2019
DOI: 10.1088/1757-899x/551/1/012072
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Flower Pollination Neural Network For Heart Disease Classification

Abstract: Heart Disease are among the leading cause of death worldwide. The application of artificial neural network as decision support tool for heart disease detection have been previously proposed. However, artificial neural network using conventional back propagation algorithm for error minimization and these algorithm tend to stuck at local minima. This paper proposed the use of flower pollination algorithm as a substitute to conventional back propagation algorithm for error minimization. Heart disease dataset obta… Show more

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Cited by 6 publications
(1 citation statement)
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“…Additionally, FPA was applied to update the Probabilistic Neural Network (PNN) weights in classification problems and produced better results than PNN on all 11 datasets [7]. Yazid www.ijacsa.thesai.org et al [15] used FPNN, which combines FPA and PNN, to classify heart diseases and found it to have higher accuracy than a standard backpropagation neural network based on results from four UCI datasets.…”
Section: Introductionmentioning
confidence: 99%
“…Additionally, FPA was applied to update the Probabilistic Neural Network (PNN) weights in classification problems and produced better results than PNN on all 11 datasets [7]. Yazid www.ijacsa.thesai.org et al [15] used FPNN, which combines FPA and PNN, to classify heart diseases and found it to have higher accuracy than a standard backpropagation neural network based on results from four UCI datasets.…”
Section: Introductionmentioning
confidence: 99%