نتایج جستجو برای: multi layer perceptron network

تعداد نتایج: 1313627  

2016
Imen Triki

This paper compares, for a microfinance institution, the performance of two individual classification models: Logistic Regression (Logit) and Multi-Layer Perceptron Neural Network (MLP), to evaluate the credit risk problem and discriminate good creditors from bad ones. Credit scoring systems are currently in common use by numerous financial institutions worldwide. However, credit scoring using ...

This paper presents the prediction of vehicle's velocity time series using neural networks. For this purpose, driving data is firstly collected in real world traffic conditions in the city of Tehran using advance vehicle location devices installed on private cars. A multi-layer perceptron network is then designed for driving time series forecasting. In addition, the results of this study are co...

F Nazari M.H Abolbashari,

This study presents a new procedure based on Artificial Neural Network (ANN) for identification of double cracks in Functionally Graded Beams (FGBs). A cantilever beam is modeled using Finite Element Method (FEM) for analyzing a double-cracked FGB and evaluation of its first four natural frequencies for different cracks depths and locations. The obtained FEM results are verified against availab...

1999
B. Solaiman M. C. Mouchot R. K. Koffi

In this study, the application of a combined segmentation method using the CannyDeriche filter and a Multi Layer Perceptron neural network is considered. The segmentation of five LANDSAT spectral bands is conducted. Obtained segmented images are combined using a multi experts approach in order to improve the segmentation quality and to preserve the land cover regions.

Journal: :Neurocomputing 2003
Walmir M. Caminhas Douglas A. G. Vieira João A. Vasconcelos

In this paper, both the architecture and learning procedure underlying the parallel layer perceptron is presented. This topology, di1erent to the previous ones, uses parallel layers of perceptrons to map nonlinear input–output relationships. Comparisons between the parallel layer perceptron, multi-layer perceptron and ANFIS are included and show the e1ectiveness of the proposed topology. c © 20...

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