Вы здесь ▸ Обсуждение ▸
Мои публикации
Публикации: статьи в журналах и сборниках конференций, доклады, презентации, отчеты, авторские свидетельства.
Иванов В.К., Семенова Т.И.
Обзор основных направлений интеллектуализации планирования экономического развития предприятия Proceedings Article
In: Междисциплинарные исследования экономических систем. Материалы II Всероссийской научно-практической конференции. Под редакцией А.Н. Бородулина. Тверь, 2022. С. 63-67., pp. 63-67, ТвГТУ, 2022.
Abstract | Links | BibTeX | Метки: enterprise development, fuzzy logic, fuzzy system, genetic algorithm, intellectualization, neural network, operational planning, strategic planning, генетический алгоритм, интеллектуализация, нейронная сеть, нечёткая логика, оперативное планирование, развитие предприятия, стратегическое планирование
@inproceedings{nokey,
title = {Обзор основных направлений интеллектуализации планирования экономического развития предприятия},
author = {Иванов В.К. and Семенова Т.И.},
url = {https://disk.yandex.ru/i/_q3GESbD7v2cIg},
year = {2022},
date = {2022-05-27},
urldate = {2022-05-27},
booktitle = {Междисциплинарные исследования экономических систем. Материалы II Всероссийской научно-практической конференции. Под редакцией А.Н. Бородулина. Тверь, 2022. С. 63-67.},
pages = {63-67},
publisher = {ТвГТУ},
abstract = {В статье представлен краткий обзор основных направлений и подходов к интеллектуализации систем планирования экономического развития предприятия. Обзор подготовлен на основе публикаций российских ученых и специалистов с целью дать системное представление о ландшафте применения методов искусственного интеллекта в планировании – одной из важных производственных областей. В условиях экономической среды, связанных с неполнотой, неточностью и нестабильностью информации и ее трактовок, часто возникает невозможность однозначного выбора эффективных вариантов принятия решений в ходе планирования производства. Одним из способов сокращения этой неопределенности является применение интеллектуальных вычислительных процедур принятия решений.
Main Directions of Enterprise Economic Development Planning Intellectualization
This article presents descriptions of a number of approaches to the intellectualization of enterprise economic development planning systems. The review has been prepared on the basis of publications by Russian scientists and specialists in order to give a systematic idea of the landscape of applying artificial intelligence methods in planning, one of the important production areas. In the conditions of the economic environment associated with incompleteness, inaccuracy and instability of information and its interpretation, it often becomes impossible to unambiguously choose effective decision-making options in the course of production planning. One way to reduce this uncertainty is to use intelligent computational decision-making procedures.},
keywords = {enterprise development, fuzzy logic, fuzzy system, genetic algorithm, intellectualization, neural network, operational planning, strategic planning, генетический алгоритм, интеллектуализация, нейронная сеть, нечёткая логика, оперативное планирование, развитие предприятия, стратегическое планирование},
pubstate = {published},
tppubtype = {inproceedings}
}
В статье представлен краткий обзор основных направлений и подходов к интеллектуализации систем планирования экономического развития предприятия. Обзор подготовлен на основе публикаций российских ученых и специалистов с целью дать системное представление о ландшафте применения методов искусственного интеллекта в планировании – одной из важных производственных областей. В условиях экономической среды, связанных с неполнотой, неточностью и нестабильностью информации и ее трактовок, часто возникает невозможность однозначного выбора эффективных вариантов принятия решений в ходе планирования производства. Одним из способов сокращения этой неопределенности является применение интеллектуальных вычислительных процедур принятия решений.
Main Directions of Enterprise Economic Development Planning Intellectualization
This article presents descriptions of a number of approaches to the intellectualization of enterprise economic development planning systems. The review has been prepared on the basis of publications by Russian scientists and specialists in order to give a systematic idea of the landscape of applying artificial intelligence methods in planning, one of the important production areas. In the conditions of the economic environment associated with incompleteness, inaccuracy and instability of information and its interpretation, it often becomes impossible to unambiguously choose effective decision-making options in the course of production planning. One way to reduce this uncertainty is to use intelligent computational decision-making procedures.
