nowadays, it has demonstrated that viruses can be transmitted by water and foods. therefore, it causes the research to develop for detecting different viruses in water and foods. among foods, milk can transfer potentially pathogenic viruses. on the other hand, to achieve every method for recovery and extraction of viruses in raw milk it needs to know about impact of milk components on viruses. ...

one of the main problems of supply chain network design is uncertainty. to consider this, designing of a three-echelon supply chain in a fuzzy environment is discussed in this paper. since satisfaction of some constraints in supply chain is vital and necessary, so this research proposes a direct solution approach to find the solution which represents the trade-off between feasibility degree of ...

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...

This paper presents a fuzzy-tuned neural network, which is trained by an improved genetic algorithm (GA). The fuzzy-tuned neural network consists of a neural-fuzzy network and a modified neural network. In the modified neural network, a neuron model with two activation functions is used so that the degree of freedom of the network function can be increased. The neural-fuzzy network governs some...

In an earlier companion paper [56] a supervised learning neural network pattern classifier called the fuzzy min-max classification neural network was described. In this sequel, the unsupervised learning pattern clustering sibling called the fuzzy min-max clustering neural network is presented. Pattern clusters are implemented here as fuzzy sets using a membership function with a hyperbox core t...

In this paper, we propose a new approach to critical path analysis in a project network whose activity times are uncertain. The uncertain parameters in the project network are represented by fuzzy numbers. We use fuzzy arithmetic and a fuzzy ranking method to determine the fuzzy critical path of the project network without converting the fuzzy activity times to classical numbers. The proposed m...

A fuzzy neural network and its relevant fuzzy neuron and fuzzy learning algorithm are introduced. An object-oriented implementation of fuzzy neural network in MATLAB environment is realized. Simulations are carried out by SIMULINK. The performance of fuzzy neural network is experimentally compared with other neural networks trained by backpropagation algorithms. It shows better convergence spee...

Awareness of the level of river flow and its fluctuations at different times is one of the significant factor to achieve sustainable development for water resource issues. Therefore, the present study two hybrid models, Wavelet- Adaptive Neural Fuzzy Interference System (WANFIS) and Wavelet- Artificial Neural Network (WANN) are used for flow prediction of Gamasyab River (Nahavand, Hamedan, Iran...

| In this paper we present a new kind of neural network architecture designed for control tasks, which we call fuzzy neural network. The structure of the network can be interpreted in terms of a fuzzy controller. It has a three-layered architecture and uses fuzzy sets as its weights. The fuzzy error backpropagation algorithm, a special learning algorithm inspired by the standard BP-procedure fo...