Literature DB >> 18267711

Backpropagation neural nets with one and two hidden layers.

J de Villiers1, E Barnard.   

Abstract

The differences in classification and training performance of three- and four-layer (one- and two-hidden-layer) fully interconnected feedforward neural nets are investigated. To obtain results which do not merely reflect performance on a particular data set, the networks are trained on various distributions, which are themselves drawn from a distribution of distributions. Experimental results indicate that four-layered networks are more prone to fall into bad local minima, but that three- and four-layered networks perform similarly in all other respects.

Year:  1993        PMID: 18267711     DOI: 10.1109/72.182704

Source DB:  PubMed          Journal:  IEEE Trans Neural Netw        ISSN: 1045-9227


  8 in total

1.  An Evaluation of Artificial Neural Networks in Predicting Pancreatic Cancer Survival.

Authors:  Steven Walczak; Vic Velanovich
Journal:  J Gastrointest Surg       Date:  2017-08-03       Impact factor: 3.452

2.  Classification of normal and abnormal electrogastrograms using multilayer feedforward neural networks.

Authors:  Z Lin; J Maris; L Hermans; J Vandewalle; J D Chen
Journal:  Med Biol Eng Comput       Date:  1997-05       Impact factor: 2.602

3.  Effects of Input Parameter Range on the Accuracy of Artificial Neural Network Prediction for the Injection Molding Process.

Authors:  Junhan Lee; Dongcheol Yang; Kyunghwan Yoon; Jongsun Kim
Journal:  Polymers (Basel)       Date:  2022-04-23       Impact factor: 4.967

4.  EEG power spectrum and neural network based sleep-hypnogram analysis for a model of heat stress.

Authors:  Rakesh Kumar Sinha
Journal:  J Clin Monit Comput       Date:  2008-06-03       Impact factor: 2.502

5.  Backpropagation artificial neural network classifier to detect changes in heart sound due to mitral valve regurgitation.

Authors:  Rakesh Kumar Sinha; Yogender Aggarwal; Barda Nand Das
Journal:  J Med Syst       Date:  2007-06       Impact factor: 4.460

6.  Artificial neural network detects changes in electro-encephalogram power spectrum of different sleep-wake states in an animal model of heat stress.

Authors:  R K Sinha
Journal:  Med Biol Eng Comput       Date:  2003-09       Impact factor: 3.079

7.  A preliminary study on automated freshwater algae recognition and classification system.

Authors:  Mogeeb A A Mosleh; Hayat Manssor; Sorayya Malek; Pozi Milow; Aishah Salleh
Journal:  BMC Bioinformatics       Date:  2012-12-13       Impact factor: 3.169

8.  A Data-Driven Investigation on Surface Electromyography Based Clinical Assessment in Chronic Stroke.

Authors:  Fuqiang Ye; Bibo Yang; Chingyi Nam; Yunong Xie; Fei Chen; Xiaoling Hu
Journal:  Front Neurorobot       Date:  2021-07-15       Impact factor: 2.650

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.