Françoise Brouaye

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—This work presents the results of the studies concerning the application of different neural network training algorithms to enhance the prediction of a radio network planning tool. Investigations are made on a hybrid model that combines the a-priori information in form of simulation results with the a-posteriori knowledge contained in measurement data. The(More)
— We have used measurements taken on real network to enhance the performance of our radio network planning tool. A distribution learning technique is adopted to realize this challenged task. To ensure better generalization capabilities of the learning algorithm, a preprocessing of data is required and involves the use of a clustering algorithm that divides(More)
Till now Cancer is a big question for scientific community cause of no existing treatments could solve the problems related to this dreadful disease. Research is in well progress since half century but it failed to give an accurate solution to fight against it. The development of technology in science day night tries to develop new methods of treatment. One(More)
— We propose a method to enhance the quality and precision of prediction results using measurements in the context of radio network modelling. The proposed method involves the use of an Independent Component Analysis (ICA) block and a MultiLayer Perceptron (MLP) Artificial Neural Network (ANN). The role of the ICA block is to make the variables at the input(More)
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