Deep Learning in Solving Mathematical Equations

Solving a mathematical equation can be a tough task. There is a need for employing deep learning in this field. Hence, it can be easier to solve mathematical equations. Deep networks have been applied into various fields and showed a great performance in terms of accurate generalization. In this paper, a deep network, named stacked auto-encoder (SAE) with two hidden layers is trained to learn solving mathematical equations. The network is trained and tested using 200 different equations, where 100 are used for training and 100 for testing. Experimentally, the network showed good generalization accuracy in predicting the answers of solving the mathematical equations which were not used during the training of the network.