Fuzzy neural networks have several features that make them well suited to a wide range þÿ o l knowledge engineering applications. These strengths include fast and accurate learning, good generalisation capabilities, excellent explanation facilities in the fonn of semanticallymeaningful fuzzy rules, and the ability to accommodate both data and existing expert knowledge about the problem under co...

-Fuzzy theory is integrated with Artificial Neural Network to create a bridge safety assessment model, through which the Fuzzy-Neural Network is improved in the light of sample data simulation. First, determine network layers interms of the seven critiria for bridge safety assessment. Then enter sample data at the input layer; study sample at the fuzzy reasoning layer by BP calculation method; ...

Accurately forecasting the foreign exchange rate is important for export-oriented enterprises. For this purpose, a fuzzy and neural approach is applied in this study. In the fuzzy and neural approach, multiple experts construct fuzzy linear regression (FLR) equations from various viewpoints to forecast the foreign exchange rate. Each FLR equation can be converted into two equivalent nonlinear p...

In this paper, an adaptive neuro-fuzzy system, called HyFIS, is proposed to build and optimise fuzzy models. The proposed model introduces the learning power of neural networks into the fuzzy logic systems and provides linguistic meaning to the connectionist architectures. Heuristic fuzzy logic rules and input-output fuzzy membership functions can be optimally tuned from training eramples by a ...

Neural Networks (NN), Type-1 Fuzzy Logic Systems (T1FLS) and Interval Type-2 Fuzzy Logic Systems (IT2FLS) are universal approximators, they can approximate any non-linear function. Recent research shows that embedding T1FLS on an NN or embedding IT2FLS on an NN can be very effective for a wide number of non-linear complex systems, especially when handling imperfect information. In this paper we...

daily constant discharges are needed estimating daily discharge in the hydrological model. the different number of statistical years, statistical deficiencies, and measurement error leads to the formation of time series with an uncommon time base. hence the reconstruction of daily discharge data is of paramount importance. in this research, daily discharge was reconstructed in two stages in one...

Fire alarm system is important in high-rise building. In this paper, a fire alarm system of high-rise building is designed using fuzzy system theory and neural network. The fuzzy system has superiority in inference and the neural network has superiority in learning. The design parameters of the fuzzy system can be adjusted automatically by combining the fuzzy system with the neural network. The...

This paper proposes a new hybrid time series forecasting system which is the fusion of the fuzzy system and the artificial neural network. The proposed fuzzy-neural system consists of 5 layers: the input layer, the fuzzification layer, the inference layer, the hidden layer, and the output layer. The artificial neural network is used as the fuzzy inference engine, while the genetic algorithm is ...

This paper analyzes the performance and practical implementation of fuzzy-neural networks for the autonomous motion of mobile robots. The designed fuzzy-neural controller is a refined version of a conventional fuzzy controller, and was trained to optimize a given cost function minimizing positioning error. It was found that the mobile robot with fuzzy-neural controller presents good positioning...

Aimed at fuzzy clustering based on the generalized entropy, an image segmentation algorithm by joining space information of image is presented in this paper. For solving the optimization problem with generalized entropy’s fuzzy clustering, both Hopfield neural network and multi-synapse neural network are used in order to obtain cluster centers and fuzzy membership degrees. In addition, to impro...