Main Directions of Enterprise Economic Development Planning Intellectualization
This article presents descriptions of a number of approaches to the intellectualization of enterprise economic development planning systems. The review has been prepared on the basis of publications by Russian scientists and specialists in order to give a systematic idea of the landscape of applying artificial intelligence methods in planning, one of the important production areas. In the conditions of the economic environment associated with incompleteness, inaccuracy and instability of information and its interpretation, it often becomes impossible to unambiguously choose effective decision-making options in the course of production planning. One way to reduce this uncertainty is to use intelligent computational decision-making procedures.
Иванов В.К., Семенова Т.И.
О некоторых подходах к решению задач производственного планирования с использованием методов искусственного интеллекта Proceedings Article
In: Междисциплинарные исследования экономических систем. Материалы II Всероссийской научно-практической конференции. Под редакцией А.Н. Бородулина. Тверь, 2022. С. 129-136., pp. 129-136, ТвГТУ, 2022.
Abstract | Links | BibTeX | Метки: enterprise development, fuzzy logic, fuzzy system, genetic algorithm, intellectualization, neural network, operational planning, strategic planning, генетический алгоритм, интеллектуализация, нейронная сеть, нечёткая логика, оперативное планирование, развитие предприятия, стратегическое планирование
@inproceedings{nokey,
title = {О некоторых подходах к решению задач производственного планирования с использованием методов искусственного интеллекта},
author = {Иванов В.К. and Семенова Т.И.},
url = {https://disk.yandex.ru/i/gWXfVueaPe_-AA},
year = {2022},
date = {2022-05-27},
urldate = {2022-05-27},
booktitle = {Междисциплинарные исследования экономических систем. Материалы II Всероссийской научно-практической конференции. Под редакцией А.Н. Бородулина. Тверь, 2022. С. 129-136.},
pages = {129-136},
publisher = {ТвГТУ},
abstract = {Статья содержит описание ряда подходов к решению задач производственного планирования. Рассматриваются задачи оптимизации системы сбалансированных показателей, оперативно-календарного планирования производства, планирования загрузки оборудования и потребностей в материалах. Отмечается, что при появлении случайных событий, влияющих на процесс производства, применение методов искусственного интеллекта позволяет точнее учитывать изменения или вносить корректировки в исходные данные тем самым существенно сокращать время планирования.
On Some Approaches to Enterprise Economic Development Planning Intellectualization
This article presents descriptions of a number of approaches to the intellectualization of enterprise economic development planning systems. The review has been prepared on the basis of publications by Russian scientists and specialists in order to give a systematic idea of the landscape of applying artificial intelligence methods in planning, one of the important production areas. In the conditions of the economic environment associated with incompleteness, inaccuracy and instability of information and its interpretation, it often becomes impossible to unambiguously choose effective decision-making options in the course of production planning. One way to reduce this uncertainty is to use intelligent computational decision-making procedures.},
keywords = {enterprise development, fuzzy logic, fuzzy system, genetic algorithm, intellectualization, neural network, operational planning, strategic planning, генетический алгоритм, интеллектуализация, нейронная сеть, нечёткая логика, оперативное планирование, развитие предприятия, стратегическое планирование},
pubstate = {published},
tppubtype = {inproceedings}
}
Статья содержит описание ряда подходов к решению задач производственного планирования. Рассматриваются задачи оптимизации системы сбалансированных показателей, оперативно-календарного планирования производства, планирования загрузки оборудования и потребностей в материалах. Отмечается, что при появлении случайных событий, влияющих на процесс производства, применение методов искусственного интеллекта позволяет точнее учитывать изменения или вносить корректировки в исходные данные тем самым существенно сокращать время планирования.
On Some Approaches to Enterprise Economic Development Planning Intellectualization
This article presents descriptions of a number of approaches to the intellectualization of enterprise economic development planning systems. The review has been prepared on the basis of publications by Russian scientists and specialists in order to give a systematic idea of the landscape of applying artificial intelligence methods in planning, one of the important production areas. In the conditions of the economic environment associated with incompleteness, inaccuracy and instability of information and its interpretation, it often becomes impossible to unambiguously choose effective decision-making options in the course of production planning. One way to reduce this uncertainty is to use intelligent computational decision-making procedures.
