introductapplication of neural network of multi layers perceptron (mlp) in site selection of municipal solid ‎waste landfilling with emphasis on hydrogeomorphic characteristics (case study: fereydoonshahr city)‎introduction‏:‏cities are at the nexus of a further threat to the environment, namely the production of an increasing ‎quantity and complexity of wastes. the estimated quantity of munici...

Low Probability of Intercept (LPI) radars are developed on an advanced architecture by making use coded waveforms. Detection and classification radar waveforms important in many critical applications like electronic warfare, threat to surveillance. Precise estimation parameter the type waveform will provide information about also helps develop sophisticated intercept receiver. The present work ...

abstract recent interest in describing the spatial distribution patterns of weeds through using interpolation methods has increased to estimate weed seedling density from spatially refferenced data and evaluation of applicable to site-specific weed management. in this research, a multi layer perceptron neural network (mlpnn) model was developed to predict the spatial distribution of h. glaucum ...

In this paper, we report on experiments in which we used neural networks for statistical anomaly intrusion detection systems. The five types of neural networks that we studied were: Perceptron; Backpropagation; PerceptronBackpropagation-Hybrid; Fuzzy ARTMAP; and Radial-Based Function. We collected four separate data sets from different simulation scenarios, and these data sets were used to test...

Accurate models of Overcurrent (OC) with inverse time relay characteristics play an important role for coordination of power system protection schemes. This paper proposes a new method for modeling OC relays curves. The model is based on fuzzy logic and artificial neural networks. The feed forward multilayer perceptron neural network is used to calculate operating times of OC relays for various...