Hybrid quantum inspired neural model for commodity price prediction

Quantum Neural Network (QNN) can improve upon the inadequacies of the classical neural network (CNN). The CNN requires a huge memory and needs more computational power. A new field of computation is emerging which integrates quantum computation with CNN. A quantum inspired hybrid model of quantum neurons and classical neurons is proposed. This paper details an approach, perhaps the first attempt, towards commodities price prediction using this concept is evolved. The commodity price prediction initiates the use of QNN in financial engineering applications.