On Some Approaches to Enterprise Economic Development Planning Intellectualization
This article presents descriptions of a number of approaches to the intellectualization of enterprise economic development planning systems. The review has been prepared on the basis of publications by Russian scientists and specialists in order to give a systematic idea of the landscape of applying artificial intelligence methods in planning, one of the important production areas. In the conditions of the economic environment associated with incompleteness, inaccuracy and instability of information and its interpretation, it often becomes impossible to unambiguously choose effective decision-making options in the course of production planning. One way to reduce this uncertainty is to use intelligent computational decision-making procedures.
Ivanov V.K., Palyukh B.V., Sotnikov A.N.
Additive Criteria to Evaluate Relevance of Innovative Objects in Data Warehouse Journal Article
In: Lobachevskii Journal of Mathematics, vol. 41, no. 12, pp. 2535–2541, 2020, ISSN: 1995-0802.
Abstract | Links | BibTeX | Altmetric | Метки: additive criterion, additive independence, data warehouse, genetic algorithm, innovation, innovation index, partial criterion, search query, utility function
@article{V.K.Ivanov12,
title = {Additive Criteria to Evaluate Relevance of Innovative Objects in Data Warehouse},
author = {Ivanov V.K. and Palyukh B.V. and Sotnikov A.N.},
url = {https://disk.yandex.ru/i/atOSEIgY7P6F_Q},
doi = {10.1134/S199508022012015X },
issn = {1995-0802},
year = {2020},
date = {2020-11-30},
urldate = {2020-11-30},
journal = {Lobachevskii Journal of Mathematics},
volume = {41},
number = {12},
pages = {2535–2541},
abstract = {The article discusses some aspects of warehousing object descriptions having significant innovation potential. The procedure for selecting such descriptions consists of two consecutive phases. The first phase involves generating effective search queries with a special genetic algorithm (GAP). In the second phase, the model developed determines the index of innovativeness of an object archetype. Meanwhile the values of additive selection criteria are calculated. In the former case, the criterion is a fitness function of GAP. In the latter case, the criterion is the index of innovativeness. The purpose of the article is to justify the additive criterion applicability for calculating the value of the GAP fitness function. The article describes general conditions of applying additive evaluation criteria and shows how these conditions are met for the GAP fitness function. The analysis of the partial criteria gives grounds to assert their additive independence and, therefore, the correct use of additive n-dimensional utility function. Some additional reasons for applying additive criterion are also given. In general, the article proposes a unified approach to generating global assessment criteria and the relevance of unified formal structure is shown. The models presented in the article are used to develop adequate computational algorithms for the developed data warehouse support system. },
keywords = {additive criterion, additive independence, data warehouse, genetic algorithm, innovation, innovation index, partial criterion, search query, utility function},
pubstate = {published},
tppubtype = {article}
}
The article discusses some aspects of warehousing object descriptions having significant innovation potential. The procedure for selecting such descriptions consists of two consecutive phases. The first phase involves generating effective search queries with a special genetic algorithm (GAP). In the second phase, the model developed determines the index of innovativeness of an object archetype. Meanwhile the values of additive selection criteria are calculated. In the former case, the criterion is a fitness function of GAP. In the latter case, the criterion is the index of innovativeness. The purpose of the article is to justify the additive criterion applicability for calculating the value of the GAP fitness function. The article describes general conditions of applying additive evaluation criteria and shows how these conditions are met for the GAP fitness function. The analysis of the partial criteria gives grounds to assert their additive independence and, therefore, the correct use of additive n-dimensional utility function. Some additional reasons for applying additive criterion are also given. In general, the article proposes a unified approach to generating global assessment criteria and the relevance of unified formal structure is shown. The models presented in the article are used to develop adequate computational algorithms for the developed data warehouse support system.
Ivanov V.K., Palyukh B.V., Sotnikov A.N.
Features of Data Warehouse Support Based on a Search Agent and an Evolutionary Model for Innovation Information Selection Proceedings Article
In: Advances in Intelligent Systems and Computing. Proceedings of the Fourth International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’19) , pp. 120-130, Springer, Cham, 2020, ISBN: 978-30-3050-096-2.
