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ДИДАКТИЧЕСКИЕ ПРИНЦИПЫ «ОБУЧЕНИЯ» НЕЙРОННЫХ СЕТЕЙ НА ПРИМЕРЕ МОДЕЛИРОВАНИЯ ЭКСПЕРТНОЙ СИСТЕМЫ ФОРМИРОВАНИЯ КАДРОВОГО РЕЗЕРВА ОРГАНИЗАЦИИ

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Title: ДИДАКТИЧЕСКИЕ ПРИНЦИПЫ «ОБУЧЕНИЯ» НЕЙРОННЫХ СЕТЕЙ НА ПРИМЕРЕ МОДЕЛИРОВАНИЯ ЭКСПЕРТНОЙ СИСТЕМЫ ФОРМИРОВАНИЯ КАДРОВОГО РЕЗЕРВА ОРГАНИЗАЦИИ
Publisher Information: Дидактика математики: проблемы и исследования, 2022.
Publication Year: 2022
Subject Terms: искусственный интеллект, didactic principles of learning, learning algorithm, экспертная система, neural network, 4. Education, алгоритм обучения, кадровый резерв, дидактические принципы обучения, artificial intelligence, personnel reserve, нейронная сеть, expert system
Description: The article is devoted to the actual problem of using the didactic principles of teaching mathematics and mathematical modeling, used in the educational process of higher education, to «train» neural networks on the example of an information-analytical expert system for the selection and management of an organization's personnel. Personnel is an important component of any organization, an element of its complex system. And, the more complex this system is, the more attention each element requires from the management of its potential. The presence of a successful personnel management system in the organization is an important goal of the development of any organization. The first step towards this goal is the development of a model of a personnel management system. The main functions of personnel management systems are often reduced to the selection of qualified specialists. The functioning of these systems should be carried out using modern information technologies and artificial intelligence systems. The most promising technology in this context is the use of neural networks "trained" for selection in accordance with the developed algorithm, and expert systems designed on their basis. All components of the "learning" system are built based on didactic principles transferred from the field of teaching mathematics and informatics to the field of developing elements of artificial intelligence. A structural-functional model of an information-analytical system is presented, an algorithm for «learning» a neural network using the Hebb learning method, as well as specialized software for processing and evaluating the results of «learning» is described.
Статья посвящена актуальной проблеме использования дидактических принципов обучения математике и математическому моделированию, применяемых в образовательном процессе высшей школы, для «обучения» нейронных сетей на примере информационно-аналитической экспертной системы подбора и управления персоналом организации. Представлены структурно-функциональная модель информационно-аналитической системы, описан алгоритм «обучения» нейронной сети с использованием метода обучения Хебба, а также специализированное программное обеспечение обработки и оценки результатов «обучения».
Document Type: Research
DOI: 10.24412/2079-9152-2022-55-7-16
Rights: CC BY
Accession Number: edsair.doi...........7f1e8d35fa4b9a2df694017714d13c76
Database: OpenAIRE
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  Data: ДИДАКТИЧЕСКИЕ ПРИНЦИПЫ «ОБУЧЕНИЯ» НЕЙРОННЫХ СЕТЕЙ НА ПРИМЕРЕ МОДЕЛИРОВАНИЯ ЭКСПЕРТНОЙ СИСТЕМЫ ФОРМИРОВАНИЯ КАДРОВОГО РЕЗЕРВА ОРГАНИЗАЦИИ
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  Data: <searchLink fieldCode="DE" term="%22искусственный+интеллект%22">искусственный интеллект</searchLink><br /><searchLink fieldCode="DE" term="%22didactic+principles+of+learning%22">didactic principles of learning</searchLink><br /><searchLink fieldCode="DE" term="%22learning+algorithm%22">learning algorithm</searchLink><br /><searchLink fieldCode="DE" term="%22экспертная+система%22">экспертная система</searchLink><br /><searchLink fieldCode="DE" term="%22neural+network%22">neural network</searchLink><br /><searchLink fieldCode="DE" term="%224%2E+Education%22">4. Education</searchLink><br /><searchLink fieldCode="DE" term="%22алгоритм+обучения%22">алгоритм обучения</searchLink><br /><searchLink fieldCode="DE" term="%22кадровый+резерв%22">кадровый резерв</searchLink><br /><searchLink fieldCode="DE" term="%22дидактические+принципы+обучения%22">дидактические принципы обучения</searchLink><br /><searchLink fieldCode="DE" term="%22artificial+intelligence%22">artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22personnel+reserve%22">personnel reserve</searchLink><br /><searchLink fieldCode="DE" term="%22нейронная+сеть%22">нейронная сеть</searchLink><br /><searchLink fieldCode="DE" term="%22expert+system%22">expert system</searchLink>
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  Data: The article is devoted to the actual problem of using the didactic principles of teaching mathematics and mathematical modeling, used in the educational process of higher education, to «train» neural networks on the example of an information-analytical expert system for the selection and management of an organization's personnel. Personnel is an important component of any organization, an element of its complex system. And, the more complex this system is, the more attention each element requires from the management of its potential. The presence of a successful personnel management system in the organization is an important goal of the development of any organization. The first step towards this goal is the development of a model of a personnel management system. The main functions of personnel management systems are often reduced to the selection of qualified specialists. The functioning of these systems should be carried out using modern information technologies and artificial intelligence systems. The most promising technology in this context is the use of neural networks "trained" for selection in accordance with the developed algorithm, and expert systems designed on their basis. All components of the "learning" system are built based on didactic principles transferred from the field of teaching mathematics and informatics to the field of developing elements of artificial intelligence. A structural-functional model of an information-analytical system is presented, an algorithm for «learning» a neural network using the Hebb learning method, as well as specialized software for processing and evaluating the results of «learning» is described.<br />Статья посвящена актуальной проблеме использования дидактических принципов обучения математике и математическому моделированию, применяемых в образовательном процессе высшей школы, для «обучения» нейронных сетей на примере информационно-аналитической экспертной системы подбора и управления персоналом организации. Представлены структурно-функциональная модель информационно-аналитической системы, описан алгоритм «обучения» нейронной сети с использованием метода обучения Хебба, а также специализированное программное обеспечение обработки и оценки результатов «обучения».
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      – SubjectFull: искусственный интеллект
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      – SubjectFull: didactic principles of learning
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      – SubjectFull: дидактические принципы обучения
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      – TitleFull: ДИДАКТИЧЕСКИЕ ПРИНЦИПЫ «ОБУЧЕНИЯ» НЕЙРОННЫХ СЕТЕЙ НА ПРИМЕРЕ МОДЕЛИРОВАНИЯ ЭКСПЕРТНОЙ СИСТЕМЫ ФОРМИРОВАНИЯ КАДРОВОГО РЕЗЕРВА ОРГАНИЗАЦИИ
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