Network-flow problems can be solved by several methods. Labeling techniques can be used to solve wide variety of network problems. A new algorithm to find the fuzzy maximal flow between source and sink was proposed by Kumar et el. [19]. They have represented normal triangular fuzzy numbers as network flow. It is not possible to restrict the membership function to the normal form and proposed th...

In this paper, a hybrid Fuzzy Neural Network (FNN) system for function approximation is presented. The proposed FNN can handle numeric and fuzzy inputs simultaneously. The numeric inputs are fuzzified by input nodes upon presentation to the network while the Fuzzy rule based knowledge is translated directly into network architecture. The connections between input to hidden nodes represent rule ...

Fuzzy logic, neural network, fuzzy-neural networks play an important role in the linguistic modeling of intelligent control and decision making in complex systems. The Fuzzy-Neural Network (FNN) learning represents one of the most effective algorithms to build such linguistic models. This paper proposes an Artificial Immune Algorithm (AIA) based optimal learning fuzzy-neural network (IM-FNN). T...

quality of service (qos) refers to a set of rules or techniques that help the network administrators use the available network resources optimally to manage the effects of congestion and to treat the applications according to their needs. the differentiated services architecture (diffserv) allows providing quality of service to users. the major diffserv premise is that individual flows with sim...

Fuzzy inference systems and neural networks are complementary technologies in the design of adaptive intelligent systems. Artificial Neural Network (ANN) learns from scratch by adjusting the interconnections between layers. Fuzzy Inference System (FIS) is a popular computing framework based on the concept of fuzzy set theory, fuzzy if-then rules, and fuzzy reasoning. A neuro-fuzzy system is sim...

The jamor purpose of the present research is to predict the total stock market index of Tehran Stock Exchange, using a combined method of Wavelet transforms, Fuzzy genetics, and neural network in order to predict the active participations of finance market as well as macro decision makers.To do so, first the prediction was made by neural network, then a series of price index was decomposed by w...

Symmetric polygonal fuzzy number is employed to build an improved feedforward fuzzy neural network (FNN). First, a novel fuzzy arithmetic and extension principle for the polygonal fuzzy numbers is derived. Second, the topological architecture of a three layer feedforward FNN is presented, and the input-output law of this network is systematically studied. Third, a fuzzy BP learning algorithm fo...

introduction according to the shortage of water resources in the world, it seems necessary the use of refined water, particularly in arid and semi-arid areas such as iran. the correct treatment, management and the control of refining process needs to investigate effective parameters in this process precisely. therefore, because of the uncertainty and complexity in refining qualitative parameter...

The purpose of the current research is to provide a performance appraisal system capable of considering the value chain network structure of research and development (R&D) projects for Complex products and systems (CoPS) under uncertainty of data. Therefore, in order to achieve this goal, a network data envelopment analysis (NDEA) approach and the possibilistic programming to provide a new fuzz...