Multidimensional scaling is one of the important techniques for a big data management. In this paper, various statistical analyses are compared to find the best-fitting method for a representation of a higher dimensional data using the reduced or smaller dimensional data using various multivariate analyses with maximum likelihood estimation through the neurofuzzy systems, which estimate the pre...

The aim of this paper is to present and compare four different neuro-fuzzy approaches to the construction of fuzzy rule-based models for dynamic processes. These approaches have been applied to modelling of an industrial gas furnace system (Box-Jenkins benchmark). The following neuro-fuzzy systems have been considered: nfMod – the system proposed in this paper, the well-known ANFIS and NFIDENT ...

A closed-loop system is developed to control the weld fusion which is specified by the topside and back-side bead widths of the weld pool. Because in many applications only a top-side sensor is allowed which is attached to and moves with the welding torch, an image processing algorithm and neurofuzzy model have been incorporated to measure and estimate the top-side and back-side bead widths bas...

We present a formal description of a neurofuzzy system capable of aligning two sequences recognizing their internal structure. The alignment is done on two levels: grouping of the elements and alignment of groups. The system incorporates expert knowledge on both levels. Furthermore, it can be optimized by a learning algorithm adapted from the neural network domain. The system has been applied t...

this paper presents the bio-inspired neurofuzzy based route selection system to avoid traffic congestion. The proposed neuro-fuzzy system selects the best multi-parameters direction between two desired nodes: source and the endpoint. This research practices a mixture of neuro-fuzzy logic and ant colony system (ACS) algorithm for the principal routing to fulfill all the preferred requirements of...

The problem of finding relations between structure of large molecules and their chemical and biological activity is known as the structure-activity relation problem (SAR). Two neural networks developed in our group were applied to this problem: the Feature Space Mapping neurofuzzy system and the constrained MLP network used to extract logical rules. Two SAR data sets were analyzed: antibiotic a...