The Development of Deep Learning Methods to Select Passion Fruit for the Ageing Society

Abstract

The objective of this research is to develop a decision support framework using deep learning methods to select passion fruit for the ageing society. Many substances present in passion fruit such as vitamin A, vitamin C, and vitamin E can contribute to beneficial effects in our body. Especially, it could help to reduce the risk of cardiovascular diseases suitable for the ageing society. It is expected that 4-age levels of passion fruit for three groups of ageing society can be classified and suggested by using multi-layer perceptron neural network (MLPNN) architectures in Python program. The implications of the study are that selecting age levels of passion fruit is appropriate for three ageing society groups. The deep neural network model can generate the accuracy of a trained dataset is 73.9 % and a tested dataset is 72.5%. This model is used to create the computer software which is convenient for the selection of passion fruit or other fruits for the fruit juice industry.