Relevant bibliographies by topics / Method of clusterization

Academic literature on the topic 'Method of clusterization'

Author: Grafiati
Published: 30 May 2022
Last updated: 31 May 2022

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Contents

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Method of clusterization.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "Method of clusterization"

1

Kravets, Petro. "Gaming Method of Ontology Clusterization." Webology 16, no. 1 (June 30, 2019): 55–76. http://dx.doi.org/10.14704/web/v16i1/a179.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Mkrtchian, Oleksandr. "Automatic landscape-ecological regionalization by the application of clustering and segmentation." Visnyk of the Lviv University. Series Geography, no. 47 (November 27, 2014): 177–84. http://dx.doi.org/10.30970/vgg.2014.47.950.

Full text
Abstract:
The paper deals with the principles and methods of automatic landscape-ecological regionalization by the clusterization and segmentation methods. The employment of ecological morphometric indices as criteria for clusterization and segmentation has been justified. The method of the quantification of spatial dependencies between typological and regional spatial units based on information theory has been suggested. Key words: regionalization, clusterization, segmentation.
APA, Harvard, Vancouver, ISO, and other styles
3

Litvinenko, Natalya, Orken Mamyrbayev, Assem Shayakhmetova, and Mussa Turdalyuly. "Clusterization by the K-means method when K is unknown." ITM Web of Conferences 24 (2019): 01013. http://dx.doi.org/10.1051/itmconf/20192401013.

Full text
Abstract:
There are various methods of objects’ clusterization used in different areas of machine learning. Among the vast amount of clusterization methods, the K-means method is one of the most popular. Such a method has as pros as cons. Speaking about the advantages of this method, we can mention the rather high speed of objects clusterization. The main disadvantage is a necessity to know the number of clusters before the experiment. This paper describes the new way and the new method of clusterization, based on the K-means method. The method we suggest is also quite fast in terms of processing speed, however, it does not require the user to know in advance the exact number of clusters to be processed. The user only has to define the range within which the number of clusters is located. Besides, using suggested method there is a possibility to limit the radius of clusters, which would allow finding objects that express the criteria of one cluster in the most distinctive and accurate way, and it would also allow limiting the number of objects in each cluster within the certain range.
APA, Harvard, Vancouver, ISO, and other styles
4

Сірий, Олексій Олександрович. "Message clusterization method based on archive transformation." ScienceRise 6, no. 2(11) (June 21, 2015): 76. http://dx.doi.org/10.15587/2313-8416.2015.44364.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Sadovsky, Michael G., Eugene Yu Bushmelev, and Anatoly N. Ostylovsky. "New Clusterization Method Based on Graph Connectivity Search." Journal of Siberian Federal University. Mathematics & Physics 10, no. 4 (December 2017): 443–49. http://dx.doi.org/10.17516/1997-1397-2017-10-4-443-449.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Savina, N. P., N. A. Galstyan, O. V. Litvishko, and E. A. Zakrevskaya. "Using Methods of Intellectual Analysis to Step up Profitability of Network Business." Vestnik of the Plekhanov Russian University of Economics, no. 2 (April 13, 2022): 176–85. http://dx.doi.org/10.21686/2413-2829-2022-2-176-185.

Full text
Abstract:
The article studies the use of drug-store chain clusterization and determines strategy of work with each of the clusters, which is necessary because key work parameters of drug-store chains, such as selling speed, the number of brands of the company being investigated in the chain, the condition of stores, availability of strong competitors in the chain selling must be verified. Another reason is complexity of company resource distribution to build communications with drug-store chains (representatives’ calls) and products themselves among drug-store chains. To resolve the problem of drug-store clusterization k-means method based on the assessment of the company share and the share of a concrete brand in the drug-store chain was chosen for the research. As metrics for identifying the quality of obtained results ‘silhouette’ was chosen, i.e. the form of a cluster set representation. Its factor is equal to 0.514, which testifies to rather high accuracy of results and possibility to introduce this algorithm into real business practice. By cluster analyzing the multitude of drug-store chains a set of three clusters was identified. On the basis of these results of clusterization and current business requirements for each cluster a number of recommendations were put forward aimed at interaction between the pharmaceutical company and drug-store chains in the aspect of assessing the competition environment, analyzing selling speed and re-filling stocks of the chain, frequency of pharmaceutical representatives’ calls to drug-store chains. The findings of the research allowed us to draw a conclusion that any method of clusterization of drug-store data should be renewed in view of the quality of result interpretation, topicality of initial criteria of clusterization and should be corrected proceeding from business requirements, which arrive from marketer teams and managers on medicine categories and separate brands.
APA, Harvard, Vancouver, ISO, and other styles
7

Yuryev, G. A., E. K. Verkhovskaya, and N. E. Yuryeva. "Stochastic swarm clusterization method in natural language data processing." Experimental Psychology (Russia) 11, no. 3 (2018): 5–18. http://dx.doi.org/10.17759/exppsy.2018110301.

