We consider function approximation by fuzzy systems. Fuzzy systems are typically used for approximating deterministic functions, in which the stochastic uncertainty is ignored. We propose probabilistic fuzzy systems in which the probabilistic nature of uncertainty is taken into account. Furthermore, these systems take also fuzzy uncertainty into account by their fuzzy partitioning of input and ...

increasing development of engineering projects construction such as city subway needs appropriate investigation, management and control of groundwater. therefore, precise estimation of hydrogeological parameters such as hydraulic conductivity is the most important factor in studies and modeling of groundwater and geotechnical issues. in recent decades, various laboratory and field methods exist...

Fuzzy inference method based approach to the forming of modular intellectual system of assessment the quality of communication services is proposed. Developed under this approach the basic fuzzy estimation model takes into account the recommendations of the International Telecommunication Union in respect of the operation of packet switching networks based on IPprotocol. To implement the main f...

Using a set of confidence intervals, we develop a common approach, to construct a fuzzy set as an estimator for unknown parameters in statistical models. We investigate a method to derive the explicit and unique membership function of such fuzzy estimators. The proposed method has been used to derive the fuzzy estimators of the parameters of a Normal distribution and some functions of parameter...

Estimation of temporal fuzzy sets that model dynamic processes is discussed. It has been found that although poles of attraction can be estimated fairly well with different fuzzy partitioning algorithms, membership function estimates may fail in accurately describing dynamic changes within the observed signals. Two types of fuzzy partitioning algorithms are compared: fuzzy c-means (FCM) and fuz...

A new approach for testing fuzzy hypotheses based on fuzzy data is introduced. According to the proposed approach, a method is first developed based on the defined fuzzy point estimation, which are then used to make a procedure for testing fuzzy hypotheses. This approach has been used to test simple, one-sided and two-sided fuzzy hypotheses. Two new criteria, called degree of acceptance (DA) an...

Clustering is a standard approach in analysis of data and construction of separated similar groups. The most widely used robust soft clustering methods are fuzzy, rough and rough fuzzy clustering. The prominent feature of soft clustering leads to combine the rough and fuzzy sets. The Rough Fuzzy C-Means (RFCM) includes the lower and boundary estimation of rough sets, and fuzzy membership of fuz...

The  tunnel  boring  machine  (TBM)  penetration  rate  estimation  is  one  of  the  crucial  and complex  tasks  encountered  frequently  to  excavate  the  mechanical  tunnels.  Estimating  the machine  penetration  rate  may  reduce  the  risks  related  to  high  capital  costs  typical  for excavation  operation.  Thus  establishing  a  relationship  between  rock  properties  and  TBM pe...