In many geographical applications there is a need to model spatial phenomena not simply by sharply bounded objects but rather through vague concepts due to indeterminate boundaries. Spatial database systems and geographical information systems are currently not able to deal with this kind of data. In order to support these applications , for an important kind of vagueness called fuzziness, we p...

It is shown that, for any spatial frame L (i.e., L is a complete lattice generated by the set of all prime elements), both the specialization L-preorder of L-topological spaces introduced by Lai and Zhang [Fuzzy preorder and fuzzy topology, Fuzzy Sets and Systems 157 (2006) 1865–1885] and that of L-fuzzifying topological spaces introduced by Fang and Qiu [Fuzzy orders and fuzzifying topologies,...

The idea of spherical fuzzy soft set (SFSS) is a new hybrid model (SS) and (SFS). An SFSS approach for information analysis fusion, modeling. We define the concepts spherical-fuzzy-soft-set topology (SFSS-topology) separation axioms. Several characteristics SFSS-topology are investigated related results derived. developed an extended choice value method (CVM) AHP-TOPSIS (analytical hierarchy pr...

In this paper, we dene the concepts of compatibility between twofuzzy subsets on Q, the set of states of a max- min general fuzzy automatonand transitivity in a max-min general fuzzy automaton. We then construct auniform structure on Q, and dene a topology on it. We also dene the conceptof semi-uniform structures on a nonempty set X and construct a semi-uniformstructure on the set of states of ...

After introducing many different types of prefilter convergence, we introduce an universal method to define various notions of compactness using cluster point and convergence of a prefilter and to prove the Tychonoff theorem using characterizations of ultra(maximal) prefilters. : prefilter convergence, universal method, Tychonoff theorem, ultra prefilter, good extension

In the synthesis of a fuzzy system two steps are generally employed: the identification of a structure and the optimization of the parameters defining it. This paper presents a methodology to automatically perform these two steps in conjunction using a three-phase approach to construct a fuzzy system from numerical data. Phase 1 outlines the membership functions and system rules for a specific ...

Evolutionary optimization aims to tune the hyper-parameters during learning in a computationally fast manner. For of multi-task problems, evolution is done by creating unified search space with dimensionality that can include all tasks. Multi-task achieved via selective imitation where two individuals same type skill are encouraged crossover. Due relatedness tasks, resulting offspring may have ...