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

immunity
........\best.m
........\calfitvalue.m
........\calobjvalue.m
........\code.txt
........\crossover.m
........\decodebinary.m
........\decodechrom.m
........\hjjsort.m
........\initpop.asv
........\initpop.m
........\main.m
........\mutation.m
........\readme.txt
........\resultselect.m
........\selection.m

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