Title of article :
M-POLYNOMIAL METHOD FOR TOPOLOGICAL INDICES OF 3-LAYERED PROBABILISTIC NEURAL NETWORKS
Author/Authors :
JAVAID, M Department of Mathematics - School of Science - University of Management and Technology (UMT) - Lahore, Pakistan , RAHEEM, A Department of Mathematics - National University of Singapore, Singapore , ABBAS, M Department of Mathematics - GC University - Lahore, Pakistan , CAO, J School of Mathematics - and Research Center for Complex Systems and Network Sciences - Southeast University, Nanjing, China
Abstract :
A molecular network can be uniquely identified 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 first 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 find the better one among all the obtained results.
Keywords: M-polynomial, Degree-based TI’s, Networks, Probabilistic neural network.
Keywords :
M-polynomial , Degree-based TI’s , Networks , Probabilistic neural network
Journal title :
Turkish World Mathematical Society Journal of Applied and Engineering Mathematics
