{"id":10297,"date":"2026-04-06T16:48:21","date_gmt":"2026-04-06T15:48:21","guid":{"rendered":"https:\/\/izvestiyakbncran.ru\/?page_id=10297"},"modified":"2026-06-18T09:14:56","modified_gmt":"2026-06-18T08:14:56","slug":"25-6-11-en","status":"publish","type":"page","link":"https:\/\/izvestiyakbncran.ru\/index.php\/en\/25-6-11-en\/","title":{"rendered":"25.6.11 En"},"content":{"rendered":"\n<h1 class=\"wp-block-heading has-lora-font-family\" style=\"font-size:22px\"><strong>Development of an algorithm based on logical operations to detect patterns in data with missing values<\/strong><\/h1>\n\n\n\n<p class=\"has-foreground-color has-text-color has-link-color has-lora-font-family has-extra-small-font-size wp-elements-4cfc8f24eba0790350f7c6a71f007f86 wp-block-paragraph\" style=\"margin-top:0;margin-bottom:0;padding-top:0;padding-bottom:0\"><strong>L.A. Lyutikova<br><\/strong><\/p>\n\n\n\n<div class=\"wp-block-group is-vertical is-content-justification-left is-nowrap is-layout-flex wp-container-core-group-is-layout-20193d73 wp-block-group-is-layout-flex\" style=\"border-style:none;border-width:0px;margin-top:0;margin-bottom:0;padding-top:0;padding-bottom:0\">\n<p class=\"has-text-color has-link-color has-lora-font-family wp-elements-1934a6274ad67c2dd8d97ce7471e2bbb wp-block-paragraph\" style=\"color:#5b1919;font-size:12px;text-decoration:underline\"><\/p>\n\n\n\n<div class=\"wp-block-group is-horizontal is-layout-flex wp-container-core-group-is-layout-9076828a wp-block-group-is-layout-flex\" style=\"min-height:0px;margin-top:0;margin-bottom:0;padding-top:0;padding-bottom:0\">\n<div class=\"wp-block-buttons is-content-justification-left is-layout-flex wp-container-core-buttons-is-layout-856cf56e wp-block-buttons-is-layout-flex\" style=\"margin-top:0;margin-bottom:0;padding-top:0;padding-right:0;padding-bottom:0;padding-left:0\">\n<div class=\"wp-block-button has-custom-width wp-block-button__width-100 is-style-outline is-style-outline--1\"><a class=\"wp-block-button__link has-background-background-color has-text-color has-background has-link-color has-border-color has-custom-font-size wp-element-button\" href=\"http:\/\/izvestiyakbncran.ru\/wp-content\/uploads\/2026\/06\/lyut-11.pdf\" style=\"border-color:#5b1919;border-style:solid;border-width:2px;border-radius:8px;color:#5b1919;padding-top:0.4rem;padding-right:var(--wp--preset--spacing--40);padding-bottom:0.4rem;padding-left:var(--wp--preset--spacing--40);font-size:12px\">PDF<\/a><\/div>\n<\/div>\n\n\n\n<div style=\"height:0px;width:0px\" aria-hidden=\"true\" class=\"wp-block-spacer wp-container-content-273e683f\"><\/div>\n\n\n\n<div class=\"wp-block-buttons is-layout-flex wp-block-buttons-is-layout-flex\">\n<div class=\"wp-block-button has-custom-width wp-block-button__width-100 is-style-outline is-style-outline--2\"><a class=\"wp-block-button__link has-background-background-color has-text-color has-background has-link-color has-border-color has-text-align-center has-custom-font-size wp-element-button\" href=\"https:\/\/journals.rcsi.science\/1991-6639\/article\/xml\/391431\" style=\"border-color:#5b1919;border-width:2px;border-top-left-radius:8px;border-top-right-radius:8px;border-bottom-left-radius:8px;border-bottom-right-radius:8px;color:#5b1919;padding-top:0.4rem;padding-right:var(--wp--preset--spacing--40);padding-bottom:0.4rem;padding-left:var(--wp--preset--spacing--40);font-size:12px\">JATS