This paper describes the fuzzy modeling of permanent magnet generator for studying its mechanical dynamic analysis. Firstly electromagnetic torque analysis of the generator is carried out using finite element based package. Then fuzzy model of the generator is developed. Performance was evaluated by comparing, integrated fuzzy model, individual fuzzy model and finite element model for the gener...

Fuzzy logic is a powerful tool to model knowledge uncertainty, measurements imprecision, and vagueness. However, there is another type of vagueness that arises when data have multiple forms of expression that fuzzy logic does not address quite well. This is the case for multiple instance learning problems (MIL). In MIL, an object is represented by a collection of instances, called a bag. A bag ...

Neuro-fuzzy inference systems have been used in many areas in civil engineering applications. A stability assessment model for epimetamorphic rock slopes has been developed by using Adaptive Neuro-Fuzzy Inference System (ANFIS) for its capacity of dynamic nonlinear analyses. In the present study the inference system is employed to predict the stability of the slope by choosing bulk density γ, t...

Short term prediction of traffic flow is one of the most essential elements of all proactive traffic control systems. Although various methodologies have been applied to forecast traffic parameters, several researchers have showed that compared with the individual methods, hybrid methods provide more accurate results . These results made the hybrid tools and approaches a more common method for ...

In complex manufacturing, the system parameters have dynamic and nonlinear characters. Existing parameters setting methods show low efficiency and accuracy, and some setting experience accumulated in engineering practice can not be fully used. Therefore, an online parameter setting method with improved adaptive neuro-based fuzzy inference model is proposed in this paper. The advantages of ANFIS...

Precise control of electro-hydraulic actuator (EHA) system has been an interesting subject due to its nonlinearities and uncertainties characteristics. Good control can be designed when precise model of the system is available. Linear ARX modelling has widely been applied and satisfying result has been obtained, through linearization process. The objective of this paper is to compare ARX model ...

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 paper, two different hybrid intelligent systems are applied to develop practical soft identifiers for modeling the tool-tissue force as well as the resulted maximum local stress in laparoscopic surgery. To conduct the system identification process, a 2D model of an in vivo porcine liver was built for different probing tasks. Based on the simulation, three different geometric features, i...

The prediction of groundwater quality is very important for the management of water resources and environmental activities. The present study has integrated a number of methods such as Geographic Information Systems (GIS) and Artificial Intelligence (AI) methodologies to predict groundwater quality in Kerman plain (including HCO3-, concentrations and Electrical Conductivity (EC) of groundwater)...

In this study, EEG signals were classified by using the average powers extracted by means of the rectangle approximation window based average power method from the power spectral densities of frequency sub-bands of the signals and two different artificial neural networks (ANNs) which are adaptive neuro-fuzzy inference system (ANFIS) and multilayer perceptron neural network (MLPNN). In order to ...