of inorganic and organic substances and materials science, information technologies and control systems. Publishing scientific papers in these directions are the main development "vectors" of the "Eastern-European Journal of Enterprise Technologies". Since, these are those directions of scientific researches, the results of which can be directly used in modern industrial production: space and aircraft industry, instrument-making industry, mechanical engineering, power engineering, chemical industry and metallurgy.