XML<\/a><\/div>\n<\/div>\n<\/div>\n\n\n\n<p class=\"has-text-color has-link-color has-lora-font-family has-extra-small-font-size wp-elements-41ee428b6a5740c7f514a7432ff786a3 wp-block-paragraph\" style=\"border-style:none;border-width:0px;border-top-left-radius:0px;border-top-right-radius:0px;border-bottom-left-radius:0px;border-bottom-right-radius:0px;color:#5b1919;margin-top:0;margin-right:0;margin-bottom:0;margin-left:0;padding-top:0;padding-right:0;padding-bottom:0;padding-left:0\"><\/p>\n<\/div>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity is-style-wide\" style=\"margin-top:var(--wp--preset--spacing--20);margin-bottom:var(--wp--preset--spacing--20)\"\/>\n\n\n\n<p class=\"has-foreground-color has-text-color has-link-color has-lora-font-family has-extra-small-font-size wp-elements-d59004a06d2eaef1e3970833b4981e2b wp-block-paragraph\" style=\"line-height:1.4\"><em><strong><strong>Abstract<\/strong>.<\/strong> <\/em>This paper presents a method of local interpretation of solutions of a trained neural network by functions of multivalued predicate logic. The local interpretation of a neural network refers to the process of explaining the decisions made by the model on a specific example or in the vicinity of a specific input. The proposed approach is based on a set of functions of multivalued logic, which are generalized operations that meet certain requirements. By combining these functions, it is possible to detect internal patterns in the data and even correct the results obtained with the help of neural networks. The proposed method was investigated in the context of classification problems using multidimensional discrete features. In such cases, each attribute can take one of k possible values and have equal importance for class identification. This approach opens up new possibilities for understanding and explaining the rules underlying the data, which are not always obvious when using conventional neural networks.<\/p>\n\n\n\n<p class=\"has-foreground-color has-text-color has-link-color has-lora-font-family has-extra-small-font-size wp-elements-df03325adc83c022634de6b79d43432f wp-block-paragraph\" style=\"line-height:1.4\"><\/p>\n\n\n\n<p class=\"has-foreground-color has-text-color has-link-color has-lora-font-family has-extra-small-font-size wp-elements-c1c7bc5404c234ea52cc8dd0e91be4f9 wp-block-paragraph\" style=\"line-height:1.4\"><strong><em><strong>Keywords<\/strong>:<\/em><\/strong> interpretation, multivalued logic, neural network, generalized addition, data<\/p>\n\n\n\n<p class=\"has-foreground-color has-text-color has-link-color has-lora-font-family has-extra-small-font-size wp-elements-df03325adc83c022634de6b79d43432f wp-block-paragraph\" style=\"line-height:1.4\"><\/p>\n\n\n\n<p class=\"has-foreground-color has-text-color has-link-color has-lora-font-family wp-elements-9b98197caf579c35efff47fdd035118e wp-block-paragraph\" style=\"font-size:12px;line-height:1.4\"><strong><strong>For citation<\/strong>.