Avtomatizirovannoe Formirovanie Nechetkikh Klassifikatorov
| AUTHOR | Sergienko Roman |
| PUBLISHER | LAP Lambert Academic Publishing (12/30/2011) |
| PRODUCT TYPE | Paperback (Paperback) |
Description
Rabota predstavlyaet soboy dissertatsiyu na soiskanie uchenoy stepeni kandidata tekhnicheski nauki po spetsial'nosti 05.13.17 "teoreticheskie osnovy informatiki." Dissertatsiya zashchishchena 10.12.2010 v Sibirskom Federal'nom Universitete (g. Krasnoyarsk). Rabota posvyashchena issledovaniyu nechetkikh klassifikatorov, odnovremenno reshayushchikh zadachi klassifikatsii i obnaruzheniya novykh znaniy v dannykh. Predlagaetsya novyy metod formirovaniya nechetkogo klassifikatora, ob"edinyayushchiy dva osnovnykh podkhoda k proektirovaniyu nechetkikh sistem evolyutsionnymi algoritmami - Pittsburgskiy i Michiganskiy. Dlya avtomaticheskoy nastroyki parametrov evolyutsionnogo algoritma predlagaetsya koevolyutsionnyy podkhod. Dlya obosnovaniya tselesoobraznosti ispol'zovaniya koevolyutsionnogo algoritma provedeny kompleksnye issledovaniya dannogo podkhoda na mnozhestve testovykh i prakticheskikh zadach optimizatsii razlichnykh klassov (bezuslovnaya i uslovnaya, odno- i mnogokriterial'naya optimizatsiya). Provedeny issledovaniya novogo metoda formirovaniya nechetkogo klassifikatora na ryade prakticheskikh zadach klassifikatsii iz razlichnykh predmetnykh oblastey (ekonomika, meditsina, biologiya, materialovedenie, distantsionnoe zondirovanie Zemli i dr.), pokazany preimushchestva metoda.
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Product Details
ISBN-13:
9783844393132
ISBN-10:
3844393137
Binding:
Paperback or Softback (Trade Paperback (Us))
Content Language:
Russian
More Product Details
Page Count:
196
Carton Quantity:
42
Product Dimensions:
6.00 x 0.45 x 9.00 inches
Weight:
0.65 pound(s)
Country of Origin:
US
Subject Information
BISAC Categories
Computers | General
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Rabota predstavlyaet soboy dissertatsiyu na soiskanie uchenoy stepeni kandidata tekhnicheski nauki po spetsial'nosti 05.13.17 "teoreticheskie osnovy informatiki." Dissertatsiya zashchishchena 10.12.2010 v Sibirskom Federal'nom Universitete (g. Krasnoyarsk). Rabota posvyashchena issledovaniyu nechetkikh klassifikatorov, odnovremenno reshayushchikh zadachi klassifikatsii i obnaruzheniya novykh znaniy v dannykh. Predlagaetsya novyy metod formirovaniya nechetkogo klassifikatora, ob"edinyayushchiy dva osnovnykh podkhoda k proektirovaniyu nechetkikh sistem evolyutsionnymi algoritmami - Pittsburgskiy i Michiganskiy. Dlya avtomaticheskoy nastroyki parametrov evolyutsionnogo algoritma predlagaetsya koevolyutsionnyy podkhod. Dlya obosnovaniya tselesoobraznosti ispol'zovaniya koevolyutsionnogo algoritma provedeny kompleksnye issledovaniya dannogo podkhoda na mnozhestve testovykh i prakticheskikh zadach optimizatsii razlichnykh klassov (bezuslovnaya i uslovnaya, odno- i mnogokriterial'naya optimizatsiya). Provedeny issledovaniya novogo metoda formirovaniya nechetkogo klassifikatora na ryade prakticheskikh zadach klassifikatsii iz razlichnykh predmetnykh oblastey (ekonomika, meditsina, biologiya, materialovedenie, distantsionnoe zondirovanie Zemli i dr.), pokazany preimushchestva metoda.
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