Comparison of Multi Layer Perceptron and Jordan Elman Neural Networks for Diagnosis of Hypertension


Turk F., BARIŞÇI N. , Ciftci A., Ekmekci Y.

INTELLIGENT AUTOMATION AND SOFT COMPUTING, vol.21, no.1, pp.123-134, 2015 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 21 Issue: 1
  • Publication Date: 2015
  • Doi Number: 10.1080/10798587.2014.959312
  • Title of Journal : INTELLIGENT AUTOMATION AND SOFT COMPUTING
  • Page Numbers: pp.123-134

Abstract

In this study, from 150 individuals over the age of 30 taken no drugs, sex, age, height, weight, HDL, LDL, Triglyceride, smoking and uric acid were measured. 65 of them are normal but 85 consist of the patients. This data was transferred to the computer by processing methods of quantitative analysis. Data obtained of each patient was applied Artificial Neural Network (ANN) models. The results obtained will be classified as either normal or the patient. Using Multi Layer Perceptron (MLP) neural network, 80.4% of patient individuals and 81.8% of normal individuals were classified correctly. Using Jordan Elman neural network, 85.3% of the patient individuals and 87.8% of normal individuals were classified correctly.