In today’s world there is exponential increase in the use of air conditioning devices. The enhancement in utilization of such devices makes it essential for them to work with their full capability and efficiency. The fuzzy inference systems are best suited for the applications requiring easy interpretation, human reasoning, accurate decision making and control. The fuzzy inference systems resem...

in modern agriculture, image processing technique is used for mechanization and intelligent machines instead of humans. one of them is identifying varieties of plants and fruits. identifying plant varieties is important in plant eugenic programs. visual examination of plant leaves and fruits are the common processes for this aim. identification and classification of plants using machine vision ...

The fuzzy rule based inference is known to be a useful tool to capture the behavior of an approximate system in transportation. One of the obstacles of implementing the fuzzy rule based inference, however, has been to calibrate the membership functions of the fuzzy sets used in the rules. This paper proposes a way to calibrate the membership function when a set of input and output data is given...

Fuzzy logic, neural network, fuzzy-neural networks play an important role in the linguistic modeling of intelligent control and decision making in complex systems. The Fuzzy-Neural Network (FNN) learning represents one of the most effective algorithms to build such linguistic models. This paper proposes an Artificial Immune Algorithm (AIA) based optimal learning fuzzy-neural network (IM-FNN). T...

This study presents a novel controller of magnetic levitation system by using new neuro-fuzzy structures which called flexible neuro-fuzzy systems. In this type of controller we use sliding mode control with neuro-fuzzy to eliminate the Jacobian of plant. At first, we control magnetic levitation system with Mamdanitype neuro-fuzzy systems and logical-type neuro-fuzzy systems separately and then...

By Fuzzy theory we mean Zadeh’s mathematical theory of generalized sets and their associated logics. At this state of the art, fuzzy theory has provided significant contributions to artificial intelligence via a broader umbrella of soft computing. Like other theories of mathematics, such as number theory and potential theory, fuzzy theory has its own agenda, concepts, and techniques. However, j...

Fuzzy models have been designed to represent approximate or imprecise relationships in complex systems and have been successfully employed in control systems, expert systems, and decision analysis. Classically, fuzzy models were built from human expertise and knowledge of the system being modeled. As systems have grown more complex it has become increasingly difficult to construct models direct...

Inference mechanisms and interpretations of fuzzy rule bases are studied together from the point of view of systems of fuzzy relation equations. A proper use of an inference mechanism connected to a fuzzy relation interpreting a fuzzy rule base is certified by keeping the fundamental interpolation condition. The paper aims at new solutions of systems of fuzzy relation equations which are motiva...

Interlacing techniques were introduced in the early analog TV transmission systems as an efficient mechanism capable of halving the video bandwidth. Currently, interlacing is also used by some modern digital TV transmission systems, however, there is a problem at the receiver side since the majority of modern display devices require a progressive scanning. De-interlacing algorithms convert an i...

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...