Abstract | Links | BibTeX | Altmetric | Метки: data warehouse, genetic algorithm, innovation index, Innovativeness, Intelligent agent, novelty, relevance, subject search
@inproceedings{V.K.2020,
title = {Features of Data Warehouse Support Based on a Search Agent and an Evolutionary Model for Innovation Information Selection},
author = {Ivanov V.K. and Palyukh B.V. and Sotnikov A.N.},
url = {https://disk.yandex.ru/i/FT7JLsQmXPIMgQ
https://doi.org/10.1007/978-3-030-50097-9_13},
doi = {10.1007/978-3-030-50097-9_13},
isbn = {978-30-3050-096-2},
year = {2020},
date = {2020-00-01},
urldate = {2020-00-01},
booktitle = {Advances in Intelligent Systems and Computing. Proceedings of the Fourth International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’19) },
volume = {1156},
pages = {120-130},
publisher = {Springer, Cham},
abstract = {Innovations are the key factor of the competitiveness of any modern business. This paper gives the systematized results of investigations on the data warehouse technology with an automatic data-replenishment from heterogeneous sources. The data warehouse is suggested to contain information about objects having a significant innovative potential. The selection mechanism for such information is based on quantitative evaluation of the objects innovativeness, in particular their technological novelty and relevance for them. The article presents the general architecture of the data warehouse, describes innovativeness indicators, considers Theory of Evidence application for processing incomplete and fuzzy information, defines basic ideas of measurement processing procedure to compute probabilistic values of innovativeness components, summarizes using evolutional approach in forming the linguistic model of object archetype, gives information about an experimental check if the model developed is adequate. The results of these investigations can be used for business planning, forecasting technological development, investment project expertise.
Ivanov, V.K., Palyukh, B.V., Sotnikov, A.N. (2020). Features of Data Warehouse Support Based on a Search Agent and an Evolutionary Model for Innovation Information Selection. In: Kovalev, S., Tarassov, V., Snasel, V., Sukhanov, A. (eds) Proceedings of the Fourth International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’19). IITI 2019. Advances in Intelligent Systems and Computing, vol 1156. Springer, Cham. https://doi.org/10.1007/978-3-030-50097-9_13 (Scopus)},
keywords = {data warehouse, genetic algorithm, innovation index, Innovativeness, Intelligent agent, novelty, relevance, subject search},
pubstate = {published},
tppubtype = {inproceedings}
}
Innovations are the key factor of the competitiveness of any modern business. This paper gives the systematized results of investigations on the data warehouse technology with an automatic data-replenishment from heterogeneous sources. The data warehouse is suggested to contain information about objects having a significant innovative potential. The selection mechanism for such information is based on quantitative evaluation of the objects innovativeness, in particular their technological novelty and relevance for them. The article presents the general architecture of the data warehouse, describes innovativeness indicators, considers Theory of Evidence application for processing incomplete and fuzzy information, defines basic ideas of measurement processing procedure to compute probabilistic values of innovativeness components, summarizes using evolutional approach in forming the linguistic model of object archetype, gives information about an experimental check if the model developed is adequate. The results of these investigations can be used for business planning, forecasting technological development, investment project expertise.
Ivanov, V.K., Palyukh, B.V., Sotnikov, A.N. (2020). Features of Data Warehouse Support Based on a Search Agent and an Evolutionary Model for Innovation Information Selection. In: Kovalev, S., Tarassov, V., Snasel, V., Sukhanov, A. (eds) Proceedings of the Fourth International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’19). IITI 2019. Advances in Intelligent Systems and Computing, vol 1156. Springer, Cham. https://doi.org/10.1007/978-3-030-50097-9_13 (Scopus)
Ivanov, V.K., Palyukh, B.V., Sotnikov, A.N. (2020). Features of Data Warehouse Support Based on a Search Agent and an Evolutionary Model for Innovation Information Selection. In: Kovalev, S., Tarassov, V., Snasel, V., Sukhanov, A. (eds) Proceedings of the Fourth International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’19). IITI 2019. Advances in Intelligent Systems and Computing, vol 1156. Springer, Cham. https://doi.org/10.1007/978-3-030-50097-9_13 (Scopus)
Иванов В.К., Думина Д.С., Семенов Н.А.
