PYTHON APPROACH: A FUZZY TIME SERIES FORECASTING TECHNIQUE IS USED TO PREDICT ONLINE RETAIL FOR FUEL BOOKING SERVICES

This paper describes the implementation of the Fuzzy Time Series approach, which was produced by estimating the interval length using the distribution method. The duration of the interval is critical in the fuzzy forecasting approach since it affects the accuracy of the predicting findings. The goal of developing this forecasting model is to achieve higher predicting accuracy. In this analysis, Statistical data on fuel bookings in online shopping were utilized to test the methodology on a certain day. The Python programming language is utilized during data processing. Based on the FTS method's accuracy test, it is possible to conclude that this technique gives better forecasting outcomes.