<\/strong> Lyutikova L.A. Development of an algorithm based on logical operations to detect patterns in data with missing values. News of the Kabardino-Balkarian Scientific Center of RAS. 2023. No. 6(116). Pp. 109\u2013115. DOI: 10.35330\/1991-6639-2023-6-116-109-115<\/p>\n\n\n\n<p class=\"has-foreground-color has-text-color has-link-color has-lora-font-family wp-elements-17c3333a0b1db39b7fa4a3e1a1572bc4 wp-block-paragraph\" style=\"font-size:12px;line-height:1.4\"><\/p>\n\n\n\n<details class=\"wp-block-details has-foreground-color has-text-color has-link-color has-lora-font-family has-extra-small-font-size wp-elements-2d8c98ae87871ad3951a9fa8ddbc10d9 is-layout-flow wp-container-core-details-is-layout-f488f964 wp-block-details-is-layout-flow\" style=\"font-style:normal;font-weight:700;line-height:1.5\"><summary><strong>R<\/strong>eferences<\/summary>\n<ol style=\"margin-top:0;margin-bottom:0\" class=\"wp-block-list\">\n<li style=\"font-style:normal;font-weight:400\">Zhuravlev Yu.I. On the algebraic approach to solving problems of recognition or classification. <em>Problemy kibernetiki<\/em> [Problems of cybernetics]. 1978. Vol. 33. Pp. 5\u201368. (In Russian)<\/li>\n\n\n\n<li style=\"font-style:normal;font-weight:400\">Shibzukhov Z.M. Correct algorithms for aggregating operations. <em>Raspoznavaniye obrazov i analiz izobrazheniy <\/em>[Pattern recognition and image analysis]. 2014. No. 3\u201324. Pp. 377\u2013382. (In Russian)<\/li>\n\n\n\n<li style=\"font-style:normal;font-weight:400\">Naimi A.I., Balzer L.B. Multilevel generalization: an introduction to super learning. <em>European Journal of Epidemiology<\/em>. 2018. Vol. 33. Pp. 459\u2013464.<\/li>\n\n\n\n<li style=\"font-style:normal;font-weight:400\">Wang H., Smith S. Big data analysis and perturbation using a data mining algorithm. <em>Journal of Soft Computing Paradigm<\/em>. 2021. No. 3\u201301. Pp. 19\u201328.<\/li>\n\n\n\n<li style=\"font-style:normal;font-weight:400\">Joe MrK Vijesh, Jennifer S. Raj User Recommendation System Dependent on LocationBased Orientation Context. <em>Journal of Trends in Computer Science and Smart Technology<\/em>. 2021. No. 3\u201301. Pp. 14\u201323.<\/li>\n\n\n\n<li style=\"font-style:normal;font-weight:400\">Grabisch M., Marichal J-L., Pap E. Aggregation functions. <em>Cambridge University Press<\/em>. Vol. 127. P. 16.<\/li>\n\n\n\n<li style=\"font-style:normal;font-weight:400\">Calvo T., Belyakov G. Aggregating functions based on penalties. <em>Fuzzy sets and systems.<\/em> No. 10\u2013161. Pp. 1420\u20131436.<\/li>\n\n\n\n<li style=\"font-style:normal;font-weight:400\">Mesiar R., Komornikova M., Kolesarova A., Calvo T. Fuzzy aggregation functions: a revision. Sets and their extensions: representation, aggregation and models. Springer-Verlag. Berlin, 2008.<\/li>\n\n\n\n<li style=\"font-style:normal;font-weight:400\">Yang F., Yang Zh., Cohen W.W. Differentiable learning of logical rules for reasoning in the knowledge base. <em>Advances in the field of neural information processing systems<\/em>. 2017. Pp. 2320\u20132329.<\/li>\n\n\n\n<li style=\"font-style:normal;font-weight:400\">Flach P. <em>Mashinnoye obucheniye: nauka i iskusstvo postroyeniya algoritmov, kotoryye izvlekayut znaniya iz dannykh <\/em>[Machine learning: the science and art of building algorithms that extract knowledge from data]. Moscow, DMK Press, 2015. 400 p. (In Russian)<\/li>\n\n\n\n<li style=\"font-style:normal;font-weight:400\">Lyutikova L.A., Shmatova E.V. Algorithm for constructing logical operations to identify patterns in data. E3S Web of Conferences, Moscow, November 25\u201327, 2020. Vol. 224. P. 01009.