Full text
Abstract:
Consider natural language data processing technology based on non-linear dimensionality reduction method which takes into account the discriminating power of the solution found for given values of the categorical variable associated with each observation. Stochastic optimization method known as the “Particle swarm optimization” is proposed to found characteristics that ensure the best separation of observations in terms of a given quality functional. The basis for evaluating the quality of the solution lies in the purity of the clusters obtained with the k-means method, or with using self-organizing Kohonen feature maps.
APA, Harvard, Vancouver, ISO, and other styles
8

Tumino, A., C. Spitaleri, S. Cherubini, G. D’Agata, L. Guardo, M. Gulino, I. Indelicato, et al. "Clusterization of light nuclei and the Trojan Horse Method." Journal of Physics: Conference Series 863 (June 2017): 012072. http://dx.doi.org/10.1088/1742-6596/863/1/012072.

Full text
APA, Harvard, Vancouver, ISO, and other styles
9

Gorobchenko, O. "DEVELOPMENT OF THE METHOD OF CLUSTERIZATION OF TRAIN SITUATIONS." Collection of scientific works of the State University of Infrastructure and Technologies series "Transport Systems and Technologies" 1, no. 37 (June 29, 2021): 187–95. http://dx.doi.org/10.32703/2617-9040-2021-37-18.

Full text
Abstract:
The introduction of intelligent locomotive control systems requires better approaches to assessing and monitoring the current train situation than those used in modern traction rolling stock. Automatic detection of complex abnormal situations is currently not provided. For example, determining the inefficiency of the brakes, speeding, the presence of obstacles or people on the track, the deterioration of the traction properties of rolling stock, etc. relies solely on the driver of the locomotive. Given the important impact of these factors on traffic safety, it is proposed to include in the functions of automated and intelligent traffic control systems recognition of abnormal situations and notification of its occurrence. When driving a train, all objects of classification (train situations) are divided into a finite number of classes. A finite number of precedent objects are known and studied for each class. The task of pattern recognition is to assign a new recognizable situation to a class. The classifier or decisive rule is the rule of assigning the image of a train situation to one of the classes on the basis of its vector of features. An order of classification of train situations has been developed, which allows to allocate clusters of any complex shape, provided that different parts of such clusters are connected by chains of close to each other elements. The measure of difference is the square of the Euclidean distance.
APA, Harvard, Vancouver, ISO, and other styles
10

PRONYAYEVA, Lyudmila I., Ol'ga A. FEDOTENKOVA, and Anna V. PAVLOVA. "Analyzing the state and development trends in economic clusterization processes in foreign countries." National Interests: Priorities and Security 17, no. 5 (May 14, 2021): 808–37. http://dx.doi.org/10.24891/ni.17.5.808.

Full text
Abstract:
Subject. The article discusses the existing trends and national approaches to clustering in foreign economies, which concurrently determine the socio-economic parity of strategic growth indicators. Objectives. We determine the most suitable conditions for cluster structures to emerge in national economies and macroregions, and look for methods to optimize and use how economic clusterization in Russia can be developed. Methods. The study is based on general scientific methods, such as the generalization, synthesis and analysis, and special ones, which serve for evaluating the trajectory of clusterization processes in national economics across the globe, and point out their specifics. Furthermore, we applied the comprehensive approach to evaluating the development trajectory of cluster structures, and involved classification and identification techniques and the method of grouping and graphic representation. Results. We grouped countries by purpose of national economic clusterization, and performed the comparative analysis of clustering model through indicative points. The article presents approaches to describing key clusterization centers at the macroregional development level. The article spotlights the most frequent specialization of clusters abroad. We analyzed how cluster structures develop in the European Union, and concurrently assessed the volume of funds allocated to cluster structures there and the existing strategic partnerships of clusters in Europe. Conclusions and Relevance. The study allows to optimize the existing approaches to clustering of the Russian economy through the analysis of global practices of cluster structures’ operation, which can expand opportunities for making national integrated entities more competitive.
APA, Harvard, Vancouver, ISO, and other styles
More sources

Dissertations / Theses on the topic "Method of clusterization"

1

Смирнов, Олександр Владиславович. "Визначення емоційного стану людини на базі аналізу голосових характеристик." Master's thesis, Київ, 2018. https://ela.kpi.ua/handle/123456789/23637.

