an application of fuzzy time series with different universal discourse interval lengths for rice production in india

In this paper, we offered a fts-based tutorial on rice farming in india. the relevant literature is reviewed, which serves as a basis for the main concepts and models based on different forms of fts forecasts. in an effort to inspire readers to contribute to this field of study, we also highlight the challenges and recent work that aims to fill in some of these knowledge gaps. finally, time series forecasting is a useful tool for organizing and making decisions. an increasing number of methods, ranging from traditional statistical models to soft computing and artificial intelligence approaches, have been developed to generate increasingly accurate forecasts. pyfts is an open-source, free python library created by the laboratory of machine intelligence and data science that implements a number of fts models that have been published in the literature. in order to determine the interval in the fuzzy time series, chen's method of fts, comparing numerous values of n (number of interval) is used in this paper. we are interested to minimizing the mse in the forecasting using pyfts.