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immunity

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  • Update : 2008-10-13
  • Size : 8.8kb
  • Downloaded :1次
  • Author :江泉
  • About : 江泉
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Introduction - If you have any usage issues, please Google them yourself
provide a source of artificial immune algorithm, the algorithm process include : 1. Two of the parameters set. Initial randomly generated groups-- pop = initpop (popsize, chromlength) 3. Fault type coding, each act a! Code (1 :), normal; Code (2, :), 50%; Code (3 :), 150%. Fault actual measured data coding, here Unnoralcode, 188% 4. Beginning iteration (M) : 1) the objective function value : Euclidean distance [objvalue] = calobjvalue (pop, i) 2) calculation of each individual groups of fitness calfitvalue fitvalue = ( objvalue) 3) = newpop choice selection (pop, fitvalue) objvalue = calobjvalue (newpop, i) =% newpop cross-crossover (newpop, pc, k) = calobjvalue objvalue (newpop, i) =% variation newpop mutation (newpop, pm ) objvalue = calobjvalue (newpop, i)% 5. groups sought to adapt th
Packet file list
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Packet : 67506266immunity.rar filelist
immunity\best.m
immunity\calfitvalue.m
immunity\calobjvalue.m
immunity\code.txt
immunity\crossover.m
immunity\decodebinary.m
immunity\decodechrom.m
immunity\hjjsort.m
immunity\initpop.asv
immunity\initpop.m
immunity\main.m
immunity\mutation.m
immunity\readme.txt
immunity\resultselect.m
immunity\selection.m
immunity
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