К вопросу о реализации генетического алгоритма для решения задач поиска тематической информации в интернете Proceedings Article
In: Международный научно-технический конгресс «Интеллектуальные системы и информационные технологии - 2020». «IS&IT’20». Труды конгресса. Секция 1 «Эволюционное моделирование», pp. 17-28, Таганрог, 2020, ISBN: 978-56-0436-899-2.
Abstract | Links | BibTeX | Метки: additive function, fitness function, genetic algorithm, relevance, search query, weight factor, аддитивный критерий, весовой коэффициент, генетический алгоритм, поисковый запрос, релевантность, фитнес-функция
@inproceedings{V.K.Ivanov13,
title = {К вопросу о реализации генетического алгоритма для решения задач поиска тематической информации в интернете},
author = {Иванов В.К. and Думина Д.С. and Семенов Н.А.},
url = {https://disk.yandex.ru/i/wYjDcfkpmMg4Zw},
isbn = {978-56-0436-899-2},
year = {2020},
date = {2020-00-01},
urldate = {2020-00-01},
booktitle = {Международный научно-технический конгресс «Интеллектуальные системы и информационные технологии - 2020». «IS&IT’20». Труды конгресса. Секция 1 «Эволюционное моделирование»},
volume = {1},
pages = {17-28},
publisher = {Таганрог},
abstract = {В статье представлено возможное решение задачи выбора способа аналитического определения весовых коэффициентов для аддитивной фитнес-функции генетического алгоритма. Этот генетический алгоритм является основой эволюционного процесса, формирующего в поисковой системе устойчивую и эффективную популяцию запросов для получения высоко релевантных результатов. Приведено формальное описание фитнес-функции алгоритма, которая представляет собой взвешенную сумму трех неоднородных критериев.
V.K. Ivanov, D.S. Dumina, N.A. Semenov. On the Impletmentation of a Genetic Algorithm for Solving Problems of Searching for Thematic Information on the Internet
A possible solution to the problem of choosing a method for the weight factors analytical determination for the genetic algorithm additive fitness function is presented. This genetic algorithm is the evolutionary process basis, which forms a stable and effective queries population in the search engine to obtain highly relevant results. A fitness function formal description, which is a weighted sum of three heterogeneous criteria is given.},
keywords = {additive function, fitness function, genetic algorithm, relevance, search query, weight factor, аддитивный критерий, весовой коэффициент, генетический алгоритм, поисковый запрос, релевантность, фитнес-функция},
pubstate = {published},
tppubtype = {inproceedings}
}
В статье представлено возможное решение задачи выбора способа аналитического определения весовых коэффициентов для аддитивной фитнес-функции генетического алгоритма. Этот генетический алгоритм является основой эволюционного процесса, формирующего в поисковой системе устойчивую и эффективную популяцию запросов для получения высоко релевантных результатов. Приведено формальное описание фитнес-функции алгоритма, которая представляет собой взвешенную сумму трех неоднородных критериев.
V.K. Ivanov, D.S. Dumina, N.A. Semenov. On the Impletmentation of a Genetic Algorithm for Solving Problems of Searching for Thematic Information on the Internet
A possible solution to the problem of choosing a method for the weight factors analytical determination for the genetic algorithm additive fitness function is presented. This genetic algorithm is the evolutionary process basis, which forms a stable and effective queries population in the search engine to obtain highly relevant results. A fitness function formal description, which is a weighted sum of three heterogeneous criteria is given.
V.K. Ivanov, D.S. Dumina, N.A. Semenov. On the Impletmentation of a Genetic Algorithm for Solving Problems of Searching for Thematic Information on the Internet
A possible solution to the problem of choosing a method for the weight factors analytical determination for the genetic algorithm additive fitness function is presented. This genetic algorithm is the evolutionary process basis, which forms a stable and effective queries population in the search engine to obtain highly relevant results. A fitness function formal description, which is a weighted sum of three heterogeneous criteria is given.
Ivanov V.K., Palyukh B.V., Sotnikov A.N.
Conformance Evaluation of Genetic Algorithm for Evolutionary Area Search of Canonical Model Journal Article
In: Lobachevskii Journal of Mathematics, vol. 40, no. 11, pp. 1799–1808, 2019, ISSN: 1995-0802.
