Neutrosophic deep neural network and its application to soil microbe analysis

Abstract

Abstract:An overview of a Neutrosophic Deep Neural Network (NDNN) is given here to illustrate how artificial neuralnetworksandneutrosophicsetscanbecombinedtoprofitfromthecomprehensivetruth,indeterminate,andfalsitydegreesknowninneutrosophiclogic. TheinvestigationdetailshowtheNDNNarchitecturewasgraduallyenrichedfromitsinitialandsimpleststructure,whichwasaNeutrosophicNeuralNetwork(NNN)withonlyaone-layerneuron. Next,itprogressesto an NNN with one layer and one multi-input neuron, and then becomes even more sophisticated as an NNN with onelayer and several multi-input neurons. As a result, the framework concludes with a real NDNN made up of multiplelayers, and every layer includes several multi-input neurons. For each network structure, new sets of formulas are giventoestimatetheparametersofneuralnetworksasneutrosophictripletsforweightsandactivations. TheuseoftheNDNNinsoilmicrobeprocessingisdemonstratedtoproveitsusefulnessinhandlingsituationswithuncertaintyandindeterminacy.