This work focuses on adapting artificial intelligence techniques for urban growth modeling using multitemporal imagery. Fuzzy set theory and cellular automata are used for this purpose. Fuzzy set theory preserves the spatial continuity of the growth process through allowing a test pixel to be partially developed unlike the binary crisp system (developed/undeveloped). The development level ident...

Based on previous work on encoding deterministic nite-state automata (DFAs) in discrete-time, second-order recurrent neural networks with sigmoidal discriminant functions, we propose an algorithm that constructs an augmented recurrent neural network that encodes fuzzy nite-state automata (FFAs). Given an arbitrary FFA, we apply an algorithm which transforms the FFA into an equivalent determinis...

Satellite image classification is a significant technique used in remote sensing for the computerized study and pattern recognition of satellite information, which make possible the routine explanation of a huge quantity of information. Nowadays cellular automata are implemented for simulation of satellite images and also cellular automata relates to categorization in satellite image is used si...

Taking intuitionistic fuzzy sets as the structures of truth values, we propose the notions of intuitionistic fuzzy context-free grammars (IFCFGs, for short) and pushdown automata with final states (IFPDAs). Then we investigate algebraic characterization of intuitionistic fuzzy recognizable languages including decomposition form and representation theorem. By introducing the generalized subset c...

Dubois. D. , Prade. H. 1980. Fuzzy Sets and Systems. Mathematics in Science and Engineering, Academic Press, New York, 144. Jun. Y. B. , Kavikumar. J. 2011. Bipolar Fuzzy Finite State Machines. Bull. Malays. Sci. Soc. 34 no. 1: 181-188. Kandel. A. , Lee. S. C. Fuzzy Switching and Automata Theory Applications. Edward Arnold Publishers Ltd, London. Lee. K. J. 2000. Bipolar-valued fuzzy sets and t...

Neurofuzzy systems—the combination of artificial neural networks with fuzzy logic—have become useful in many application domains. However, conventional neurofuzzy models usually need enhanced representational power for applications that require context and state (e.g., speech, time series prediction, control). Some of these applications can be readily modeled as finite state automata. Previousl...

Dubois. D. , Prade. H. 1980. Fuzzy Sets and Systems. Mathematics in Science and Engineering, Academic Press, New York, 144. Jun. Y. B. , Kavikumar. J. 2011. Bipolar Fuzzy Finite State Machines. Bull. Malays. Sci. Soc. 34 no. 1: 181-188. Kandel. A. , Lee. S. C. Fuzzy Switching and Automata Theory Applications. Edward Arnold Publishers Ltd, London. Lee. K. J. 2000. Bipolar-valued fuzzy sets and t...

• Proposing a novel theoretical solution to accelerate learning algorithms of GFMM. Providing proofs mathematical lemmas for the proposed method. Assessing efficiency method on widely used datasets. The training time in GFMM model is significantly reduced. This paper proposes process general fuzzy min-max neural network. purpose reduce unsuitable hyperboxes selected as potential candidates expa...

Here we study the notions of lattice-valued finite state machine and lattice-valued fuzzy transformation semigroup when the lattice consists of all the closed subintervals contained in [0, 1]. So, we can apply techniques of interval-valued fuzzy sets to fuzzy automata. In particular, we prove that Atanassov’s Kα operators allow us to retrieve the information given by the transition functions of...