We propose an automatic methodology framework for shortand long-term prediction of time series by means of fuzzy inference systems. In this methodology, fuzzy techniques and statistical techniques for nonparametric residual variance estimation are combined in order to build autoregressive predictive models implemented as fuzzy inference systems. Nonparametric residual variance estimation plays ...

Li and Pedrycz [Y. M. Li, W. Pedrycz, Fuzzy finite automata and fuzzy regular expressions with membership values in lattice ordered monoids, Fuzzy Sets and Systems 156 (2005) 68–92] have proved fundamental results that provide different equivalentways to represent fuzzy languageswithmembership values in a lattice-orderedmonoid, and generalize the well-known results of the classical theory of fo...

To face the reality of practical multiple criteria problems usually possessing characters of fuzziness, and to consider group decision making with various subjective–objective backgrounds usually participating in decision-making process. In this paper, the experts’ opinions are described by linguistic terms which can be expressed in trapezoidal (or triangular) fuzzy numbers. To make the consens...

This paper presents the m e w of sensor fusion based on the Adaptive Fuzzy Kalman Filtering. This method has been applied to fuse position signals from the Global Positioning System (GPS) and Inertial Navigation System (INS) for the autonomous mobile vehicles. The presented method has been validated in 3-0 environment and is of particular importance for guidance, navigation, and control of flyi...

Let α1 be a formula from N5 logic, and let α2 be the formula that is obtained from α1 by replacing conjunction, disjunction and implication by respectively a t-norm ⊗, a t-conorm ⊕ and an implicator →. Noting that V − 2 (w, a) ∈ {0, 1} and V + 2 (w, a) ∈ {0, 1} for all a ∈ At and w ∈ {h, t}, it follows easily from the definitions (17)–(23) that V1(w,α1) = 1 iff V2(w,α2) = [1, 1], V1(w,α1) = 1 i...

Peterson’s Intermediate Syllogisms, generalizing Aristotelian syllogisms by intermediate quantifiers ‘Many’, ‘Most’ and ‘Almost all’, are studied. It is demonstrated that, by associating certain values V, W and U on standard Lukasiewicz MV–algebra with the first and second premise and the conclusion, respectively, the validity of a corresponding intermediate syllogism is determined by a simple ...

Recently, the rough set and fuzzy set theory have generated a great deal of interest among more and more researchers. Granular computing (GrC) is an emerging computing paradigm of information processing and an approach for knowledge representation and data mining. The purpose of granular computing is to seek for an approximation scheme which can effectively solve a complex problem at a certain ...

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Reinforcement Learning (RL) is thought to be an appropriate paradigm to acquire policies for autonomous learning agents that work without initial knowledge because RL evaluates learning from simple “evaluative” or “critic” information instead of “instructive” information used in Supervised Learning. There are two well-known types of RL, namely Actor-Critic Learning and Q-Leaning. Among them, Q-...

7 0 9 0 | P a g e c o u n c i l f o r I n n o v a t i v e R e s e a r c h M a y 2 0 1 6 w w w . c i r w o r l d . c o m An Optimization Method Using Clustering Technique for the Human Emotions Detection Artificial Neuro-Fuzzy Logic System Omayya Murad, Mohammed Malkawi 1 st The University Of Jordan, Amman Jordan, [email protected] 2 nd Associate Professor at JUST, Irbid, Jordan, mimalkawi@...