On Curvilinear Regression Analysis via Newly Proposed Entropies for Some Benzene Models

To avoid exorbitant and extensive laboratory experiments, QSPR analysis, based on topological descriptors, is a very constructive statistical approach for analyzing the numerous physical chemical properties of compounds. Therefore, we presented some new entropy measures which are sum neighborhood degree vertices. Firstly, made partition edges benzene derivatives neighboring vertices then computed version entropies. Secondly, use software SPSS developing correlation between newly introduced entropies physicochemical derivatives. Our obtained results demonstrated that critical temperature C mathvariant="script">T , pressure id="M2"> mathvariant="script">P volume id="M3"> mathvariant="script">V can be predicted through fifth geometric arithmetic entropy, second id="M4"> S K id="M5"> N D respectively. Other remaining characteristics include Gibb’s energy id="M6"> mathvariant="normal">qℰ id="M7"> mathvariant="normal">log P molar refractivity id="M8"> mathvariant="normal">ℳℛ Henry’s law id="M9"> mathvariant="normal">ℋℒ by using sixth id="M10"> entropy.