Semnan University Press Journal of Modeling in Engineering 2008-4854 21 73 1402 04 01 Providing an expert system with the help of Arithmetic meta-heuristic algorithm to diagnose the infectious disease of covid-19 Providing an expert system with the help of Arithmetic meta-heuristic algorithm to diagnose the infectious disease of covid-19 47 61 7795 10.22075/jme.2023.27986.2312 FA Faezeh Ebrahimi Allameh Mohaddes Nouri University-Nour-Computer group. Alireza Azari Moghaddam Maziar Higher Education Institute-Nour-Computer Faculty Mohsen Nejad Khairullah Allameh Mohaddes Nouri University-nour-Computer Faculty Journal Article 1401 05 11 The last two years have been the most critical and critical period of the Covid-19 pandemic.This disease has affected most aspects of life around the world. From a clinical point of view, several methods are available for early diagnosis of the disease, but the capabilities of these methods have been limited. As a result, many studies have been conducted to automatically diagnose the disease. Artificial intelligence has provided potential technical solutions to the medical community to make quick diagnosis based on clinical symptoms.In this research, the patient's clinical symptoms (fever, cough, sore throat, shortness of breath, weakness, sense of taste and smell, environment) are examined with the help of a questionnaire,then the input data is examined by one of rule based system or fuzzy system methods, in the fuzzy method with the help of arithmetic meta-heuristic algorithm. The optimized weight parameter is then applied to the data with the optimized weight fuzzy logic. At the end, the output will be shown as healthy person, weak corona, middel corona, high corona. This article is based on several databases, in which about 600 data have been completed by individuals through questionnaires, 2000 data have been published by the World Health Organization for corona patients, and about 400 data have been provided through hospital data. It was observed that in this system, the accuracy rate is equal to 98%, sensitivity is 100%, specificity is 98% and the F- score is 95%. The last two years have been the most critical and critical period of the Covid-19 pandemic.This disease has affected most aspects of life around the world. From a clinical point of view, several methods are available for early diagnosis of the disease, but the capabilities of these methods have been limited. As a result, many studies have been conducted to automatically diagnose the disease. Artificial intelligence has provided potential technical solutions to the medical community to make quick diagnosis based on clinical symptoms.In this research, the patient's clinical symptoms (fever, cough, sore throat, shortness of breath, weakness, sense of taste and smell, environment) are examined with the help of a questionnaire,then the input data is examined by one of rule based system or fuzzy system methods, in the fuzzy method with the help of arithmetic meta-heuristic algorithm. The optimized weight parameter is then applied to the data with the optimized weight fuzzy logic. At the end, the output will be shown as healthy person, weak corona, middel corona, high corona. This article is based on several databases, in which about 600 data have been completed by individuals through questionnaires, 2000 data have been published by the World Health Organization for corona patients, and about 400 data have been provided through hospital data. It was observed that in this system, the accuracy rate is equal to 98%, sensitivity is 100%, specificity is 98% and the F- score is 95%. https://modelling.semnan.ac.ir/article_7795_b6316875957c2abc3c47e20f6e026a42.pdf