The management of uncertainty and imprecision is becoming more and more important in knowledge-based systems. Fuzzy logic provides a systematic basis for representing and inferring with this kind of knowledge. This paper describes an approach for fuzzy inference based on an uncertainty forward propagation method and a change in the granularity of the elements involved. The proposed model is abl...

The aim of this paper is to compare first order predicate logic, fuzzy logic and non-monotonic logic as knowledge representation methods. First, we define five properties of knowledge; conceptualization, transfer, modification, integration and decomposition. We also evaluate first order predicate logic, fuzzy logic and non-monotonic logic for the above properties, in the view of accuracy, compl...

This paper proposes a fuzzy abductive inference to realize a creative thinking support system. The fuzzy logic is applied to Peng and Reggia's abductive inference for handling degrees of manifestations. Application of the new method to a diagnostic problem is shown and the e ectiveness of the proposed method is demonstrated by comparing the inferred results with those by the conventional fuzzy ...

fuzzy logic, 67algebraic semantics, 53approximate reasoning, 6axiomatic extensions of MTL, 56 Bellman, R., 21bipolar possibilistic logic, 93BL logic, 51 canonical chain, 66canonical completeness, 66canonical extension, 83Carnap, R., 3comparative truth, 63compositionality, 29computational complexity, 73core fuzzy logic, 58 De Finetti B., 3degre...

Hybrid systems composed of AI approaches have shown quite remarkable results in diagnosis. Designing of such multi-method sytems generally bears some diiculties in nding a uniform representation of inputs and outputs of their subsystems. Since Fuzzy Logic, too, has proven high importance in Artiicial Intelligence, due to its adequate pseudoverbal representation of knowledge, it is well suited t...

This work presents the development and experimental evaluation of a method based on fuzzy logic to locate mobile robots in an Intelligent Space using wireless sensor networks (WSNs). The problem consists of locating a mobile node using only inter-node range measurements, which are estimated by radio frequency signal strength attenuation. The sensor model of these measurements is very noisy and ...

This paper introduces a new method of empowering Logical Petri Nets (LPN) and Fuzzy Logical Petri Nets (FLPN) [1] using multiple logic. In this paper we proposed a Multi-Logical Petri Nets (MLPN) and Multi-Logical Fuzzy Petri Nets (MLFPN) based on Logical Petri Nets (LPN) and Fuzzy Logical Petri Nets (FLPN). Here we have showed that, how multiple logic is implemented in MLPN and MLFPN. The prop...

This paper presents the modeling of a photovoltaic (PV) module at varying atmospheric conditions such as irradiation and temperature. It also includes the maximum power point tracking (MPPT) of the PV module using conventional perturb and observe (P&O) method and fuzzy logic controller. For the performance analysis, the simulation of the PV module along with MPPT controller is done by using MAT...

This paper presents a review study of PID and fuzzy logic controller for level control of the tank. PID controller is widely used in industries for level control and non-linear system but tuning of PID controller is difficult and it use a mathematical model of the system which is also difficult to find for highly nonlinear system. Fuzzy logic controller use linguistic method to control the syst...

A new scheme to obtain optimal fuzzy subsets and rules is proposed. The method is derived from the use of genetic algorithms, where the genes of the chromosome are classified into two different types. These genes can be arranged in a hierarchical form, where one type of genes controls the other type of genes. The effectiveness of this genetic formulation enables the fuzzy subsets and rules to b...