Full text
Abstract:
Метою даної роботи є дослідження голосових сигналів у частотній та часовій області для ідентифікації об’єктивних параметрів, що дозволяють класифікувати голос людини за емоційним забарвленням. За проведеними дослідженнями розроблене програмне забезпечення із використанням програмного пакету Mathlab 2014a. У результаті виконання роботи: створено нові методи обробки голосу, які передбачають використання для характеристики психологічного типу людини; отримані результати, які в подальшому можуть бути використані в психіатрії для якісної оцінки емоційно-вольових порушень при різних психо-паталогіях; для оцінки кадрового потенціалу працівників; важливим застосуванням подібних методів можуть стати правоохоронні системи та засоби безпеки в напрямку виявлення агресивно забарвлених голосів; розроблено програмне забезпечення, що дозволяє класифікувати голос людини в залежності від її емоційного стану.
The purpose of this work is to study the voice signals in the frequency and time domain for the identification of objective parameters that allow to classify a person's voice by emotional coloring According to the research, software was developed using the Mathlab 2014a software package. As a result of the work: created new methods of voice processing, which provide for use to characterize the psychological type of person; obtained results that can be used in psychiatry for qualitative evaluation of emotional and volitional disorders in various psychological pathologies; to assess staffing potential of employees; law enforcement systems and security measures in the direction of detecting aggressively colored voices may become an important use of such methods; Software has been developed that allows you to classify a person's voice depending on her emotional state.
Целью данной работы является исследование голосовых сигналов в частотной и временной области для идентификации объективных параметров, позволяющих классифицировать голос человека по эмоциональной окраске. По проведенным исследованиям разработанное программное обеспечение с использованием программного пакета Mathlab 2014a. В результате выполнения работы: созданы новые методы обработки голоса, которые предусматривают использование для характеристики психологического типа человека; полученные результаты, которые в дальнейшем могут быть использованы в психиатрии для качественной оценки эмоционально-волевых нарушений при различных психо-патологии; для оценки кадрового потенциала работников; важным применением подобных методов могут стать правоохранительные системы и средства безопасности в направлении выявления агрессивно окрашенных голосов; разработано программное обеспечение, позволяющее классифицировать голос человека в зависимости от его эмоционального состояния.
APA, Harvard, Vancouver, ISO, and other styles
2

Зaвeрухa, Ceргiй Ceргiйoвич, and Sergiy Serhiyovych Zaverukha. "Мeтoди клacтeризaцiї oблiкoвих зaпиciв кoриcтувaчiв для cиcтeм oбмiну пoвiдoмлeннями." Master's thesis, 2020. http://elartu.tntu.edu.ua/handle/lib/34111.

