Alina shafronenko (11 risultati)
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Da: California Books, Miami, FL, U.S.A.California Books
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Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections
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Da: Chiron Media, Wallingford, Regno UnitoChiron Media
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Da: moluna, Greven, Germaniamoluna
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Da: preigu, Osnabrück, Germaniapreigu
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Taschenbuch. Condizione: Neu. Neuro-Fuzzy Clustering of Distorted Data Using Cat Swarm Optimization | Alina Shafronenko (u. a.) | Taschenbuch | 60 S. | Englisch | 2020 | LAP LAMBERT Academic Publishing | EAN 9786200506429 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[…dot]de | Anbieter: preigu.
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Da: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
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PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Da: PBShop.store UK, Fairford, GLOS, Regno UnitoPBShop.store UK
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PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Nowadays, computational intelligence technologies often and quite successfully are used in solving complex problems that, as a rule, do not have an analytical solution. Today, these technologies and especially artificial neural net…works (ANN) are widely used to solve various problems of signal processing, optimization, optimal and adaptive control, pattern recognition, identification, time- series prediction, etc. At the same time, the described approaches to data recovery are workable only in cases when the initial data are set a priori, and the 'object-property' table or time series has a fixed number of observations, i.e. do not change during processing. This book is devoted to the development and study of methods for dynamic data mining, containing missing and distorted observations. The main feature of data mining methods is to establish the presence and nature of hidden patterns in data, whereas traditional methods mainly deal with parametric evaluation of already established patterns. 60 pp. Englisch.
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Nowadays, computational intelligence technologies often and quite successfully are used in solving complex problems that, as a rule, do not have an analytical solution. Today, these technologies and especially artificial neural network…s (ANN) are widely used to solve various problems of signal processing, optimization, optimal and adaptive control, pattern recognition, identification, time- series prediction, etc. At the same time, the described approaches to data recovery are workable only in cases when the initial data are set a priori, and the ¿object-property¿ table or time series has a fixed number of observations, i.e. do not change during processing. This book is devoted to the development and study of methods for dynamic data mining, containing missing and distorted observations. The main feature of data mining methods is to establish the presence and nature of hidden patterns in data, whereas traditional methods mainly deal with parametric evaluation of already established patterns.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 60 pp. Englisch.
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Nowadays, computational intelligence technologies often and quite successfully are used in solving complex problems that, as a rule, do not have an analytical solution. Today, these technologies and especially artificial neural networks… (ANN) are widely used to solve various problems of signal processing, optimization, optimal and adaptive control, pattern recognition, identification, time- series prediction, etc. At the same time, the described approaches to data recovery are workable only in cases when the initial data are set a priori, and the 'object-property' table or time series has a fixed number of observations, i.e. do not change during processing. This book is devoted to the development and study of methods for dynamic data mining, containing missing and distorted observations. The main feature of data mining methods is to establish the presence and nature of hidden patterns in data, whereas traditional methods mainly deal with parametric evaluation of already established patterns.
Editore: LAP Lambert Academic Publishing, 2025
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Da: CitiRetail, Stevenage, Regno UnitoCitiRetail
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Paperback. Condizione: new. Paperback. Monografiya prisvyachena novim efektivnim nechitkim metodam obchislyuvalnogo intelektu, a same, nechitkiy klasterizatsii danikh za umov apriornoi neviznachenosti ta nadannya im adaptivnikh vlastivostey, shcho zabezpechue mozhlivist opratsovuvannya potokiv nestatsionarnikh danikh, vikrivleni…kh zavadami ta propuskami, shcho poslidovno nadkhodyat na obrobku v onlayn rezhimi. Provedeno analiz isnuyuchikh metodiv obrobki potokiv danikh v umovakh apriornoi neviznachenosti ta vikrivlenosti, obgruntovano neobkhidnist virishennya zadach klasterizatsii ta analizu danikh za umov zminnikh kharakteristik potoku, shcho vklyuchae zminu kilkosti klasiv, ikhnoi strukturi ta neperedbachuvanikh dreyfiv. Rozrobleno adaptivni metodi nechitkoi klasterizatsii, yaki zdatni pratsyuvati yak v paketnomu, tak i v onlayn rezhimakh, a takozh na vibirkakh, shcho zminyuyut rozmirnist ta formu klasteriv; dozvolyayut obroblyati veliki obsyagi danikh, shcho mozhut nadkhoditi na obrobku poslidovno u formi potokiv danikh, efektivno pratsyuvati za umov potochnoi ta apriornoi neviznachenosti, stokhastichnosti, neliniynosti, nestatsionarnosti ta e naybilsh pristosovanimi dlya virishennya zadach Data Mining ta Data Stream Mining. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
