The unavailability of sufficient data and uncertainty in modeling, some techniques, and decision-making processes play a significant role in many engineering and management problems.  Attain to sure solutions for a problem under accurate consideration is essential.  In this paper, an application of fuzzy inference system for modeling the indeterminacy involved in the problem of HSE risk assessm...

This paper discusses design of adaptive Genetic Algorithms (GA) on the base Fuzzy Inference System (FIS). There are two possible ways for integrating Fuzzy Logic and Genetic Algorithms. One involves the applications of Genetic Algorithms for solving optimization and search problem related with fuzzy systems. The another, the use of “fuzzy tools” for modeling and adapting Genetic Algorithm contr...

One of the best ways for better understanding of biological experiments is mathematical modeling. Modeling cancer is one of the complicated biological modeling that has uncertainty. Therefore, fuzzy models have studied because of their application in achievement uncertainty in modeling. Overall, the main purpose of this modeling is creating a new view of complex phenomena. In this paper, fuzzy ...

In this paper, dynamic modeling of a Vestas 660 kW wind turbine and its validation are performed based on operational data extracted from Eoun-Ebn-Ali wind farm in Tabriz, Iran. The operational data show that the turbine under study, with a classical PI controller, encounters high fluctuations when controlling the output power at its rated value. The turbine modeling is performed by deriving th...

The dynamic behavior of an industrial tunneltype furnace is of the fundamental importance for the quality of the processed products. The knowledge of the furnace dynamics can make the control of the system easier as well as it can eliminate certain operational problems. The various subsystems existent in a tunnel-type furnace are usually controlled by conventional techniques and independent con...

In this manuscript, the reliability of a robotic system has been analyzed using the available data (containing vagueness, uncertainty, etc). Quantification of involved uncertainties is done through data fuzzification using triangular fuzzy numbers with known spreads as suggested by system experts. With fuzzified data, if the existing fuzzy lambda–tau (FLT) technique is employed, then the comput...

The composition of simple local models for approximating complex nonlinear mappings is a common practice in recent modeling and control literature. This paper presents a comparative analysis of two different local approaches: the neuro-fuzzy inference system and the lazy learning approach. A neuro-fuzzy system is an hybrid representation which combines the linguistic description of fuzzy infere...

In this paper a novel method for designing hierarchical fuzzy logic Systems are investigated. A new method using genetic algorithms for design of hierarchical fuzzy logic systems are proposed. The proposed method is then applied to financial modelling and prediction. A hierarchical fuzzy logic system is developed to predict quarterly interest rates in Australia. The new method proposed determin...