Sehraneh Ghaemi

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University course timetabling is a NP-hard problem which is very difficult to solve by conventional methods. A highly constrained combinatorial problem, like the timetable, can be solved by evolutionary methods. In this paper, among the evolutionary computation (EC) algorithms, a genetic algorithm (GA) for solving university course timetabling problems is(More)
In this paper, the type-2 fuzzy logic system (T2FLS) controller using the feedback error learning (FEL) strategy has been proposed for load frequency control (LFC) in the restructure power system. The original FEL strategy consists of an intelligent feedforward controller (INFC) (i.e. artificial neural network (ANN)) and the conventional feedback controller(More)
This paper proposes a novel approach for training of proposed recurrent hierarchical interval type-2 fuzzy neural networks (RHT2FNN) based on the square-root cubature Kalman filters (SCKF). The SCKF algorithm is used to adjust the premise part of the type-2 FNN and the weights of defuzzification and the feedback weights. The recurrence property in the(More)
In this paper, using artificial neural network ANN for tracking of maximum power point is discussed. Error back propagation method is used in order to train neural network. Neural network has advantages of fast and precisely tracking of maximum power point. In this method neural network is used to specify the reference voltage of maximum power point under(More)
The study of human behavior during driving is of primary importance for the improvement of drivers' security. This study is complex because of numerous situations in which the driver may be involved. In this paper, we propose a hierarchical fuzzy system for human in a driver-vehicle-environment system to model takeover by different drivers. The driver’s(More)