uz zy ▁sets ▁are ▁associated ▁with ▁the ▁terms ▁that ▁appear ▁in ▁the ▁ante ced ents ▁( IF - part ) ▁or ▁consequ ents ▁( TH EN - part ) ▁of ▁rules , ▁and ▁with ▁the ▁inputs ▁to ▁and ▁the ▁outputs ▁of ▁the ▁F LS . ▁M emb ership ▁functions ▁are ▁used ▁to ▁describe ▁these ▁f uz zy ▁sets , ▁and ▁in ▁a ▁type - 1 ▁F LS ▁they ▁are ▁all ▁type - 1 ▁f uz zy ▁sets , ▁whereas ▁in ▁an ▁interval ▁type - 2 ▁F LS ▁at ▁least ▁one ▁membership ▁function ▁is ▁an ▁interval ▁type - 2 ▁f uz zy ▁set . ▁ ▁An ▁interval ▁type - 2 ▁F LS ▁lets ▁any ▁one ▁or ▁all ▁of ▁the ▁following ▁kinds ▁of ▁un cert aint ies ▁be ▁quant ified : ▁▁ ▁W ords ▁that ▁are ▁used ▁in ▁ante ced ents ▁and ▁consequ ents ▁of ▁rules — because ▁words ▁can ▁mean ▁different ▁things ▁to ▁different ▁people . ▁ ▁Un certain ▁consequ ents — because ▁when ▁rules ▁are ▁obtained ▁from ▁a ▁group ▁of ▁exper ts , ▁consequ ents ▁will ▁often ▁be ▁different ▁for ▁the ▁same ▁rule , ▁i . e . ▁the ▁exper ts ▁will ▁not ▁necessarily ▁be ▁in ▁agreement . ▁ ▁M emb ership ▁function ▁parameters — because ▁when ▁those ▁parameters ▁are ▁optimized ▁using ▁uncertain ▁( no isy ) ▁training ▁data , ▁the ▁parameters ▁become ▁uncertain . ▁ ▁No isy ▁measurements — because ▁very ▁often ▁it ▁is ▁such ▁measurements ▁that ▁activ ate ▁the ▁F LS . ▁ ▁In ▁Fig . ▁ 3 , ▁measured ▁(