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The main problem for Supervised Multi-layer Neural Network (SMNN) model such as Back propagation network lies in finding the suitable weights during training in order to improve training time as well as achieve high accuracy. The important issue in the training process of the existing SMNN model is initialization of the weights which is random and creates(More)
—Learning is the important property of Back Propagation Network (BPN) and finding the suitable weights and thresholds during training in order to improve training time as well as achieve high accuracy. Currently, data pre-processing such as dimension reduction input values and pre-training are the contributing factors in developing efficient techniques for(More)
—Intelligent multi agent systems have great potentials to use in different purposes and research areas. One of the important issues to apply intelligent multi agent systems in real world and virtual environment is to develop a framework that support machine learning model to reflect the whole complexity of the real world. In this paper, we proposed a(More)
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