For decades, scientists have studied the blast wave profile produced by an explosive detonation. Based on a significant amount of experimental data, propagation has been predicted under given parameters. However, most studies only looked at central point initiation for spherical form explosives. The purpose this research is to compare prediction performance peak overpressure based type explosiv...

In object detection, spatial knowledge assisted systems are effective. Object detection is a main and challenging issue to analyze object-related information. Several existing techniques were developed consider the problem as classification perform feature selection classification. But these still face, less computational efficiency high time consumption. This paper resolves above limitations u...

Earthquake disasters can cause enormous social and economic damage, therefore the sustainability of infrastructure requires mitigation earthquake consequences. In seismic design infrastructures, it is essential to estimate response site during earthquake. Geotechnical engineers have developed quantitative methods for analyzing ground response. This study proposes a multilayer perceptron (MLP) m...

This paper considers the similarity between two measures of air pollution/quality control, on the one hand, and widely used indicators of life quality and welfare, on the other. We have developed a multi-layer perceptron neural network system which is trained to predict the measurements of air quality (emissions of sulphur and nitrogen oxides), using Eurostat data for 34 countries. We used life...

In this paper, we propose to study four meteorological and seasonal time series coupled with a multi-layer perceptron (MLP) modeling. We chose to combine two transfer functions for the nodes of the hidden layer, and to use a temporal indicator (time index as input) in order to take into account the seasonal aspect of the studied time series. The results of the prediction concern two years of me...

The classification of remote sensing images performed with different classifiers usually produces different results. The aim of this paper is to investigate whether the outputs of different soft classifications may be combined to increase the classification accuracy, using the uncertainty information to choose the best class to assign to each pixel. If there is disagreement between the outputs ...

Performance of neural-networks learning is known to be sensitive to the initial weight setting and architecture|number of hidden layers and neurons in these layers. This shortcoming can be alleviated if some approximation of the target concept in terms of a logical description is available. The paper reports a successful attempt to initialize neural networks by decision-tree generators. The sys...