Structural modeling using rough sets

A rough set-based approach to handling spatial uncertainty in binary images

“…The problem here is that finding such an equivalence relation seems to obviate the need for any further processing to do the edge detection. Wojcik and Wojcik (1996) demonstrate how rough sets are more accurately used in context based image processing than statistical means, and they present a neural network to uncover ''casual relationships (between images) using a rough sets approach'' (Wojcik and Wojcik, 1996). In essence they show how through the empirical algorithms based on rough sets, are superior to those based on statistics (guessing).…”

System Health Prognostic Model Using Rough Sets

“…By this the proposed system correctly assesses the critical factors for prediction. Relating health status measurement to the equivalence class of the rough sets representing the healthy ranges and not to the mean or to median is the key difference with respect to statistics [6]. Note, that matrices [p], [D], and [G] are not the values of the variables as commonly used in statistics, they are the ratios directly representing health problem level.…”

“…Latent variables describing object's health degradation over some recent time periods are collected into matrices. The object is in good health if each record of the following matrix inequalities is true (compare [6]):…”

“…[D] is the matrix of rough sets covariances [6] representing degradation influences of all health status endogenous variables on the endogenous variables:…”

“…The proposed model is a data fusion system similar to [6], in which terms are the products of ratios of degradation and the ratios of influences on the degradations. The degradation data fusion system presented here is deterministic for data sequenced by time.…”