Full text
Abstract:
У квaлiфiкaцiйнiй рoбoтi мaгicтрa прoвeдeнo дocлiджeння мeтoдiв iєрaрхiчнoї клacтeризaцiї, a тaкoж рoзрoблeнo пришвидшeний мeтoд iєрaрхiчнoї клacтeризaцiї шляхoм викoриcтaння зacoбiв бaгaтoпoтoкoвoгo прoгрaмувaння. У пeршoму рoздiлi булo зрoблeнo кoрoткий oгляд тeхнoлoгiй дoбувaння дaних, рoзглянутo цiлi i влacтивocтi клacтeрiв. Крiм цьoгo, булo рoзглянутo вiдмiннocтi мiж клacтeризaцiєю тa клacифiкaцiєю. В другoму рoздiлi був прoвeдeний oгляд ocнoвних мeтoдiв пoбудoви iєрaрхiчних клacтeрiв, ocнoвнi вiдмiннocтi з цeнтрoїдними тa cтaтиcтичними мoдeлями. Визнaчeнo cлaбкi cтoрoни iєрaрхiчнoї мoдeлi тa прeдcтaвлeнo cпociб вирiшeння прoблeм з швидкicтю викoнaння. Трeтiй рoздiл мicтить вимoги дo cтвoрювaнoгo прoгрaмнoгo прoдукту тa кoрoткий oгляд викoриcтoвувaних iнcтрумeнтiв. В чeтвeртoму рoздiлi пoкaзaнo прoцec рoзрoбки рoзпoдiлeнoї лoгiки iєрaрхiчнoї клacтeризaцiї. Прeдcтaвлeнo рeзультaти тecтувaння i викoнaння cтвoрeнoї мoдeлi нa cучacних бaгaтoпoтoкoвих cиcтeмaх.
In the qualification work of the master the research of methods of hierarchical clustering is carried out, and also the accelerated method of hierarchical clustering by use of means of multithreaded programming is developed. In the first section, a brief overview of data mining technologies was made, and the goals and properties of clusters were considered. In addition, the differences between clustering and classification were considered. The second section reviews the main methods of constructing hierarchical clusters, the main differences with centroid and statistical models. The weaknesses of the hierarchical model are identified and a way to solve speed problems is presented. The third section contains the requirements for the created software product and a brief overview of the tools used. The fourth section shows the process of developing a distributed logic of hierarchical clustering. The results of testing and execution of the created model on modern multithreaded systems are presented.
ВCТУП ...9 1 КЛACТEРИЗAЦIЯ ДAНИХ ...11 1.1 Iнтeлeктуaльнi тeхнoлoгiї дoбувaння дaних ...11 1.2 Визнaчeння клacтeрнoгo aнaлiзу ....12 1.3 Зaдaчi тa cфeри зacтocувaння клacтeризaцiї дaних ..14 1.4 Цiлi i влacтивocтi клacтeрiв ....16 1.5 Мeтoди клacтeрнoгo aнaлiзу ...19 1.6 Клacтeрнa eквiвaлeнтнicть ...20 1.7 Iєрaрхiчнa клacтeризaцiя ...21 1.8 Бaзoвий aглoмeрaтний iєрaрхiчний клacтeрний aлгoритм ..22 1.9 Пiдхoди дo пoбудoви iєрaрхiчних клacтeрiв ...24 1.10 Фoрмулa Лeнca-Вiльямca для близькocтi клacтeрiв ...28 1.11 Ключoвi прoблeми iєрaрхiчнoї клacтeризaцiї...29 1.12 Виcнoвки ...30 2 OГЛЯД ВIДOМИХ CИCТEМ КЛACТEРИЗAЦIЇ КOРИCТУВAЧIВ ...32 2.1 Клacтeризaцiя кoриcтувaчiв в cиcтeмaх тaргeтингу ....32 2.1.1 Google ads ...32 2.1.2 Facebook Business Manager ...34 2.2 Клacтeризaцiя кoриcтувaчiв в cтрiмiнгoвих ceрвicaх ....35 2.2.1 YouTube ....35 2.2.2 Deezer ....36 2.3 Клacтeризaцiя кoриcтувaчiв в coцiaльних мeрeжaх знaйoмcтв ...37 2.3.1 Tinder ...38 2.3.2 Badoo ...39 2.4 Клacтeризaцiя в cиcтeмaх групoвих чaтiв ...40 2.4.1 ЧaтПрocтoТaк ...40 2.4.2 Amino ...41 2.5 Виcнoвки ...42 3 ПРAКТИЧНA РEAЛIЗAЦIЯ КЛACТEРИЗAЦIЇ КOРИCТУВAЧIВ ...44 3.1 Ocнoвнi вимoги дo прoгрaмнoгo зaбeзпeчeння ...44 3.2 Oпиc oбрaних зacoбiв для рoзрoбки прoгрaмнoгo зaбeзпeчeння ...45 3.2.1 Мoвa прoгрaмувaння Java...45 3.2.2 Викoриcтoвувaннi бiблioтeки ...46 3.2.3 Iнтeгрoвaнe ceрeдoвищe рoзрoбки Intelij idea ..47 3.2.4 Cиcтeмa кoнтрoлю вeрciй git ...48 3.2.5 Cиcтeмa aвтoмaтичнoї збiрки maven ...49 3.3. Рeaлiзaцiя дoдaтку вибрaними cпocoбaми ...50 3.3.1 Вибiр cтруктури для n-вимiрнoгo вeктoру ...50 3.3.2 Вибiр cтруктури iєрaрхiчнoї клacтeризaцiї ..51 3.3.3 Пул iєрaрхiчних вузлiв ...52 3.4 Ocнoвнi зacoби мультипoтoкoвoгo прoгрaмувaння ...54 3.4.1 Пул пoтoкiв ...54 3.4.2 Мoдифiкaтoри дocтупу ...56 3.4.3 Бaр’єр ...57 3.5 Пoбудoвa мaтрицi пoдiбнocтeй ...58 3.5.1 Пoрiвняння нaбoрiв дaних ...58 3.5.2. Пoбудoвa iєрaрхiчнoгo дeрeвa нa ocнoвi мaтрицi пoдiбнocтeй ....59 3.6 Тecтувaння нa кoрeктнicть ....59 3.7 Прoдуктивнicть ...60 3.8 Виcнoвки ...61 4 OХOРOНA ПРAЦI ТA БEЗПEКA В НAДЗВИЧAЙНИХ CИТУAЦIЯХ ...62 4.1 Зacтeрeжeння нeщacних випaдкiв тa упрaвлiння ризикaми ....62 4.2. Ocвiтлeння вирoбничих примiщeнь для рoбoти з ВДТ тa лoкaльнiй кoмп’ютeрнiй мeрeжi ...67 ВИCНOВКИ ...70 ПEРEЛIК ДЖEРEЛ ...71 ДOДAТКИ
APA, Harvard, Vancouver, ISO, and other styles

