Open AccessThe Best Way to Access Gas Stations using Fuzzy Logic Controller in a Neutrosophic Environment
Author(s) -
Muhammad Naveed Jafar,
Muhammad Saqlain,
Aasia Mansoob,
Asma Riffat
Publication year - 2020
Publication title -
scientific inquiry and review
Language(s) - English
Resource type - Journals
eISSN - 2521-2435
pISSN - 2521-2427
DOI - 10.32350/sir.41.03
Subject(s) - toolbox , fuzzy logic , computer science , controller (irrigation) , matlab , fuzzy inference system , data mining , inference , real time computing , fuzzy control system , artificial intelligence , adaptive neuro fuzzy inference system , programming language , agronomy , biology
These days, Google Map is used to find any location and/or to define the route to any given place. Its accuracy is up to 30 meters but if neutrosophic numbers are used, it gives more accuracy. To check the implementation of neutrosophic numbers in Google Map, a system is developed based on Fuzzy Logic Controller (FLC) using neutrosophic numbers to find the gas station which is nearest, less parking car units and with few traffic signals on the way. In this way, it takes less time to reach the available gas station. This system enables the driver to find a fuel station with more accuracy. We took five linguistic inputs including distance, gas availability, parking car unit, amount of gas, and the number of traffic signals to get one output, that is, time. We assigned different neutrosophic soft sets to each linguistic input. FLC inference was designed using 108 rules based on if-then statements to select time to reach the gas station. The results were veried by MATLAB’s Fuzzy Logic Toolbox.