Computing topological indices of probabilistic neural network
Javaid M., Cao J.
© 2017 The Natural Computing Applications Forum A numeric quantity that characterizes the whole structure of a network is called a topological index. In the studies of quantitative structure-activity relationship and quantitative structure-property relationship, the topological indices are utilized to guess the physical features related to the bioactivities and chemical reactivities in certain networks. A neural network is a computer system modeled on the nerve tissue and nervous system. The neural networks are not only studied in Neurochemistry. There are many applications of these networks in different areas of studies such as intrusion detection system, image processing, artificial intelligence, localization, medicine, chemical, and environmental sciences. In this paper, we compute the degree-based topological indices of the probabilistic neural network for the first time. At the end, a numerical comparison between all the indices is also shown with the help of the Cartesian coordinate system.