aspg-3-552-1791417114 20261007235154 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group Fusion: Practice and Applications FPA 2770-0070 2692-4048 2020 2 1 Shaymaa Adnan Abdulrahman Department of computer Engineering, Imam Ja’afar Al-Sadiq University, Baghdad, Iraq Rafah Amer Jaafar Department of computer Engineering, Imam Ja’afar Al-Sadiq University, Baghdad, Iraq Alcoholism may be recognized with the use of (EEG) analyzing signals. None-the-less, the analysis of the multi-channel signals of EEG is a complicated issue that usually needs performing complex computation operations and takes quite a long time to execute. The presented research will propose 13 optimal channel to feature extraction. In this research, an innovative horizontal visibility graph entropy (HVGE) method has been proposed for evaluating signals of EEG from controlled drinkers and alcoholic subjects and comparing against an approach of sample entropy (SaE). Values of HVGE and SaE have been obtained from 1200 records of bio-medical signals. While in classification step using SVM as classifier. 2020 14 21 552 https://creativecommons.org/licenses/by/4.0/ 10.54216/FPA.020103 https://www.americaspg.com/journal/3/article/552 https://www.americaspg.com/storage/3461.pdf