The neural network MolNet prediction of alkane enthalpies Original Research Article

MolNet, a new type of multi-layer feedforward neural network, is presented together with its application to the computation of alkane enthalpies. The MolNet neural network changes its topology (the number of neurons in the input and hidden layers, together with the number and type of connections) according to the molecular structure of the chemical compound presented to the network. The structure of each molecule is encoded in the corresponding molecular graph that is used to set the MolNet topology. Each atom from the molecular graph has a corresponding neuron in the input and hidden layers, respectively. Three structural descriptors derived from the molecular graph are used as input data for the first layer of neurons, namely the degree, the distance sum, and the reciprocal distance sum.