Table 16 Correlation coefficient of linear and quadratic regression models.

Values of linear regression model				Values of quadratic regression model
Topological indices	\(\mathcal{B}\mathcal{P}\)	\(\mathcal{E}\mathcal{V}\)	\(\mathcal{F}\mathcal{P}\)	\(\mathcal{I}\mathcal{R}\)	\(\mathcal{B}\mathcal{P}\)	\(\mathcal{E}\mathcal{V}\)	\(\mathcal{F}\mathcal{P}\)	\(\mathcal{I}\mathcal{R}\)
M\(_{1}\)(G)	0.8837	0.856	0.8818	0.6707	0.9359	0.9131	0.9361	0.7937
M\(_{2}\)(G)	0.867	0.8364	0.8643	0.6676	0.9236	0.9001	0.9224	0.8049
H(G)	0.8905	0.8659	0.8886	0.6738	0.9423	0.9195	0.9424	0.7836
F(G)	0.8692	0.8382	0.8675	0.6435	0.9268	0.9035	0.9273	0.7858
ISI(G)	0.8815	0.8547	0.879	0.6857	0.9334	0.9105	0.9325	0.8047
AZI(G)	0.8617	0.8341	0.8578	0.6882	0.9156	0.8923	0.9120	0.8125
ABC(G)	0.8959	0.8703	0.8946	0.6711	0.9447	0.9220	0.9459	0.7800
HM(G)	0.8831	0.8509	0.8819	0.6731	0.9321	0.9050	0.9335	0.7992
GA(G)	0.8906	0.8659	0.8884	0.6877	0.9408	0.9183	0.9404	0.7970

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