in today’s business competitive world, decision makers of companies try to employ standard, efficient, theoretical and operational proven methods as a competitive advantage for making their critical strategic business decisions in order to survive in their industry. in this paper, a hybrid model based on fuzzy analytic hierarchy process (fahp) and artificial neural network (ann) is presented. t...

Finding the collapse susceptible portion of a power system is one of the purposes of voltage stability analysis. This part which is a voltage control area is called the voltage weak area. Determining the weak area and adjecent voltage control areas has special importance in the improvement of voltage stability. Designing an on-line corrective control requires the voltage weak area to be determi...

Finding the collapse susceptible portion of a power system is one of the purposes of voltage stability analysis. This part which is a voltage control area is called the voltage weak area. Determining the weak area and adjecent voltage control areas has special importance in the improvement of voltage stability. Designing an on-line corrective control requires the voltage weak area to be determi...

in this study, several data-driven techniques including system identification, adaptive neuro-fuzzy inference system (anfis), artificial neural network (ann) and wavelet-artificial neural network (wavelet-ann) models were applied to model rainfall-runoff (rr) relationship. for this purpose, the daily stream flow time series of hydrometric station of hajighoshan on gorgan river and the daily rai...

To use fuzzy controllers for automization tasks appropriate fuzzy sets and fuzzy rules have to be deened. This can be diicult in some domains, and the resulting controller has to be tuned. Neuro{fuzzy models can help in this tuning process by adapting fuzzy sets and creating fuzzy rules. Combinations of neural networks and fuzzy controllers are suitable if there is only partial knowledge in the...

Software estimation accuracy is among the greatest challenges for software developers. This study aimed at building and evaluating a neuro-fuzzy model to estimate software projects development time. The forty-one modules developed from ten programs were used as dataset. Our proposed approach is compared with fuzzy logic and neural network model and Results show that the value of MMRE (Mean of M...

In this paper, a framework of a unified neural and neuro-fuzzy approach to integrate implicit and explicit knowledge in hybrid intelligent systems is presented. In the developed hybrid system, training data used for neural and neuro-fuzzy models represents implicit domain knowledge. On the other hand, the explicit domain knowledge is represented by fuzzy rules, directly mapped into equivalent c...

optimization of machining parameters is very important and the main goal in every machining process. surface finishing prediction is a pre-requirement to establish a center for automatic machining operations. in this research, a neuro-fuzzy approach is used in order to model and predict the surface roughness in dry turning. this approach has both the learning capability of neural network and li...

Motion control of mobile robots is a typical nonlinear tracking control issue and has been discussed with different control schemes such as PID, GPC, sliding mode, predictive control etc[1]-[3]. Intelligent control techniques, based on neural networks and fuzzy logic, have also been developed for path tracking control of mobile robots[4][5]. While conventional neural networks have good ability ...