Abstract | Links | BibTeX | Altmetric | Метки: coding, crossover, defining length, fitness function, genetic algorithm, genotype, Holland’s schema theorem, innovation index, order, query, scheme, subject search
@article{nokey,
title = {Conformance Evaluation of Genetic Algorithm for Evolutionary Area Search of Canonical Model},
author = {Ivanov V.K. and Palyukh B.V. and Sotnikov A.N.},
url = {https://disk.yandex.ru/i/Q42TFMNFM5XGlg},
doi = {10.1134/S1995080219110155},
issn = {1995-0802},
year = {2019},
date = {2019-11-30},
urldate = {2019-11-30},
journal = {Lobachevskii Journal of Mathematics},
volume = {40},
number = {11},
pages = {1799–1808},
publisher = {Pleiades Publishing, Ltd.},
abstract = {The theory and practice of genetic algorithms is largely based on the Schema Theorem. It was formulated for a canonical genetic algorithm and proves its ability to generate a sufficient number of effective schemata of individuals. Genetic algorithms to solve specific problems and to be different from canonical ones have to be checked to find out whether the Schema Theorem evaluates the algorithm fitness. The article validates the way of testing the algorithm developed as a technique of an area search. The methodology and research results are stated consistently. Coding specifics of the search queries are noted, a criterion of the coding method applicability is substantiated. A variant of the genotype geometric coding is proposed. In comparison with other methods of binary search coding, it provides a short code length and uniqueness as well as conforms the formulated criterion of applicability. Supporting experimental results are given. The Schema Theorem is shown to hold with the iterative execution of the genetic algorithm being tested.
},
keywords = {coding, crossover, defining length, fitness function, genetic algorithm, genotype, Holland’s schema theorem, innovation index, order, query, scheme, subject search},
pubstate = {published},
tppubtype = {article}
}
The theory and practice of genetic algorithms is largely based on the Schema Theorem. It was formulated for a canonical genetic algorithm and proves its ability to generate a sufficient number of effective schemata of individuals. Genetic algorithms to solve specific problems and to be different from canonical ones have to be checked to find out whether the Schema Theorem evaluates the algorithm fitness. The article validates the way of testing the algorithm developed as a technique of an area search. The methodology and research results are stated consistently. Coding specifics of the search queries are noted, a criterion of the coding method applicability is substantiated. A variant of the genotype geometric coding is proposed. In comparison with other methods of binary search coding, it provides a short code length and uniqueness as well as conforms the formulated criterion of applicability. Supporting experimental results are given. The Schema Theorem is shown to hold with the iterative execution of the genetic algorithm being tested.
Иванов В.К.
Обоснование и постановка задачи прогнозирования результатов генетического алгоритма Journal Article
In: vol. 8, no. 57, pp. 5-13, 2016.
Abstract | Links | BibTeX | Метки: crossover, data centre, defining length, fitness function, genetic algorithm, genotype, Holland’s schema theorem, order, query, representation, scheme, subject search, генетический алгоритм, генотип, кодирование, кроссинговер, определяющая длина, поисковый запрос, порядок, схема, тематический поиск, теорема Холланда, фитнес-функция
@article{nokey,
title = {Обоснование и постановка задачи прогнозирования результатов генетического алгоритма},
author = {Иванов В.К.},
url = {https://disk.yandex.ru/i/I6iQWk2vOm4p8A
https://cyberleninka.ru/article/n/obosnovanie-i-postanovka-zadachi-prognozirovaniya-rezultatov-geneticheskogo-algoritma/viewer},
year = {2016},
date = {2016-12-31},
urldate = {2016-12-31},
volume = {8},
number = {57},
pages = {5-13},
publisher = {СибАК},
abstract = {В статье обосновывается и формулируется постановка задачи прогнозирования результатов генетического алгоритма, разработанного для выполнения документного тематического поиска. Утверждается необходимость и полезность проверки выполнения теоремы схем Холланда для указанного алгоритма. Отмечены условия корректной проверки, в частности требования к кодированию генотипа запросов и сглаживанию фитнес-функции. Предложен метод кодирования генотипа, который использует расстояние между векторами, представ-ляющими запросы.
