Y. Kravchenko, O. Leshchenko, N. Dakhno, V. Deinega, H. Shevchenko, Oleksandr Trush
{"title":"Intellectual Fuzzy System Air Pollution Control","authors":"Y. Kravchenko, O. Leshchenko, N. Dakhno, V. Deinega, H. Shevchenko, Oleksandr Trush","doi":"10.1109/ATIT50783.2020.9349334","DOIUrl":null,"url":null,"abstract":"The paper investigates the problem of using fuzzy logic to build intelligent decision-making systems. The directions of application of fuzzy logic, as well as tools for modeling a fuzzy intelligent system for making decisions about the current state of an object are analyzed. The fuzzy logic is investigated and the corresponding fuzzy inference algorithm is chosen. All possible states of an intelligent system are determined, membership functions are constructed. Based on expert decisions, the system’s rule base was formed. For the practical implementation of an intelligent decision-making system, an air pollution analysis system was developed. This system allows assessing and making decisions about the current state of indoor air pollution.","PeriodicalId":312916,"journal":{"name":"2020 IEEE 2nd International Conference on Advanced Trends in Information Theory (ATIT)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"25","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 2nd International Conference on Advanced Trends in Information Theory (ATIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ATIT50783.2020.9349334","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 25
Abstract
The paper investigates the problem of using fuzzy logic to build intelligent decision-making systems. The directions of application of fuzzy logic, as well as tools for modeling a fuzzy intelligent system for making decisions about the current state of an object are analyzed. The fuzzy logic is investigated and the corresponding fuzzy inference algorithm is chosen. All possible states of an intelligent system are determined, membership functions are constructed. Based on expert decisions, the system’s rule base was formed. For the practical implementation of an intelligent decision-making system, an air pollution analysis system was developed. This system allows assessing and making decisions about the current state of indoor air pollution.