An increasing number of Taiwanese universities are improving operational performance through innovation and total quality management (TQM). In addition, the National Quality Award (NQA), which is based on TQM, is now used to evaluate quality performance in various industries in Taiwan. Thus, several models for performance measurement have been proposed in recent years. However, these models do ...

A fuzzy neural network, Falcon-MART, is proposed in this paper. This is a modi®cation of the original Falcon-ART architecture. Both Falcon-ART and Falcon-MART are fuzzy neural networks that can be used as fuzzy controllers or applied to areas such as forgery detection, pattern recognition and data analysis. They constitute a group of hybrid systems that incorporate fuzzy logic into neural netwo...

Wireless sensor network is used to sense the objective physical world, access to the information of the physical world. Fuzzy cluster analysis, it is involving the fuzzy boundaries between things of things according to certain requirements for the classification of mathematical methods. Wireless sensor network is used to sense the objective physical world, access to the information of the physi...

in this paper, we introduce a takagi-sugeno (ts) fuzzy model which is derived from a typical multi-layer perceptron neural network (mlp nn). at first, it is shown that the considered mlp nn can be interpreted as a variety of ts fuzzy model. it is discussed that the utilized membership function (mf) in such ts fuzzy model, despite its flexible structure, has some major restrictions. after modify...

This paper proposes a reinforcement fuzzy adaptive learning control network (RFALCON), constructed by integrating two fuzzy adaptive learning control networks (FALCON), each of which has a feedforward multilayer network and is developed for the realization of a fuzzy controller. One FALCON performs as a critic network (fuzzy predictor), the other as an action network (fuzzy controller). Using t...

In this paper, we introduce a Takagi-Sugeno (TS) fuzzy model which is derived from a typical Multi-Layer Perceptron Neural Network (MLP NN). At first, it is shown that the considered MLP NN can be interpreted as a variety of TS fuzzy model. It is discussed that the utilized Membership Function (MF) in such TS fuzzy model, despite its flexible structure, has some major restrictions. After modify...

in this paper, a novel hybrid method based on learning algorithmof fuzzy neural network and newton-cotesmethods with positive coefficient for the solution of linear fredholm integro-differential equation of the second kindwith fuzzy initial value is presented. here neural network isconsidered as a part of large field called neural computing orsoft computing. we propose alearning algorithm from ...

this paper intends to offer a new iterative method based on articial neural networks for finding solution of a fuzzy equations system. our proposed fuzzied neural network is a ve-layer feedback neural network that corresponding connection weights to output layer are fuzzy numbers. this architecture of articial neural networks, can get a real input vector and calculates its corresponding fu...

In a fuzzy project network, the higher risk path is called possible critical path. Secondary critical path is one of the possible critical path in fuzzy project network and it plays an important role in the project scheduling, risk analysis and time-cost trade-off problems in fuzzy environment. In this paper, triangular fuzzy numbers are used to express the operation times for all activities in...

In general, high-speed network traffic is a complex, nonlinear, nonstationary process and is significantly affected by immeasurable parameters and variables. Thus, a precise model of this process becomes increasingly difficult as the complexity of the process increases. Recently, fuzzy modeling has been found to be a powerful method to effectively describe a real, complex, and unknown process w...