APPLICATION OF THE INVERSE WEIBULL DISTRIBUTION TO AGRICULTURAL DATA USING FUZZY PARAMETER INTERVALS

Abstract

In several scientific fields, the inverse Weibull distribution (IWD) is widely used as a model
for dependability analysis. This paper's main objective is to develop a linear, exponential loss
function based on lowest record values for the Inverse Weibull Distribution's dependability
value and variables. After weighting the LXLF in the construction of the current function
loss, the modified linear, exponential loss function (WLXLF) was given its name. Next,
estimate the Inverse Weibull distribution's parameters and reliability functions using
WLXLF. This paper uses real-time data to estimate the parameter intervals for the inverse
Weibull distribution using two estimation methods. The maximum likelihood approach and
the relative maximum likelihood method are the foundations of these two tactics.
Additionally, we assess how relative maximum likelihood intervals for actual datasets
compare to maximum likelihood intervals. Consequently, determining the values of the
IWD's maximum likelihood intervals using fuzzy parameters inside the Corresponding realtime problem's interval. Using a fuzzy range of parameter values for real-time data, the
present study investigated the probability density function, cumulative density function, andhazard rate function of the inverse Weibull distribution. We examined Tamil Nadu's
agricultural output in 2018 in this research. It was thus shown from the comparison that the
fuzziness interval estimate performs better than the real-time data.