<\/li>\n<\/ol>\n<\/details>\n\n\n\n<details class=\"wp-block-details has-foreground-color has-text-color has-link-color has-lora-font-family has-extra-small-font-size wp-elements-0aa4f0c2f6d17b000f4fe30606833940 is-layout-flow wp-container-core-details-is-layout-9ff6af70 wp-block-details-is-layout-flow\" style=\"font-style:normal;font-weight:700;line-height:1.5\"><summary><strong>Information about the author<\/strong><\/summary>\n<div class=\"wp-block-group is-vertical is-layout-flex wp-container-core-group-is-layout-1c18c512 wp-block-group-is-layout-flex\" style=\"min-height:0px;margin-top:0;margin-bottom:0;padding-top:var(--wp--preset--spacing--20);padding-right:var(--wp--preset--spacing--40);padding-bottom:var(--wp--preset--spacing--20);padding-left:var(--wp--preset--spacing--40)\">\n<p class=\"wp-block-paragraph\" style=\"font-style:normal;font-weight:400\"><strong>Lyutikova Larisa Adolfovna<\/strong>, Candidate of Physical and Mathematics Sciences, Head of the Department of Neuroinformatics and Machine Learning, Institute of Applied Mathematics and Automation \u2013 branch of Kabardino-Balkarian Scientific Center of the Russian Academy of Sciences;<br>360000, Russia, Nalchik, 89 A Shortanov street;<br>lylarisa@yandex, ORCID: https:\/\/orcid.org\/0000-0003-4941-7854<\/p>\n\n\n\n<p class=\"wp-block-paragraph\" style=\"font-style:normal;font-weight:400\"><\/p>\n\n\n\n<p class=\"wp-block-paragraph\" style=\"font-style:normal;font-weight:400\"><br><\/p>\n\n\n\n<p class=\"wp-block-paragraph\" style=\"font-style:normal;font-weight:400\"><\/p>\n\n\n\n<p class=\"wp-block-paragraph\" style=\"font-style:normal;font-weight:400\"><\/p>\n\n\n\n<p class=\"wp-block-paragraph\" style=\"font-style:normal;font-weight:400\"><\/p>\n\n\n\n<p class=\"wp-block-paragraph\" style=\"font-style:normal;font-weight:400\"><\/p>\n\n\n\n<p class=\"wp-block-paragraph\" style=\"font-style:normal;font-weight:400\"><\/p>\n<\/div>\n<\/details>\n","protected":false},"excerpt":{"rendered":"<p>Development of an algorithm based on logical operations to detect patterns in data with missing values L.A. Lyutikova Abstract. This paper presents a method of local interpretation of solutions of a trained neural network by functions of multivalued predicate logic. The local interpretation of a neural network refers to the process of explaining the decisions [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"wp-custom-template-home","meta":{"footnotes":""},"class_list":["post-10297","page","type-page","status-publish","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.8 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>25.6.11 En - \u0418\u0417\u0412\u0415\u0421\u0422\u0418\u042f \u041a\u0410\u0411\u0410\u0420\u0414\u0418\u041d\u041e-\u0411\u0410\u041b\u041a\u0410\u0420\u0421\u041a\u041e\u0413\u041e \u041d\u0410\u0423\u0427\u041d\u041e\u0413\u041e \u0426\u0415\u041d\u0422\u0420\u0410 \u0420\u0410\u041d\u00bb<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/izvestiyakbncran.ru\/index.php\/en\/25-6-11-en\/\" \/>\n<meta property=\"og:locale\" content=\"ru_RU\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"25.6.11 En - \u0418\u0417\u0412\u0415\u0421\u0422\u0418\u042f \u041a\u0410\u0411\u0410\u0420\u0414\u0418\u041d\u041e-\u0411\u0410\u041b\u041a\u0410\u0420\u0421\u041a\u041e\u0413\u041e \u041d\u0410\u0423\u0427\u041d\u041e\u0413\u041e \u0426\u0415\u041d\u0422\u0420\u0410 \u0420\u0410\u041d\u00bb\" \/>\n<meta property=\"og:description\" content=\"Development of an algorithm based on logical operations to detect patterns in data with missing values L.A. 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