制定提高组织和技术系统决策效率的方法

Q3 Mathematics
Salman Rasheed Owaid, Yurii Zhuravskyi, Oleksandr Lytvynenko, A. Veretnov, D. Sokolovskyi, Ganna Plekhova, Volodymyr Hrinkov, Tetiana Pluhina, Serhii Neronov, Oleksii Dovbenko
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引用次数: 0

摘要

研究对象是组织和技术系统。研究对象是组织和技术系统管理问题的决策过程。提出了一种利用人工智能提高组织和技术系统决策效率的方法。该研究以巨型犰狳群算法为基础,寻找有关组织和技术系统状态的解决方案。巨型犰狳群(GAA)使用不断演化的人工神经网络进行训练,并使用先进的遗传算法来选择最佳的 GAA。该方法的操作顺序如下- 输入初始数据;- 在搜索平面上设置蚁群;- 对蚁群中的蚁群进行编号;- 确定蚁群的初始速度;- 初步评估蚁群的搜索区域;- 对蚁群的食物来源进行分类;- 对最佳蚁群个体进行分类;- 蚁群对白蚁冢进行攻击;- 用 GAA 挖掘白蚁冢;- 更新 GAA 的位置;- 检查是否存在 GAA 的捕食者;- 逃脱并对抗 GAA 的捕食者;- 检查停止标准;- 训练 GAA 知识库;- 确定智能决策支持系统所需的计算资源数量。所提方法的独创性在于,考虑到初始数据的不确定性、全局和局部搜索的先进程序以及组织和技术系统状态数据的噪声程度,设置了 GAA。该方法可以利用额外的先进程序将数据处理效率提高 14-19%。建议使用该方法来解决复杂和动态过程的评估问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
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来源期刊
Eastern-European Journal of Enterprise Technologies
Eastern-European Journal of Enterprise Technologies Mathematics-Applied Mathematics
CiteScore
2.00
自引率
0.00%
发文量
369
审稿时长
6 weeks
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.
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