Predicting Marital Satisfaction Using a Combination of Genetic Algorithm and Fuzzy Inference

Many young individuals consider a successful marriage as an immensely important goal in their lives. Consequently, extensive research has been conducted to determine the factors influencing the success or failure of marital unions. However, thus far, there has been no satisfactory scientific method proposed to predict the success of marriages. This article examines the features that affect the success of a marriage and presents a solution through which the likelihood of success or failure in a marriage can be predicted. To achieve this goal, a combination of genetic algorithm and fuzzy inference system techniques has been employed. The fuzzy rules proposed by the genetic algorithm are optimized for constructing a model to detect and predict success in marriages. The results of implementing this proposed combined system demonstrate significant enhancements in algorithm performance, yielding notably optimized solutions and predictions compared to conventional machine learning systems.

Predicting Marital Satisfaction Using a Combination of Genetic Algorithm and Fuzzy Inference Keywords:

Marital Satisfaction , predicting marital success , genetic algorithm , fuzzy inference system