M-POLYNOMIAL METHOD FOR TOPOLOGICAL INDICES OF 3-LAYERED PROBABILISTIC NEURAL NETWORKS
M. Javaid, A Raheem, M. Abbas, J. Cao
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Abstract
A molecular network can be uniquely identied by a number, polynomial or matrix. A topological index (TI) is a number that characterizes a molecular network completely which is used to predict the physical features of the certain changes such as bioactivities and chemical reactivities in the chemical compound. Javaid and Cao [Neural Comput. and Applic., 30(2018), 3869-3876] studied the rst Zagreb index, second Zagreb index, general Randic index, and augmented Zagreb index for the 3-layered probabilistic neural networks (PNN). In this paper, we prove the M-polynomial of the 3-layered PNN and use it as a latest developed tool to compute the certain degree based TI's. At the end, a comparison is also shown to nd the better one among all the obtained results.
Keywords
M-polynomial, Degree-based TI's, Networks, Probabilistic neural network.