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...

Owing to a heightened necessity, the consumption rate of electronic items has increased exponentially in recent decades, resulting huge quantities waste (e-waste). Though increasing e-waste many adverse impacts, it also provides an ample opportunity recover value from through circular economy (CE) practices. However, adoption CE practices is jeopardised by myriad barriers. This paper wishes ide...

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...

ABSTRACT Global warming is the today’s important problem for all over the world. Due to the global warming, countries come face to face with lots of problems such as shortage of clean and usable water, erosion, usage of natural resources, and climatic problems. That’s why; in this paper, we proposed a model for selection of the utilization strategies for water resources in Turkey by using analy...

In this paper, a multi-stage face detection method using hybrid neural networks is presented. The method consists of three stages: preprocessing, feature extraction and pattern classification. We introduce an adaptive filtering technique which is based on a skin-color analysis using fuzzy minmax(FMM) neural networks. A modified convolutional neural network(CNN) is used to extract translation in...