Assessing the Impacting Factors in Prediction of Parliamentary Elections Turnout Using Heuristics and Devising MIP Algorithmic Model

Abstract

The research focus is on identifying and assessing the impacting factors to be measured in order to realize prediction of parliamentary elections outcome using the (MIP) algorithmic model. We have developed a novel method for recognizing the main impacting factors in elections using the (MIP) algorithmic model. We have firstly used adaptive heuristics. In order to devise and asses the impacting factors we have devised most-important-problem (MIP) algorithmic model to predict the outcome of Kosovo parliamentary elections and grounded it on the TTB (take-the-best) strategy. An analysis of forecasting approach to elections and the performance metrics (variance) using the (MIP) algorithmic model has been used. provided are all the main variables we have measured. We have provided posterior binomial proportion. This method is very popular when modelling geopolitical situations with complex dynamics in the system. The data has derived from an originally collected survey dataset that contains the impacting factors previously identified and assessed regarding the parliamentary elections in Kosovo has been realized.