▁devi ations ▁from ▁design - base ▁or ▁estimated ▁worst - case ▁loads . ▁Another ▁engineering ▁application ▁involves ▁the ▁design ▁of ▁a ▁neural ▁net ▁for ▁detect ing ▁fault s ▁in ▁a ▁mechanical ▁system , ▁based ▁on ▁real - time ▁measurements . ▁A ▁major ▁difficulty ▁is ▁that ▁fault s ▁are ▁highly ▁id ios ync r atic , ▁so ▁that ▁training ▁data ▁for ▁the ▁neural ▁net ▁will ▁tend ▁to ▁differ ▁substantial ly ▁from ▁data ▁obtained ▁from ▁real - time ▁fault s ▁after ▁the ▁net ▁has ▁been ▁trained . ▁The ▁info - g ap ▁robust ness ▁strategy ▁enables ▁one ▁to ▁design ▁the ▁neural ▁net ▁to ▁be ▁robust ▁to ▁the ▁dispar ity ▁between ▁training ▁data ▁and ▁future ▁real ▁events . ▁ ▁Bi ology ▁ ▁Bi ological ▁systems ▁are ▁vast ly ▁more ▁complex ▁and ▁subt le ▁than ▁our ▁best ▁models , ▁so ▁the ▁conservation ▁bi ologist ▁faces ▁substantial ▁info - g aps ▁in ▁using ▁bi ological ▁models . ▁For ▁instance , ▁Le vy ▁et ▁al . ▁ ▁use ▁an ▁info - g ap ▁robust - s atisf icing ▁" method ology ▁for ▁ident ifying ▁management ▁alternatives ▁that ▁are ▁robust ▁to ▁environmental ▁uncertainty , ▁but ▁non eth eless ▁meet ▁specified ▁so cio - e conom ic ▁and ▁environmental ▁goals ." ▁They ▁use ▁info - g ap ▁robust ness ▁curves ▁to ▁select ▁among ▁management ▁options ▁for ▁spr uce - bud w orm ▁populations ▁in ▁Eastern ▁Canada . ▁Burg man ▁ ▁uses ▁the ▁fact ▁that ▁the ▁robust ness ▁curves ▁of ▁different ▁alternatives ▁can ▁intersect , ▁to ▁illustrate ▁a ▁change ▁in ▁preference ▁between