The main objective of this tutorial is to present the 2005 situation of the state-of-the-art concerning the application of soft computing methods to fault diagnosis and supervision systems. Another objective is to show the unsolved and open problems of modern fault diagnosis and supervision that can be solved either with soft computing methods or hybrid systems based on analytical and soft comp...

carbon nanostructures are famous structures which are used in several industries such as separation, treatment, energy storage (i.e. methane and hydrogen storage), etc. a successful modeling of activated carbon preparation is very important in saving time and money. there are some attempts to achieve the appropriate theoretical modeling of activated carbon preparation but most of them were almo...

In this article, a new type-2 fuzzy-based modeling approach is proposed to assess human operators’ psychophysiological states for both safety and reliability of human–machine interface systems. Such technique combines fuzzy sets with state tracking update the rule base through Bayesian process. These configurations successfully lead an adaptive, robust, transparent computational framework that ...

According to the water resources and climate change and challenges of Urmia Lake basin, which is the discharge and final destination of North West Rivers, a model was presented. Due to climate change and water resources in river basin such as rainfall, climate change in basin that has direct impact on evaporation over water catchment areas and lake water, this model can be provided. In addition...

This paper aims at development of procedures and algorithms for application of artificial intelligence tools to acquire process and analyze various types of knowledge. The proposed environment integrates techniques of knowledge and decision process modeling such as neural networks and fuzzy logic-based reasoning methods. The problem of an identification of complex processes with the use of neur...

In this paper, we present an on-line learning neuro-fuzzy system which was inspired by parts of the mechanisms in immune systems. It illustrates how an on-line learning neuro-fuzzy system can capture the basic elements of the immune system and exhibit some of its appealing properties. During the learning procedure, a neuro-fuzzy system can be incrementally constructed. We illustrate the potenti...

Fuzzy systems are currently being used in a wide field of industrial and scientific applications. Since the design and especially the optimization process of fuzzy systems can be very time consuming, it is convenient to have algorithms which construct and optimize them automatically. One popular approach is to combine fuzzy systems with learning techniques derived from neural networks. Such app...

Several adaptation techniques have been investigated to optimize fuzzy inference systems. Neural network learning algorithms have been used to determine the parameters of fuzzy inference system. Such models are often called as integrated neuro-fuzzy models. In an integrated neuro-fuzzy model there is no guarantee that the neural network learning algorithm converges and the tuning of fuzzy infer...