Issledovanie Znachimosti Parametrov Geneticheskogo Algoritma
| AUTHOR | Lipinskiy Leonid; Polyakov Sergey |
| PUBLISHER | LAP Lambert Academic Publishing (05/23/2013) |
| PRODUCT TYPE | Paperback (Paperback) |
Description
Geneticheskiy algoritm byl predlozhen v 1975 godu Dzhonom Khollandom. Dannyy metod optimizatsii yavlyaetsya evristicheskim i predstavlyaet soboy prosteyshuyu model' evolyutsii v prirode. Algoritm Khollanda ne garantiruet obnaruzheniya global'nogo resheniya za priemlemoe vremya. Krome togo, net garantii optimal'nosti naydennogo resheniya. Odnako eto ne pomeshalo emu poluchit' priznanie. Neosporimoe dostoinstvo geneticheskogo algoritma zaklyuchaetsya v ego universal'nosti. On mozhet primenyat'sya dlya resheniya zadach, dlya kotorykh ne razrabotano spetsial'nykh metodov. Ves'ma sushchestvenen tot fakt, chto teoriya geneticheskogo algoritma prosta, ne trebuet osobykh znaniy, dostupna lyubomu obyvatelyu. Nastroyka zhe parametrov geneticheskogo algoritma yavlyaetsya neprostoy zadachey. Tsel'yu raboty yavlyaetsya issledovanie znachimosti dannykh parametrov. Kakie parametry yavlyayutsya naibolee sushchestvennymi? Sushchestvuet li svyaz' mezhdu parametrami? Kakie rekomendatsii mozhno dat' po nastroyke geneticheskogo algoritma?
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Product Format
Product Details
ISBN-13:
9783659401879
ISBN-10:
3659401870
Binding:
Paperback or Softback (Trade Paperback (Us))
Content Language:
Russian
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Page Count:
92
Carton Quantity:
76
Product Dimensions:
6.00 x 0.22 x 9.00 inches
Weight:
0.32 pound(s)
Feature Codes:
Illustrated
Country of Origin:
US
Subject Information
BISAC Categories
Computers | General
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publisher marketing
Geneticheskiy algoritm byl predlozhen v 1975 godu Dzhonom Khollandom. Dannyy metod optimizatsii yavlyaetsya evristicheskim i predstavlyaet soboy prosteyshuyu model' evolyutsii v prirode. Algoritm Khollanda ne garantiruet obnaruzheniya global'nogo resheniya za priemlemoe vremya. Krome togo, net garantii optimal'nosti naydennogo resheniya. Odnako eto ne pomeshalo emu poluchit' priznanie. Neosporimoe dostoinstvo geneticheskogo algoritma zaklyuchaetsya v ego universal'nosti. On mozhet primenyat'sya dlya resheniya zadach, dlya kotorykh ne razrabotano spetsial'nykh metodov. Ves'ma sushchestvenen tot fakt, chto teoriya geneticheskogo algoritma prosta, ne trebuet osobykh znaniy, dostupna lyubomu obyvatelyu. Nastroyka zhe parametrov geneticheskogo algoritma yavlyaetsya neprostoy zadachey. Tsel'yu raboty yavlyaetsya issledovanie znachimosti dannykh parametrov. Kakie parametry yavlyayutsya naibolee sushchestvennymi? Sushchestvuet li svyaz' mezhdu parametrami? Kakie rekomendatsii mozhno dat' po nastroyke geneticheskogo algoritma?
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