Book chapters on the topic "Method of clusterization"

1

Televnoy, Andrey, Sergei Evgenievich Ivanov, and Nataliya Gorlushkina. "Hybrid Method of Multiple Factor Data Clusterization." In Communications in Computer and Information Science, 139–53. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-65218-0_11.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Televnoy, Andrey, Sergei Evgenievich Ivanov, and Nataliya Gorlushkina. "Hybrid Method of Multiple Factor Data Clusterization." In Communications in Computer and Information Science, 139–53. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-65218-0_11.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Orekhov, Andrey V., Victor I. Shishkin, and Nikolay S. Lyudkevich. "Clusterization of White Blood Cells on the Modified UPGMC Method." In Lecture Notes in Control and Information Sciences - Proceedings, 559–66. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-87966-2_62.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Lamża, Aleksander, and Zygmunt Wróbel. "Dynamics of the Clusterization Process in an Adaptative Method of Image Segmentation." In Advances in Intelligent and Soft Computing, 25–32. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13105-9_3.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Biryukov, Alexander, Oksana Brezhneva, Lyudmila Altynbaeva, Angela Schnayderman, and Natalia Efimova. "Methods of Neural Network Modeling of Clusterization of Taxpayers to Determine Credit Risk by a Financial Regulator." In Comprehensible Science, 3–13. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-85799-8_1.

Full text
APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "Method of clusterization"

1

Burtsev, G., P. A. Kharitontseva, and I. A. Uzhegova. "Fractures Clusterization Applying K-means Method Using Microimage Log Data for Fractures Characterization." In Saint Petersburg 2018. Netherlands: EAGE Publications BV, 2018. http://dx.doi.org/10.3997/2214-4609.201800138.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Krak, Iurii V., Hrygorii I. Kudin, Olexander V. Barmak, Eduard O. Manziuk, Andrzej Smolarz, and Orken Mamyrbaev. "Method and algorithm of the piecewise-hyperplane clusterization using tools of pseudo-inverse matrices." In Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2019, edited by Ryszard S. Romaniuk and Maciej Linczuk. SPIE, 2019. http://dx.doi.org/10.1117/12.2537417.

Full text
APA, Harvard, Vancouver, ISO, and other styles
3

Wattimanela, Henry Junus, and G. Haumahu. "Analysis of the distribution types of depth and magnitude of tectonic earthquake 2018 in Lombok Island based on clusterization results using K-Means method." In INTERNATIONAL CONFERENCE ON ENERGY AND ENVIRONMENT (ICEE 2021). AIP Publishing, 2021. http://dx.doi.org/10.1063/5.0059668.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Shishkin, Iurii E., and Aleksandr N. Grekov. "Analysis of Image Clusterization Methods for Oceanographical Equipment." In 2018 International Russian Automation Conference (RusAutoCon). IEEE, 2018. http://dx.doi.org/10.1109/rusautocon.2018.8501756.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Safina, O. S., and G. Tsironis. "Phase clusterization in a hierarchical network of mutually coupled van der Pole oscillators." In Methods and Means of Scientific Research. Moscow: Scientific and Technological Centre of Unique Instrumentation of RAS, 2020. http://dx.doi.org/10.25210/mmsr-2020/5.

Full text
APA, Harvard, Vancouver, ISO, and other styles
6

Wlodarczyk-Sielicka, Marta, and Andrzej Stateczny. "Selection of SOM parameters for the needs of clusterization of data obtained by interferometric methods." In 2015 16th International Radar Symposium (IRS). IEEE, 2015. http://dx.doi.org/10.1109/irs.2015.7226268.

Full text
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the extended bibliographies on the topic 'Method of clusterization' for particular source types:
Journal articles
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography