Topological properties of four-layered neural networks

• Autorzy: Javaid M. , Abbas M. , Liu Jia-Bao , Teh W. C. , Cao Jinde

Identyfikatory

DOI

10.2478/jaiscr-2018-0028

• Języki publikacji: EN

Abstrakty

EN

A topological property or index of a network is a numeric number which characterises the whole structure of the underlying network. It is used to predict the certain changes in the bio, chemical and physical activities of the networks. The 4-layered probabilistic neural networks are more general than the 3-layered probabilistic neural networks. Javaid and Cao [Neural Comput. and Applic., DOI 10.1007/s00521-017-2972-1] and Liu et al. [Journal of Artificial Intelligence and Soft Computing Research, 8(2018), 225-266] studied the certain degree and distance based topological indices (TI’s) of the 3-layered probabilistic neural networks. In this paper, we extend this study to the 4-layered probabilistic neural networks and compute the certain degree-based TI’s. In the end, a comparison between all the computed indices is included and it is also proved that the TI’s of the 4-layered probabilistic neural networks are better being strictly greater than the 3-layered probabilistic neural networks.

Słowa kluczowe

EN

degree of node; topological properties; neural network; probabilistic neural; network

• Wydawca: University of Social Sciences
• Czasopismo: Journal of Artificial Intelligence and Soft Computing Research
• Rocznik: 2019
• Tom: Vol. 9, No. 2
• Strony: 111--122
• Opis fizyczny: Bibliogr. 51 poz., rys.

Twórcy

autor

Javaid M.

• Department of Mathematics, School of Science, University of Management and Technology, Lahore, Pakistan

autor

Abbas M.

• Department of Mathematics, GC University, Lahore 54000, Pakistan

autor

Liu Jia-Bao

• School of Mathematics and Physics, Anhui Jianzhu University, Hefei, P.R. China

autor

Teh W. C.

• School of Mathematical Sciences, Universiti Sains Malaysia, 11800 USM

autor

Cao Jinde

• School of Mathematics, Southeast University, Nanjing, Jiangsu, 210096, P.R. China

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Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).