In this article we are going to discuss the improvement of the multi classes’ classification problem using multi layer Perceptron. The considered approach consists in breaking down the n-class problem into two-classes’ subproblems. The training of each two-class subproblem is made independently; as for the phase of test, we are going to confront a vector that we want to classify to all two clas...

Background: Human brucellosis is widespread in Fars province. The present study aimed to investigate the effect of climate on its incidence and determine the areas prone to the infection.Methods: Monthly meteorological data and the incidence rate of human brucellosis during 2009-2015 were collected and their correlation was studied using Pearson’s correlation coefficient. Additionally, th...

Load forecasting has become one of the major areas of research in electrical engineering and is an important problem in operation and planning of electric power generation. Load forecasting is the technique for prediction of electrical load. STLF (Short term load forecast) is essential for Power system planning. In a deregulated market it is much need for a generating company to know about the ...

Multi layer perceptron with back propagation algorithm is popular and more used than other neural network types in various fields of investigation as a non-linear predictor. Though MLP can solve complex and non-linear problems, it cannot use missing data for training directly. We propose a training algorithm with incomplete pattern data using conventional MLP network. Focusing on the fact that ...

Within forest growth modeling LOGIT models are used to predict individual tree mortality. In this paper we present, Multi-Layer Perceptron, Learning Vector Quantization and Cascade Correlation networks as different formalisms for mortality predictions. The data set for parameterizing the LOGIT model and training the different neural network types comes from the Austrian National Forest Inventor...

The subject of this thesis is the original study of the application of the multi-layer perceptron architecture to channel equalization in digital communications systems. Both theoretical analyses and simulations were performed to explore the performance of the perceptron-based equalizer (including the decision feedback equalizer). Topics covered include the factors that affect performance of th...