A Master's Thesis at the University of Basra Explores Specific, Parametric, and Algorithmic Methods for Estimating the Reliability Function of the Alpha Power Frechet Distribution with Application

A Master's Thesis at the University of Basra Explores Specific, Parametric, and Algorithmic Methods for Estimating the Reliability Function of the Alpha Power Frechet Distribution with Application

A Master's thesis at the College of Administration and Management in Basra explored the use of parametric, non-parametric, and algorithmic methods for estimating the reliability function of the Alpha Power Frechet distribution with application.

The thesis, presented by student Redha Adel Nasser, compared the parametric, non-parametric, and new algorithmic mobility coefficients in the classification of the Alpha Power Frechet distribution, which utilizes power tail reliability data. As a result, the thesis derived the mathematical gain of the distribution and applied it to real-world data from industrial pumps.

The thesis recommended integrating traditional methods with increasingly sophisticated artificial intelligence techniques and predictive systems.