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  4. Avtomaticheskoe porozhdenie gipotez v intellektualnykh sistemakh / Izd. stereotip.

Avtomaticheskoe porozhdenie gipotez v intellektualnykh sistemakh / Izd. stereotip.

Автоматическое порождение гипотез в интеллектуальных системах / Изд. стереотип.
Avtomaticheskoe porozhdenie gipotez v intellektualnykh sistemakh / Izd. stereotip.
Language
Publisher
Publication year
Format
Pages
528
ISBN
978-5-397-07090-4
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33.00 € 30.00 € w/o VAT
 
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В книге представлены результаты применения ДСМ-метода автоматического порождения гипотез для интеллектуального анализа данных. В отличие от известных методов анализа данных ДСМ-метод реализует взаимодействие трех познавательных процедур - индукции, аналогии и абдукции (в известных же нестатистических методах анализа данных реализуются лишь отдельные процедуры - например, индукция или аналогия). Особенностью ДСМ-метода является точная характеризация условий его применимости и построение спецификаций для различных предметных областей. В книге содержатся результаты применения ДСМ-метода для анализа данных в фармакологии, биохимии, медицинской диагностике, криминалистике и робототехнике. Книга предназначена для специалистов в области искусственного интеллекта и анализа данных, а также для логиков и философов, интересующихся проблемами искусственного интеллекта. Automatic Hypotheses Generation in Intelligent Systems The results of the application of JSM-method of automatic hypotheses generation in Intelligent data analysis are represented in the book. The JSM-method realizes the synthesis of three cognitive procedures - induction, analogy, abduction. This separates the method from other methods of data analysis: in non-statistical methods only single procedure - induction or analogy, for example, - is realized. The strict characterization of applicability conditions and details specifications for different domains seems to be considered as the peculiarities of JSM-method. The book contains the results of JSM-application to pharmacology, biochemistry, medical diagnostics, sociology, criminalistics and robotics. The book is intended for professionals working in the field of artificial intelligence and data analysis, as well as for logicians and philosophers with an interest in this research.
V knige predstavleny rezultaty primenenija DSM-metoda avtomaticheskogo porozhdenija gipotez dlja intellektualnogo analiza dannykh. V otlichie ot izvestnykh metodov analiza dannykh DSM-metod realizuet vzaimodejstvie trekh poznavatelnykh protsedur - induktsii, analogii i abduktsii (v izvestnykh zhe nestatisticheskikh metodakh analiza dannykh realizujutsja lish otdelnye protsedury - naprimer, induktsija ili analogija). Osobennostju DSM-metoda javljaetsja tochnaja kharakterizatsija uslovij ego primenimosti i postroenie spetsifikatsij dlja razlichnykh predmetnykh oblastej. V knige soderzhatsja rezultaty primenenija DSM-metoda dlja analiza dannykh v farmakologii, biokhimii, meditsinskoj diagnostike, kriminalistike i robototekhnike. Kniga prednaznachena dlja spetsialistov v oblasti iskusstvennogo intellekta i analiza dannykh, a takzhe dlja logikov i filosofov, interesujuschikhsja problemami iskusstvennogo intellekta. Automatic Hypotheses Generation in Intelligent Systems The results of the application of JSM-method of automatic hypotheses generation in Intelligent data analysis are represented in the book. The JSM-method realizes the synthesis of three cognitive procedures - induction, analogy, abduction. This separates the method from other methods of data analysis: in non-statistical methods only single procedure - induction or analogy, for example, - is realized. The strict characterization of applicability conditions and details specifications for different domains seems to be considered as the peculiarities of JSM-method. The book contains the results of JSM-application to pharmacology, biochemistry, medical diagnostics, sociology, criminalistics and robotics. The book is intended for professionals working in the field of artificial intelligence and data analysis, as well as for logicians and philosophers with an interest in this research.
Category
EAN
9785397070904
BIC category:
U
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