In this Final Project, Fast Generalized Fuzzy C-Means (FGFCM) algorithm has been used for segmenting an images compressed by fuzzy transforms algorithms. The images compressed input is needed for solving the problem about size of dataset, before the dataset implemented in segmentation process that used spacial information and gray value based on correlation between pixels. There are several ste...

Faculty of Technology Department of Informatics by Majid Almaraashi This thesis reports the work of using simulated annealing to design more efficient fuzzy logic systems to model problems with associated uncertainties. Simulated annealing is used within this work as a method for learning the best configurations of type-1 and type-2 fuzzy logic systems to maximise their modelling ability. There...

Fuzzy set theory has been proposed as a means for modeling the vagueness in complex systems. Fuzzy systems usually employ type-1 fuzzy sets, representing uncertainty by numbers in the range [0, 1]. Despite commercial success of fuzzy logic, a type-1 fuzzy set (T1FS) does not capture uncertainty in its manifestations when it arises from vagueness in the shape of the membership function. Such unc...

Fuzzy tori are finite dimensional C*-algebras endowed with an appropriate notion of noncommutative geometry inherited from ergodic action a closed subgroup the torus, which meant as approximations and more generally, quantum tori. A mean to specify space is by constructing over it spectral triple. We prove in this paper that we can construct triples on fuzzy which, dimension grows infinity unde...

Real-time cell scheduling is a promising area for the application of evolvable hardware (EHW). In this paper, we describe an intrinsic evolvable and online adaptive EHW for solving the packet switching problem. Based on the coding and evolution scheme, we refer to it as evolvable fuzzy hardware (EFH), an extension of our proposed evolvable fuzzy system (EFS) [1, 2] and reconfigurable fuzzy infe...

We describe in this chapter a hybrid method for adaptive model-based control of nonlinear dynamic systems using Neural Networks, Fuzzy Logic, and Fractal Theory. The new neuro-fuzzy-fractal method combines Soft Computing (SC) techniques with the concept of the fractal dimension for the domain of Nonlinear Dynamic System Control. The new method for adaptive model-based control has been implement...

This paper provides a step-by-step account of how fuzzy measures of monetary poverty and nonmonetary deprivation may be constructed based on survey data such as from EU-SILC. For non-monetary deprivation, meaning dimensions or groupings of initial items of deprivation are identified using explanatory and confirmatory factor analyses, and a weighting system is applied for the aggregation individ...

A fundamental procedure appearing within such clustering methods as k-Means, Expectation Maximization, Fuzzy-C-Means and Minimum Message Length is that of computing estimators of location. Most estimators of location exhibiting useful robustness properties require at least quadratic time to compute, far too slow for large data mining applications. In this paper, we propose O(Dn p n)-time random...