A heuristic algorithm is developed to solve the uncertainty problem and generate a suitable decision for the provided facts.
Huang [8] and Kim et al. [9] have proposed some works for applying fuzzy sets in clustering categorical data to solve the uncertainty issue.
To solve the uncertainty or imprecision in QFD, numerous researchers have applied the fuzzy set theory to QFD and developed various fuzzy QFD models.
To solve the uncertainty or imprecision in QFD, numerous researchers have attempted to apply the fuzzy set theory to QFD and have developed various fuzzy QFD approaches.
Note that the main purpose of introducing the circle-cluster in Section 3 is to solve the uncertainty of sub-block when the normalized CFO is near to +0.5 or −0.5.
Based on the study of uncertainty in calculating evacuation time, this paper put forward a safety factor determination method on the basis of fuzzy comprehensive evaluation, this method can solve the uncertainty problem effectively.
As for the unknown normalized CFO, which is randomly generated in [4.5,+0.5) or (−0.5,−4.5] to illuminate the proposed optimization method, can solve the uncertainty of sub-block. Compared with "WCM + CoSaMP", "FAWC + CoSaMP" proves that the proposed measurement matrix can improve the correct probability due to its same recovery algorithm (i.e., CoSaMP).
To solve the uncertainty on the confounding of regressive CIN III lesions, this prospective analysis with CIN III as end point should be accompanied by archival studies, in which retrospectively the HPV status of smears preceding a diagnosis of cervical cancer, is assessed.
These methods are feasible for such studies, but they do not solve the uncertainties related to quality ratings, as discussed in Section 2.2.
It has been shown that space-time joint signal processing not only improves the sensing performance but also solves the noise uncertainty problem to some extent.
