Abstract
A topological index (TI) is a quantity expressed as a number that help us to catch symmetry of network. With the help of quantitative structure property relationship (QSPR), we can guess physical and chemical properties of several networks. A neural network is a computer system based on the nerve system. There are numerous uses of these systems in different fields of studies but their most critical use to date is in Neurochemistry. In this paper, we will discuss thirteen irregularity indices for probabilistic neural networks (PNN).
Highlights
probabilistic neural networks (PNN) are likewise Parzen window pdf estimator
topological index (TI) stay invariant of two isomorphic graphs and helpful to predict many properties of PNN [1,2,3,4,5,6,7]
Other growing field is Cheminformatics, in which QSAR and quantitative structure property relationship (QSPR) relationship is used to figure out properties of concerned network
Summary
PNN are likewise Parzen window pdf estimator. In last few years these networks are widely used in different problems. Contaminate, TIs are arithmetic value link with graph of PNN and has utilization in different fields of study. TIs stay invariant of two isomorphic graphs and helpful to predict many properties of PNN [1,2,3,4,5,6,7]. Other growing field is Cheminformatics, in which QSAR and QSPR relationship is used to figure out properties of concerned network. In these investigation, a few Physico-chemical properties and TIs are helpful to examine the behavior of compound structures [8,9,10,11,12,13,14,15,16,17]. An other important topological invariant is a symmetric division index which is an excellent descriptor of the aggregate surface area for polychlorobiphenyls [29]
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