Vladimir Ivanov
Rationale Of The Problem With Prediction Of Genetic Algorithm Results
This article presents and explains the problem with prediction of the genetic algorithm results developed to perform a subject document search. The article alleges the necessity and usefulness of the verification Holland's scheme theorem for a specified algorithm. The correct test conditions and requirements including the query genotype representation and smoothing of the fitness function are described. The genotype representation method that uses the distance between vectors is offered.},
keywords = {crossover, data centre, defining length, fitness function, genetic algorithm, genotype, Holland’s schema theorem, order, query, representation, scheme, subject search, генетический алгоритм, генотип, кодирование, кроссинговер, определяющая длина, поисковый запрос, порядок, схема, тематический поиск, теорема Холланда, фитнес-функция},
pubstate = {published},
tppubtype = {article}
}
В статье обосновывается и формулируется постановка задачи прогнозирования результатов генетического алгоритма, разработанного для выполнения документного тематического поиска. Утверждается необходимость и полезность проверки выполнения теоремы схем Холланда для указанного алгоритма. Отмечены условия корректной проверки, в частности требования к кодированию генотипа запросов и сглаживанию фитнес-функции. Предложен метод кодирования генотипа, который использует расстояние между векторами, представ-ляющими запросы.
Vladimir Ivanov
Rationale Of The Problem With Prediction Of Genetic Algorithm Results
This article presents and explains the problem with prediction of the genetic algorithm results developed to perform a subject document search. The article alleges the necessity and usefulness of the verification Holland's scheme theorem for a specified algorithm. The correct test conditions and requirements including the query genotype representation and smoothing of the fitness function are described. The genotype representation method that uses the distance between vectors is offered.
Vladimir Ivanov
Rationale Of The Problem With Prediction Of Genetic Algorithm Results
This article presents and explains the problem with prediction of the genetic algorithm results developed to perform a subject document search. The article alleges the necessity and usefulness of the verification Holland's scheme theorem for a specified algorithm. The correct test conditions and requirements including the query genotype representation and smoothing of the fitness function are described. The genotype representation method that uses the distance between vectors is offered.
Ivanov V.K., Palyukh B.V., Sotnikov A.N.
Efficiency of genetic algorithm for subject search queries Journal Article
In: Lobachevskii Journal of Mathematics, vol. 37, no. 3, pp. 244–254, 2016, ISSN: 1995-0802.
Abstract | Links | BibTeX | Altmetric | Метки: convergence, data centre, fitness function, genetic algorithm, population, ranking, relevance, search precision, search query
@article{nokey,
title = {Efficiency of genetic algorithm for subject search queries},
author = {Ivanov V.K. and Palyukh B.V. and Sotnikov A.N.},
url = {https://disk.yandex.ru/i/5AegVA7CNqPk_Q},
doi = {10.1134/S1995080216030124},
issn = {1995-0802},
year = {2016},
date = {2016-03-31},
urldate = {2022-09-28},
journal = {Lobachevskii Journal of Mathematics},
volume = {37},
number = {3},
pages = {244–254},
publisher = {Pleiades Publishing, Ltd.},
abstract = {The article presents and generalizes the results on some performance indicators of genetic algorithm developed by authors and applied to effective search queries and selection of relevant results after document subject search. It is shown that the developed technology expands opportunities of semantic search and increases the number of the found relevant results. In particular, we made an effort to show the ability of the developed algorithm to achieve the neighborhood of the fitness function in a finite number of steps, to provide higher precision of search in comparison with the well-known search engines of the Internet as well as to provide the acceptable semantic relevance of the found documents.
},
keywords = {convergence, data centre, fitness function, genetic algorithm, population, ranking, relevance, search precision, search query},
pubstate = {published},
tppubtype = {article}
}
The article presents and generalizes the results on some performance indicators of genetic algorithm developed by authors and applied to effective search queries and selection of relevant results after document subject search. It is shown that the developed technology expands opportunities of semantic search and increases the number of the found relevant results. In particular, we made an effort to show the ability of the developed algorithm to achieve the neighborhood of the fitness function in a finite number of steps, to provide higher precision of search in comparison with the well-known search engines of the Internet as well as to provide the acceptable semantic relevance of the found documents.